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Articles by Jean-Philippe Thiran in JoVE

 JoVE Clinical and Translational Medicine

Yerel Gyrification Endeksi hesapla Adım Adım Öğretici: MR Görüntüleri Kortikal Katlama nasıl ölçülür


JoVE 3417 1/02/2012

1, 2,3, 4, 4, 2, 1

1Department of Psychiatry, University of Geneva School of Medicine, 2Signal Processing Laboratory, École Polytechnique Fédérale de Lausanne, 3Department of Radiology, University Hospital Center and University of Lausanne, 4Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital

Ölçüm gyrification (kortikal katlama) herhangi bir yaşta, erken beyin gelişiminde bir pencere temsil eder. Bu nedenle, daha önce yarımkürede üzerinde puan binlerce yerel gyrification ölçmek için bir algoritma geliştirdi

Other articles by Jean-Philippe Thiran on PubMed

Prognostic Accuracy of Cerebral Blood Flow Measurement by Perfusion Computed Tomography, at the Time of Emergency Room Admission, in Acute Stroke Patients

Annals of Neurology. Apr, 2002  |  Pubmed ID: 11921048

The purpose of this study was to determine the prognostic accuracy of perfusion computed tomography (CT), performed at the time of emergency room admission, in acute stroke patients. Accuracy was determined by comparison of perfusion CT with delayed magnetic resonance (MR) and by monitoring the evolution of each patient's clinical condition. Twenty-two acute stroke patients underwent perfusion CT covering four contiguous 10mm slices on admission, as well as delayed MR, performed after a median interval of 3 days after emergency room admission. Eight were treated with thrombolytic agents. Infarct size on the admission perfusion CT was compared with that on the delayed diffusion-weighted (DWI)-MR, chosen as the gold standard. Delayed magnetic resonance angiography and perfusion-weighted MR were used to detect recanalization. A potential recuperation ratio, defined as PRR = penumbra size/(penumbra size + infarct size) on the admission perfusion CT, was compared with the evolution in each patient's clinical condition, defined by the National Institutes of Health Stroke Scale (NIHSS). In the 8 cases with arterial recanalization, the size of the cerebral infarct on the delayed DWI-MR was larger than or equal to that of the infarct on the admission perfusion CT, but smaller than or equal to that of the ischemic lesion on the admission perfusion CT; and the observed improvement in the NIHSS correlated with the PRR (correlation coefficient = 0.833). In the 14 cases with persistent arterial occlusion, infarct size on the delayed DWI-MR correlated with ischemic lesion size on the admission perfusion CT (r = 0.958). In all 22 patients, the admission NIHSS correlated with the size of the ischemic area on the admission perfusion CT (r = 0.627). Based on these findings, we conclude that perfusion CT allows the accurate prediction of the final infarct size and the evaluation of clinical prognosis for acute stroke patients at the time of emergency evaluation. It may also provide information about the extent of the penumbra. Perfusion CT could therefore be a valuable tool in the early management of acute stroke patients.

What and Where in Human Audition: Selective Deficits Following Focal Hemispheric Lesions

Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale. Nov, 2002  |  Pubmed ID: 12373363

A sound that we hear in a natural setting allows us to identify the sound source and localize it in space. The two aspects can be disrupted independently as shown in a study of 15 patients with focal right-hemispheric lesions. Four patients were normal in sound recognition but severely impaired in sound localization, whereas three other patients had difficulties in recognizing sounds but localized them well. The lesions involved the inferior parietal and frontal cortices, and the superior temporal gyrus in patients with selective sound localization deficit; and the temporal pole and anterior part of the fusiform, inferior and middle temporal gyri in patients with selective recognition deficit. These results suggest separate cortical processing pathways for auditory recognition and localization.

Lossy to Lossless Object-based Coding of 3-D MRI Data

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society. 2002  |  Pubmed ID: 18249726

We propose a fully three-dimensional (3-D) object-based coding system exploiting the diagnostic relevance of the different regions of the volumetric data for rate allocation. The data are first decorrelated via a 3-D discrete wavelet transform. The implementation via the lifting steps scheme allows to map integer-to-integer values, enabling lossless coding, and facilitates the definition of the object-based inverse transform. The coding process assigns disjoint segments of the bitstream to the different objects, which can be independently accessed and reconstructed at any up-to-lossless quality. Two fully 3-D coding strategies are considered: embedded zerotree coding (EZW-3D) and multidimensional layered zero coding (MLZC), both generalized for region of interest (ROI)-based processing. In order to avoid artifacts along region boundaries, some extra coefficients must be encoded for each object. This gives rise to an overheading of the bitstream with respect to the case where the volume is encoded as a whole. The amount of such extra information depends on both the filter length and the decomposition depth. The system is characterized on a set of head magnetic resonance images. Results show that MLZC and EZW-3D have competitive performances. In particular, the best MLZC mode outperforms the others state-of-the-art techniques on one of the datasets for which results are available in the literature.

