hydra-computer-based-platform-for-aiding-clinicians-cardiovascular

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Cardiovascular diseases (CVDs) are the leading cause of death throughout the world. The total risk of developing CVD is determined by the combined effect ...

University of A Coruña

Dry eye syndrome is affecting a remarkable percentage of population. The prevalence is 10-15% of normal population, and 18-30% of contact lenses users. The break-up time (BUT) is a clinical test used for the diagnosis of this disease. In this work, we perform an analysis of parameters for a global and a local automatic computation of the BUT measure, based on criteria of specificity and sensitivity. We have tested our methodology on a dataset composed of 18 videos annotated by 4 different experts. The local analysis preserves the results of the global approach providing useful additional information about the break-up tear zone. 

Analysis of parameters for the automatic computation of the tear film break-up time test based on CCLRU standards.

Dry eye disease is a public health problem, whose multifactorial etiology challenges clinicians and researchers making necessary the collaboration between different experts and centers. The evaluation of the interference patterns observed in the tear film lipid layer is a common clinical test used for dry eye diagnosis. However, it is a time-consuming task with a high degree of intra- as well as inter-observer variability, which makes the use of a computer-based analysis system highly desirable. This work introduces iDEAS (Dry Eye Assessment System), a web-based application to support dry eye diagnosis.

iDEAS: A web-based system for dry eye assessment.

The sudden increase of blood flow in the bulbar conjunctiva, known as hyperemia, is associated to a red hue of variable intensity. Experts measure hyperemia using levels in a grading scale, a procedure that is subjective, non-repeatable and time consuming, thus creating a need for its automatisation. However, the task is far from straightforward due to data issues such as class imbalance or correlated features. In this paper, we study the specific features of hyperemia and propose various approaches to address these problems in the context of an automatic framework for hyperemia grading.

On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings.

Retinal vessel tree extraction is a crucial step for analyzing the microcirculation, a frequently needed process in the study of relevant diseases. To date, this has normally been done by using 2D image capture paradigms, offering a restricted visualization of the real layout of the retinal vasculature. In this work, we propose a new approach that automatically segments and reconstructs the 3D retinal vessel tree by combining near-infrared reflectance retinography information with Optical Coherence Tomography (OCT) sections. Our proposal identifies the vessels, estimates their calibers, and obtains the depth at all the positions of the entire vessel tree, thereby enabling the reconstruction of the 3D layout of the complete arteriovenous tree for subsequent analysis. The method was tested using 991 OCT images combined with their corresponding near-infrared reflectance retinography. The different stages of the methodology were validated using the opinion of an expert as a reference. The tests offered accurate results, showing coherent reconstructions of the 3D vasculature that can be analyzed in the diagnosis of relevant diseases affecting the retinal microcirculation, such as hypertension or diabetes, among others.

Article	Year
Analysis of parameters for the automatic computation of the tear film break-up time test based on CCLRU standards. Computer methods and programs in biomedicine\| PubMed ID: 24438992	2014
iDEAS: A web-based system for dry eye assessment. Computer methods and programs in biomedicine\| PubMed ID: 27208533	2016
On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings. Artificial intelligence in medicine\| PubMed ID: 27506129	2016
Enhanced visualization of the retinal vasculature using depth information in OCT. Medical & biological engineering & computing\| PubMed ID: 28623452	2017

Noelia Barreira

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