Application of Adaptive Image Processing Technique to Real-time Spatial Compound Ultrasound Imaging Improves Image Quality

Investigative Radiology. May, 2003  |  Pubmed ID: 12750614

To assess the impact of adaptive filter postprocessing on quality of ultrasound images.

Three-dimensional Encoding/two-dimensional Decoding of Medical Data

IEEE Transactions on Medical Imaging. Mar, 2003  |  Pubmed ID: 12760559

We propose a fully three-dimensional (3-D) wavelet-based coding system featuring 3-D encoding/two-dimensional (2-D) decoding functionalities. A fully 3-D transform is combined with context adaptive arithmetic coding; 2-D decoding is enabled by encoding every 2-D subband image independently. The system allows a finely graded up to lossless quality scalability on any 2-D image of the dataset. Fast access to 2-D images is obtained by decoding only the corresponding information thus avoiding the reconstruction of the entire volume. The performance has been evaluated on a set of volumetric data and compared to that provided by other 3-D as well as 2-D coding systems. Results show a substantial improvement in coding efficiency (up to 33%) on volumes featuring good correlation properties along the z axis. Even though we did not address the complexity issue, we expect a decoding time of the order of one second/image after optimization. In summary, the proposed 3-D/2-D multidimensional layered zero coding system provides the improvement in compression efficiency attainable with 3-D systems without sacrificing the effectiveness in accessing the single images characteristic of 2-D ones.

Sound Recognition and Localization in Man: Specialized Cortical Networks and Effects of Acute Circumscribed Lesions

Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale. Dec, 2003  |  Pubmed ID: 14504861

Functional imaging studies have shown that information relevant to sound recognition and sound localization are processed in anatomically distinct cortical networks. We have investigated the functional organization of these specialized networks by evaluating acute effects of circumscribed hemispheric lesions. Thirty patients with a primary unilateral hemispheric lesion, 15 with right-hemispheric damage (RHD) and 15 with left-hemispheric damage (LHD), were evaluated for their capacity to recognise environmental sounds, to localize sounds in space and to perceive sound motion. One patient with RHD and 2 with LHD had a selective deficit in sound recognition; 3 with RHD a selective deficit in sound localization; 2 with LHD a selective deficit in sound motion perception; 4 with RHD and 3 with LHD a combined deficit of sound localization and motion perception; 2 with RHD and 1 with LHD a combined deficit of sound recognition and motion perception; and 1 with LHD a combined deficit of sound recognition, localization and motion perception. Five patients with RHD and 6 with LHD had normal performance in all three domains. Deficient performance in sound recognition, sound localization and/or sound motion perception was always associated with a lesion that involved the shared auditory structures and the specialized What and/or Where networks, while normal performance was associated with lesions within or outside these territories. Thus, damage to regions known to be involved in auditory processing in normal subjects is necessary, but not sufficient for a deficit to occur. Lesions of a specialized network was not always associated with the corresponding deficit. Conversely, specific deficits tended not be associated predominantly with lesions of the corresponding network; e.g. deficits in auditory spatial tasks were observed in patients whose lesions involved to a larger extent the shared auditory structures and the specialized What network than the specialized Where network, and deficits in sound recognition in patients whose lesions involved mostly the shared auditory structures and to a varying degree the specialized What network. The human auditory cortex consists of functionally defined auditory areas, whose intrinsic organization is currently not understood. In particular, areas involved in the What and Where pathways can be conceived as: (1) specialized regions, in which lesions cause dysfunction limited to the damaged part; observed deficits should be then related to the specialization of the damaged region and their magnitude to the extent of the damage; or (2) specialized networks, in which lesions cause dysfunction that may spread over the two specialized networks; observed deficits may then not be related to the damaged region and their magnitude not proportional to the extent of the damage. Our results support strongly the network hypothesis.

Unilateral Hemispheric Lesions Disrupt Parallel Processing Within the Contralateral Intact Hemisphere: an Auditory FMRI Study

NeuroImage. Nov, 2003  |  Pubmed ID: 14597298

Evidence from activation studies suggests that sound recognition and localization are processed in two distinct cortical networks that are each present in both hemispheres. Sound recognition and/or localization may, however, be disrupted by purely unilateral damage, suggesting that processing within one hemisphere may not be sufficient or may be disturbed by the contralateral lesion. Sound recognition and localization were investigated psychophysically and using fMRI in patients with unilateral right hemisphere lesions. Two patients had a combined deficit in sound recognition and sound localization, two a selective deficit in sound localization, one a selective deficit in sound recognition, and two normal performance in both tasks. The overall level of activation in the intact left hemisphere of the patients was smaller than in normal control subjects, irrespective of whether the patient's performance in the psychophysical tasks was impaired. Despite this overall decrease in activation strength, patients with normal performance still exhibited activation patterns similar to those of the control subjects in the recognition and localization tasks, indicating that the specialized brain networks subserving sound recognition and sound localization in normal subjects were also activated in the patients with normal performance, albeit to an altogether lesser degree. In patients with deficient performance, on the other hand, the activation patterns during the sound recognition and localization tasks were severely reduced, comprising fewer and partly atypical activation foci compared to the normal subjects. This indicates that impaired psychophysical performance correlates with a breakdown of parallel processing within specialized networks in the contralesional hemisphere.

An Open Internet Platform to Distributed Image Processing Applied to Dermoscopy

Studies in Health Technology and Informatics. 2003  |  Pubmed ID: 14663971

Proprietary systems for dermoscopy images analysis are available to improve the diagnosis and follow-up of the pigmented skin lesions. Their performance seems comparable with that of a human expert. Progress in computer-aided classification of melanocytic lesions depends notably on judicious choices of the algorithms dedicated to the extraction of signs from the dermoscopy images and of the method which combines these signs to classify the lesions. To allow the researcher's community to benefit from their large set of elementary algorithms already available for dermoscopy, we set up a system accessible through the Internet which: allows the engineers to register their algorithms while preserving their secrecy: their programs run on their own server; lets a user to define its own sequence of image analysis and to apply it to its images: the system automatically calls the appropriate remote programs; makes possible and stimulates the synergy of worldwide researchers in order to validate algorithms of images analysis best suited to achieve the correct diagnosis and to track the malignant melanoma; makes these techniques available to the greatest number of users through the Web and thus to support a mass screening; reduces the maintenance of the system to the minimum: it requires users only an Internet browser and engineers to follow a simple widespread standardised interface for distributed programs. Various problems should be addressed: the lack of standardisation of images acquisition: algorithms based on relative colours are best suited to this system; the copyrights on images and algorithms; charging the use of remote computer resources. This system allows for an international collaborative work in the fight against the malignant melanoma by offering a conceptual and technical platform of teledermoscopy. It is intended to support synergy between the engineers and the users implied in the diagnosis and teaching of dermoscopy.

Atlas-based Segmentation of Pathological MR Brain Images Using a Model of Lesion Growth

IEEE Transactions on Medical Imaging. Oct, 2004  |  Pubmed ID: 15493697

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Segmentation of Brain Structures in Presence of a Space-occupying Lesion

NeuroImage. Feb, 2005  |  Pubmed ID: 15670676

Brain deformations induced by space-occupying lesions may result in unpredictable position and shape of functionally important brain structures. The aim of this study is to propose a method for segmentation of brain structures by deformation of a segmented brain atlas in presence of a space-occupying lesion. Our approach is based on an a priori model of lesion growth (MLG) that assumes radial expansion from a seeding point and involves three steps: first, an affine registration bringing the atlas and the patient into global correspondence; then, the seeding of a synthetic tumor into the brain atlas providing a template for the lesion; finally, the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. The method was applied on two meningiomas inducing a pure displacement of the underlying brain structures, and segmentation accuracy of ventricles and basal ganglia was assessed. Results show that the segmented structures were consistent with the patient's anatomy and that the deformation accuracy of surrounding brain structures was highly dependent on the accurate placement of the tumor seeding point. Further improvements of the method will optimize the segmentation accuracy. Visualization of brain structures provides useful information for therapeutic consideration of space-occupying lesions, including surgical, radiosurgical, and radiotherapeutic planning, in order to increase treatment efficiency and prevent neurological damage.

White Matter Fiber Tract Segmentation in DT-MRI Using Geometric Flows

Medical Image Analysis. Jun, 2005  |  Pubmed ID: 15854843

In this paper, we present a 3D geometric flow designed to segment the main core of fiber tracts in diffusion tensor magnetic resonance images. The fundamental assumption of our fiber segmentation technique is that adjacent voxels in a tract have similar properties of diffusion. The fiber segmentation is carried out with a front propagation algorithm constructed to fill the whole fiber tract. The front is a 3D surface that evolves with a propagation speed proportional to a measure indicating the similarity of diffusion between the tensors lying on the surface and their neighbors in the direction of propagation. We use a level set implementation to assure a stable and accurate evolution of the surface and to handle changes of topology of the surface during the evolution process. The fiber tract segmentation method does not need a regularized tensor field since the surface is automatically smoothed as it propagates. The smoothing is done by an intrinsic surface force, based on the minimal principal curvature. This segmentation can be used for obtaining quantitative measures of the diffusion in the fiber tracts and it can also be used for white matter registration and for surgical planning.

Ultrasound Measurement of the Fibrous Cap in Symptomatic and Asymptomatic Atheromatous Carotid Plaques

Circulation. May, 2005  |  Pubmed ID: 15911699

Fibrous cap thickness (FCT) is an important determinant of atheroma stability. We evaluated the feasibility and potential clinical implications of measuring the FCT of internal carotid artery plaques with a new ultrasound system based on boundary detection by dynamic programming.

Comparison and Validation of Tissue Modelization and Statistical Classification Methods in T1-weighted MR Brain Images

IEEE Transactions on Medical Imaging. Dec, 2005  |  Pubmed ID: 16350916

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Cross Validation of Experts Versus Registration Methods for Target Localization in Deep Brain Stimulation

Medical Image Computing and Computer-assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 2005  |  Pubmed ID: 16685873

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

Representing Diffusion MRI in 5D for Segmentation of White Matter Tracts with a Level Set Method

Information Processing in Medical Imaging : Proceedings of the ... Conference. 2005  |  Pubmed ID: 17354705

We present a method for segmenting white matter tracts from high angular resolution diffusion MR. images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the position-orientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.

Fibertract Segmentation in Position Orientation Space from High Angular Resolution Diffusion MRI

NeuroImage. Aug, 2006  |  Pubmed ID: 16815713

In diffusion MRI, standard approaches for fibertract identification are based on algorithms that generate lines of coherent diffusion, currently known as tractography. A tract is then identified as a set of such lines selected on some criteria. In the present study, we investigate whether fibertract identification can be formulated as a segmentation task that recognizes a fibertract as a region where diffusion is intense and coherent. Indeed, we show that it is possible to segment efficiently well-known fibertracts with classical image processing methods provided that the problem is formulated in a five-dimensional space of position and orientation. As an example, we choose to adapt to this newly defined high-dimensional non-Euclidean space, called position orientation space, an algorithm based on the hidden Markov random field framework. Structures such as the cerebellar peduncles, corticospinal tract, association bundles can be identified and represented in three dimensions by a back projection technique similar to maximum intensity projection. Potential advantages and drawbacks as compared to classical tractography are discussed; for example, it appears that our formulation handles naturally crossing tracts and is not biased by human intervention.

Hand Preference and Sex Shape the Architecture of Language Networks

Human Brain Mapping. Oct, 2006  |  Pubmed ID: 16541458

In right-handed subjects, language processing relies predominantly on left hemisphere networks, more so in men than in women, and in right- versus left-handers. Using DT-MRI tractography, we have shown that right-handed men are massively interconnected between the left-hemisphere language areas, whereas the homologous in the right hemisphere are sparse; interhemispheric connections between the language areas and their contralateral homologues are relatively strong. Women and left-handed men have equally strong intrahemispheric connections in both hemispheres, but women have a higher density of interhemispheric connections.

Human Auditory Belt Areas Specialized in Sound Recognition: a Functional Magnetic Resonance Imaging Study

Neuroreport. Nov, 2006  |  Pubmed ID: 17047449

The human primary auditory cortex is surrounded by at least six other, anatomically distinct areas that process auditory information. We have investigated their specialization with respect to sound recognition or sound localization with triple epoch functional magnetic resonance imaging paradigm (recognition-localization-rest) in 18 normal individuals. In each study participant, the pattern of selective activation by the recognition or by the localization tasks was superimposed on the map of the nonprimary auditory areas, as identified in previous anatomical studies. Two areas, anterior lateral and anterior areas, were activated bilaterally in significantly more individuals by the recognition than by the localization task. They are proposed to be human homologues of macaque anterolateral auditory belt area.

Understanding Diffusion MR Imaging Techniques: from Scalar Diffusion-weighted Imaging to Diffusion Tensor Imaging and Beyond

Radiographics : a Review Publication of the Radiological Society of North America, Inc. Oct, 2006  |  Pubmed ID: 17050517

The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.

A Cross Validation Study of Deep Brain Stimulation Targeting: from Experts to Atlas-based, Segmentation-based and Automatic Registration Algorithms

IEEE Transactions on Medical Imaging. Nov, 2006  |  Pubmed ID: 17117773

Validation of image registration algorithms is a difficult task and open-ended problem, usually application-dependent. In this paper, we focus on deep brain stimulation (DBS) targeting for the treatment of movement disorders like Parkinson's disease and essential tremor. DBS involves implantation of an electrode deep inside the brain to electrically stimulate specific areas shutting down the disease's symptoms. The subthalamic nucleus (STN) has turned out to be the optimal target for this kind of surgery. Unfortunately, the STN is in general not clearly distinguishable in common medical imaging modalities. Usual techniques to infer its location are the use of anatomical atlases and visible surrounding landmarks. Surgeons have to adjust the electrode intraoperatively using electrophysiological recordings and macrostimulation tests. We constructed a ground truth derived from specific patients whose STNs are clearly visible on magnetic resonance (MR) T2-weighted images. A patient is chosen as atlas both for the right and left sides. Then, by registering each patient with the atlas using different methods, several estimations of the STN location are obtained. Two studies are driven using our proposed validation scheme. First, a comparison between different atlas-based and nonrigid registration algorithms with a evaluation of their performance and usability to locate the STN automatically. Second, a study of which visible surrounding structures influence the STN location. The two studies are cross validated between them and against expert's variability. Using this scheme, we evaluated the expert's ability against the estimation error provided by the tested algorithms and we demonstrated that automatic STN targeting is possible and as accurate as the expert-driven techniques currently used. We also show which structures have to be taken into account to accurately estimate the STN location.

Visuo-motor Pathways in Humans Revealed by Event-related FMRI

Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale. Apr, 2006  |  Pubmed ID: 16307262

Whether different brain networks are involved in generating unimanual responses to a simple visual stimulus presented in the ipsilateral versus contralateral hemifield remains a controversial issue. Visuo-motor routing was investigated with event-related functional magnetic resonance imaging (fMRI) using the Poffenberger reaction time task. A 2 hemifield x 2 response hand design generated the "crossed" and "uncrossed" conditions, describing the spatial relation between these factors. Both conditions, with responses executed by the left or right hand, showed a similar spatial pattern of activated areas, including striate and extrastriate areas bilaterally, SMA, and M1 contralateral to the responding hand. These results demonstrated that visual information is processed bilaterally in striate and extrastriate visual areas, even in the "uncrossed" condition. Additional analyses based on sorting data according to subjects' reaction times revealed differential crossed versus uncrossed activity only for the slowest trials, with response strength in infero-temporal cortices significantly correlating with crossed-uncrossed differences (CUD) in reaction times. Collectively, the data favor a parallel, distributed model of brain activation. The presence of interhemispheric interactions and its consequent bilateral activity is not determined by the crossed anatomic projections of the primary visual and motor pathways. Distinct visuo-motor networks need not be engaged to mediate behavioral responses for the crossed visual field/response hand condition. While anatomical connectivity heavily influences the spatial pattern of activated visuo-motor pathways, behavioral and functional parameters appear to also affect the strength and dynamics of responses within these pathways.

Localization of Electrodes in the Subthalamic Nucleus on Magnetic Resonance Imaging

Journal of Neurosurgery. Jan, 2007  |  Pubmed ID: 17240554

The authors describe a new method of localizing electrodes on magnetic resonance (MR) images and focus on the positions of both the most efficient contact and the electrode related to the MR imaging target.

Multisensory Interactions Within Human Primary Cortices Revealed by BOLD Dynamics

Cerebral Cortex (New York, N.Y. : 1991). Jul, 2007  |  Pubmed ID: 16968869

Whether signals from different sensory modalities converge and interact within primary cortices in humans is unresolved, despite emerging evidence in animals. This is partially because of debates concerning the appropriate analyses of functional magnetic resonance imaging (fMRI) data in response to multisensory phenomena. Using event-related fMRI, we observed that simple auditory stimuli (noise bursts) activated primary visual cortices and that simple visual stimuli (checkerboards) activated primary auditory cortices, indicative of multisensory convergence. Moreover, analyses of blood oxygen level-dependent response dynamics revealed facilitation of hemodynamic response peak latencies and slopes for multisensory auditory-visual stimuli versus either unisensory condition, indicative of multisensory interactions within primary sensory cortices. Neural processing at the lowest cortical levels can be modulated by interactions between the senses. Temporal information in fMRI data can reveal these modulations and overcome analytic and interpretational challenges of more traditional procedures. In addition to providing an essential translational link with animal models, these results suggest that longstanding notions of cortical organization need to be revised to include multisensory interactions as an inherent component of functional brain organization.

Scale Space Analysis and Active Contours for Omnidirectional Images

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society. Jul, 2007  |  Pubmed ID: 17605386

A new generation of optical devices that generate images covering a larger part of the field of view than conventional cameras, namely catadioptric cameras, is slowly emerging. These omnidirectional images will most probably deeply impact computer vision in the forthcoming years, provided that the necessary algorithmic background stands strong. In this paper, we propose a general framework that helps define various computer vision primitives. We show that geometry, which plays a central role in the formation of omnidirectional images, must be carefully taken into account while performing such simple tasks as smoothing or edge detection. Partial differential equations (PDEs) offer a very versatile tool that is well suited to cope with geometrical constraints. We derive new energy functionals and PDEs for segmenting images obtained from catadioptric cameras and show that they can be implemented robustly using classical finite difference schemes. Various experimental results illustrate the potential of these new methods on both synthetic and natural images.

Mapping Human Whole-brain Structural Networks with Diffusion MRI

PloS One. 2007  |  Pubmed ID: 17611629

Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

Representing Diffusion MRI in 5-D Simplifies Regularization and Segmentation of White Matter Tracts

IEEE Transactions on Medical Imaging. Nov, 2007  |  Pubmed ID: 18041269

We present a new five-dimensional (5-D) space representation of diffusion magnetic resonance imaging (dMRI) of high angular resolution. This 5-D space is basically a non-Euclidean space of position and orientation in which crossing fiber tracts can be clearly disentangled, that cannot be separated in three-dimensional position space. This new representation provides many possibilities for processing and analysis since classical methods for scalar images can be extended to higher dimensions even if the spaces are not Euclidean. In this paper, we show examples of how regularization and segmentation of dMRI is simplified with this new representation. The regularization is used with the purpose of denoising and but also to facilitate the segmentation task by using several scales, each scale representing a different level of resolution. We implement in five dimensions the Chan-Vese method combined with active contours without edges for the segmentation and the total variation functional for the regularization. The purpose of this paper is to explore the possibility of segmenting white matter structures directly as entirely separated bundles in this 5-D space. We will present results from a synthetic model and results on real data of a human brain acquired with diffusion spectrum magnetic resonance imaging (MRI), one of the dMRI of high angular resolution available. These results will lead us to the conclusion that this new high-dimensional representation indeed simplifies the problem of segmentation and regularization.

A Surface-based Approach to Quantify Local Cortical Gyrification

IEEE Transactions on Medical Imaging. Feb, 2008  |  Pubmed ID: 18334438

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

An Active Contour-based Atlas Registration Model Applied to Automatic Subthalamic Nucleus Targeting on MRI: Method and Validation

Medical Image Computing and Computer-assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. 2008  |  Pubmed ID: 18982700

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Estimating the Confidence Level of White Matter Connections Obtained with MRI Tractography

PloS One. 2008  |  Pubmed ID: 19104666

Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics.

Congenital Heart Disease Affects Local Gyrification in 22q11.2 Deletion Syndrome

Developmental Medicine and Child Neurology. Sep, 2009  |  Pubmed ID: 19416334

22q11.2 deletion syndrome (22q11.2DS) is a common genetic condition associated with cognitive and learning impairments. In this study, we applied a three-dimensional method for quantifying gyrification at thousands of points over the cortical surface to imaging data from 44 children, adolescents, and young adults with 22q11.2DS (17 males, 27 females; mean age 17y 2mo [SD 9y 1mo], range 6-37y), and 53 healthy participants (21 males, 32 females; mean age 15y 4mo [SD 8y 6mo]; range 6-40y). Several clusters of reduced gyrification were observed, further substantiating the pattern of cerebral alterations presented by children with the syndrome. Comparisons within 22q11.2DS demonstrated an effect of congenital heart disease (CHD) on cortical gyrification, with reduced gyrification at the parieto-temporo-occipital junction in patients with CHD, as compared with patients without CHD. Reductions in gyrification can resemble mild polymicrogyria, suggesting early abnormal neuronal proliferation or migration and providing support for an effect of hemodynamic factors on brain development in 22q11.2DS. The results also shed light on the pathophysiology of acquired brain injury in other populations with CHD.

Automatic Quality Assessment in Structural Brain Magnetic Resonance Imaging

Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine. Aug, 2009  |  Pubmed ID: 19526493

MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.

Deviant Trajectories of Cortical Maturation in 22q11.2 Deletion Syndrome (22q11DS): a Cross-sectional and Longitudinal Study

Schizophrenia Research. Dec, 2009  |  Pubmed ID: 19836927

22q11.2 deletion syndrome (22q11DS) is associated with an increased susceptibility to develop schizophrenia. Despite a large body of literature documenting abnormal brain structure in 22q11DS, cerebral changes associated with brain maturation in 22q11DS remained largely unexplored. To map cortical maturation from childhood to adulthood in 22q11.2 deletion syndrome, we used cerebral MRI from 59 patients with 22q11DS, aged 6 to 40, and 80 typically developing controls; three year follow-up assessments were also available for 32 patients and 31 matched controls. Cross-sectional cortical thickness trajectories during childhood and adolescence were approximated in age bins. Repeated-measures were also conducted with the longitudinal data. Within the group of patients with 22q11DS, exploratory measures of cortical thickness differences related to COMT polymorphism, IQ, and schizophrenia were also conducted. We observed deviant trajectories of cortical thickness changes with age in patients with 22q11DS. In affected preadolescents, larger prefrontal thickness was observed compared to age-matched controls. Afterward, we observed greater cortical loss in 22q11DS with a convergence of cortical thickness values by the end of adolescence. No compelling evidence for an effect of COMT polymorphism on cortical maturation was observed. Within 22q11DS, significant differences in cortical thickness were related to cognitive level in children and adolescents, and to schizophrenia in adults. Deviant trajectories of cortical thickness from childhood to adulthood provide strong in vivo cues for a defect in the programmed synaptic elimination, which in turn may explain the susceptibility of patients with 22q11DS to develop psychosis.

Methods for Determining Frequency- and Region-dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

Journal of Neurophysiology. Jan, 2009  |  Pubmed ID: 19005004

The relationship between electrophysiological and functional magnetic resonance imaging (fMRI) signals remains poorly understood. To date, studies have required invasive methods and have been limited to single functional regions and thus cannot account for possible variations across brain regions. Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0-256 Hz) throughout the entire brain volume. This method was applied in a study where human subjects completed separate fMRI and EEG sessions while performing a passive visual task. Intracranial LFPs were estimated from the scalp-recorded data using the ELECTRA source model. We compared statistical images from BOLD signals with statistical images of each frequency of the eLFPs. In agreement with previous studies in animals, we found a significant correspondence between LFP and BOLD statistical images in the gamma band (44-78 Hz) within primary visual cortices. In addition, significant correspondence was observed at low frequencies (<14 Hz) and also at very high frequencies (>100 Hz). Effects within extrastriate visual areas showed a different correspondence that not only included those frequency ranges observed in primary cortices but also additional frequencies. Results therefore suggest that the relationship between electrophysiological and hemodynamic signals thus might vary both as a function of frequency and anatomical region.

Local Landmark-based Registration for FMRI Group Studies of Nonprimary Auditory Cortex

NeuroImage. Jan, 2009  |  Pubmed ID: 18760369

Interindividual functional and structural brain variability is a major problem in group studies, in which very focal activations are expected. Architectonic studies have shown that the human primary auditory area, which is located with a great constancy on Heschl's gyrus, is surrounded by several nonprimary auditory areas with surface areas of 40-310 mm(2). The small size of the latter makes them only partially accessible to fMRI group studies, because of imprecision in realignment when using currently available registration procedures. We describe here a new method for sulcal realignment using a non-rigid local landmark-based registration and show its application to the registration of fMRI acquisitions on the supratemporal plane. After an affine global voxel-based registration, which transforms all brains into the same standard space, we propose a non-rigid local landmark-based registration method based on thin-plate splines for matching the two sulci delimiting Heschl's gyrus of a given brain to the corresponding sulci of a reference brain. We show here that, in comparison with global affine and non-rigid approaches, our method leads in group studies to i) a much more precise alignment of Heschl's gyrus; and ii) a putatively optimal superposition of functionally corresponding areas on and around Heschl's gyrus.

Influence of the Implanted Pulse Generator As Reference Electrode in Finite Element Model of Monopolar Deep Brain Stimulation

Journal of Neuroscience Methods. Jan, 2010  |  Pubmed ID: 19895845

Electrical deep brain stimulation (DBS) is an efficient method to treat movement disorders. Many models of DBS, based mostly on finite elements, have recently been proposed to better understand the interaction between the electrical stimulation and the brain tissues. In monopolar DBS, clinically widely used, the implanted pulse generator (IPG) is used as reference electrode (RE). In this paper, the influence of the RE model of monopolar DBS is investigated. For that purpose, a finite element model of the full electric loop including the head, the neck and the superior chest is used. Head, neck and superior chest are made of simple structures such as parallelepipeds and cylinders. The tissues surrounding the electrode are accurately modelled from data provided by the diffusion tensor magnetic resonance imaging (DT-MRI). Three different configurations of RE are compared with a commonly used model of reduced size. The electrical impedance seen by the DBS system and the potential distribution are computed for each model. Moreover, axons are modelled to compute the area of tissue activated by stimulation. Results show that these indicators are influenced by the surface and position of the RE. The use of a RE model corresponding to the implanted device rather than the usually simplified model leads to an increase of the system impedance (+48%) and a reduction of the area of activated tissue (-15%).

MR Connectomics: Principles and Challenges

Journal of Neuroscience Methods. Dec, 2010  |  Pubmed ID: 20096730

MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.

JULIDE: a Software Tool for 3D Reconstruction and Statistical Analysis of Autoradiographic Mouse Brain Sections

PloS One. 2010  |  Pubmed ID: 21124830

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.

Regional Cortical Volumes and Congenital Heart Disease: a MRI Study in 22q11.2 Deletion Syndrome

Journal of Neurodevelopmental Disorders. Dec, 2010  |  Pubmed ID: 21125003

Children with congenital heart disease (CHD) who survive surgery often present impaired neurodevelopment and qualitative brain anomalies. However, the impact of CHD on total or regional brain volumes only received little attention. We address this question in a sample of patients with 22q11.2 deletion syndrome (22q11DS), a neurogenetic condition frequently associated with CHD. Sixty-one children, adolescents, and young adults with confirmed 22q11.2 deletion were included, as well as 80 healthy participants matched for age and gender. Subsequent subdivision of the patients group according to CHD yielded a subgroup of 27 patients with normal cardiac status and a subgroup of 26 patients who underwent cardiac surgery during their first years of life (eight patients with unclear status were excluded). Regional cortical volumes were extracted using an automated method and the association between regional cortical volumes, and CHD was examined within a three-condition fixed factor. Robust protection against type I error used Bonferroni correction. Smaller total cerebral volumes were observed in patients with CHD compared to both patients without CHD and controls. The pattern of bilateral regional reductions associated with CHD encompassed the superior parietal region, the precuneus, the fusiform gyrus, and the anterior cingulate cortex. Within patients, a significant reduction in the left parahippocampal, the right middle temporal, and the left superior frontal gyri was associated with CHD. The present results of global and regional volumetric reductions suggest a role for disturbed hemodynamic in the pathophysiology of brain alterations in patients with neurodevelopmental disease and cardiac malformations.

Active Deformation Fields: Dense Deformation Field Estimation for Atlas-based Segmentation Using the Active Contour Framework

Medical Image Analysis. Dec, 2011  |  Pubmed ID: 21646039

This paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and encompasses many of the state-of-the-art atlas-based segmentation methods. It also allows to perform the registration of atlas and target images based on only selected structures of interest. The versatility and potentiality of the proposed framework are demonstrated by presenting three diverse applications: In the first application, we show how the proposed framework can be used to simulate the growth of inconsistent structures like a tumor in an atlas. In the second application, we estimate the position of nonvisible brain structures based on the surrounding structures and validate the results by comparing with other methods. In the final application, we present the segmentation of lymph nodes in the Head and Neck CT images, and demonstrate how multiple registration forces can be used in this framework in an hierarchical manner.

The Connectome Viewer Toolkit: an Open Source Framework to Manage, Analyze, and Visualize Connectomes

Frontiers in Neuroinformatics. 2011  |  Pubmed ID: 21713110

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

Adaptive Strategy for the Statistical Analysis of Connectomes

PloS One. 2011  |  Pubmed ID: 21829681

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

Geodesic Active Fields--a Geometric Framework for Image Registration

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society. May, 2011  |  Pubmed ID: 21095870

In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inverse problem, which is usually solved by adding a regularization term. Here, we propose a multiplicative coupling between the registration term and the regularization term, which turns out to be equivalent to embed the deformation field in a weighted minimal surface problem. Then, the deformation field is driven by a minimization flow toward a harmonic map corresponding to the solution of the registration problem. This proposed approach for registration shares close similarities with the well-known geodesic active contours model in image segmentation, where the segmentation term (the edge detector function) is coupled with the regularization term (the length functional) via multiplication as well. As a matter of fact, our proposed geometric model is actually the exact mathematical generalization to vector fields of the weighted length problem for curves and surfaces introduced by Caselles-Kimmel-Sapiro. The energy of the deformation field is measured with the Polyakov energy weighted by a suitable image distance, borrowed from standard registration models. We investigate three different weighting functions, the squared error and the approximated absolute error for monomodal images, and the local joint entropy for multimodal images. As compared to specialized state-of-the-art methods tailored for specific applications, our geometric framework involves important contributions. Firstly, our general formulation for registration works on any parametrizable, smooth and differentiable surface, including nonflat and multiscale images. In the latter case, multiscale images are registered at all scales simultaneously, and the relations between space and scale are intrinsically being accounted for. Second, this method is, to the best of our knowledge, the first reparametrization invariant registration method introduced in the literature. Thirdly, the multiplicative coupling between the registration term, i.e. local image discrepancy, and the regularization term naturally results in a data-dependent tuning of the regularization strength. Finally, by choosing the metric on the deformation field one can freely interpolate between classic Gaussian and more interesting anisotropic, TV-like regularization.

Mapping the Human Connectome at Multiple Scales with Diffusion Spectrum MRI

Journal of Neuroscience Methods. Jan, 2012  |  Pubmed ID: 22001222

The global structural connectivity of the brain, the human connectome, is now accessible at millimeter scale with the use of MRI. In this paper, we describe an approach to map the connectome by constructing normalized whole-brain structural connection matrices derived from diffusion MRI tractography at 5 different scales. Using a template-based approach to match cortical landmarks of different subjects, we propose a robust method that allows (a) the selection of identical cortical regions of interest of desired size and location in different subjects with identification of the associated fiber tracts (b) straightforward construction and interpretation of anatomically organized whole-brain connection matrices and (c) statistical inter-subject comparison of brain connectivity at various scales. The fully automated post-processing steps necessary to build such matrices are detailed in this paper. Extensive validation tests are performed to assess the reproducibility of the method in a group of 5 healthy subjects and its reliability is as well considerably discussed in a group of 20 healthy subjects.

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