well-aligned-vertically-oriented-zno-nanorod-arrays-their-application

Well-aligned Vertically Oriented ZnO Nanorod Arrays and their Application in Inverted Small Molecule Solar Cells

This manuscript describes how to design and fabricate efficient inverted solar cells, which are based on a two-dimensional conjugated small molecule ...

National United University

We present the first experimental results of time-resolved diffuser-aided diffuse optical imaging (DADOI) method in this paper. A self-manufactured diffuser plate was inserted between the optode and the surface of a scattering medium. The diffuser was utilized to enhance the multiple scattering that destroys the image information for baseline measurement of turbid medium. Therefore, the abnormality can be detected with the modified optical density calculation. The time-domain DADOI method can provide better imaging contrast and simpler imaging than the conventional diffuse optical tomography measurement. Besides, it also reveals rich depth information with temporal responses. Therefore, the DADOI offers a great potential to detect the breast tumor and chemotherapy monitoring in clinical diagnosis.

Diffuser-aided time-domain diffuse optical imaging: a phantom study.

Long-term comparisons of infrared image can facilitate the assessment of breast cancer tissue growth and early tumor detection, in which longitudinal infrared image registration is a necessary step. However, it is hard to keep markers attached on a body surface for weeks, and rather difficult to detect anatomic fiducial markers and match them in the infrared image during registration process. The proposed study, automatic longitudinal infrared registration algorithm, develops an automatic vascular intersection detection method and establishes feature descriptors by shape context to achieve robust matching, as well as to obtain control points for the deformation model. In addition, competitive winner-guided mechanism is developed for optimal corresponding. The proposed algorithm is evaluated in two ways. Results show that the algorithm can quickly lead to accurate image registration and that the effectiveness is superior to manual registration with a mean error being 0.91 pixels. These findings demonstrate that the proposed registration algorithm is reasonably accurate and provide a novel method of extracting a greater amount of useful data from infrared images.

Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding.

Radiofrequency ablation (RFA) has been widely used as an alternative treatment modality for liver tumors. Monitoring the temperature distribution in the tissue during RFA is required to assess the thermal dosage. Ultrasound temperature imaging based on the detection of echo time shifts has received the most attention in the past decade. The coefficient k, connecting the temperature change and the echo time shift, is a medium-dependent parameter used to describe the confounding effects of changes in the speed of sound and thermal expansion as temperature increases. The current algorithm of temperature estimate based on echo time shift detection typically uses a constant k, resulting in estimation errors when ablation temperatures are higher than 50°C. This study proposes an adaptive-k algorithm that enables the automatic adjustment of the coefficient k during ultrasound temperature monitoring of RFA. To verify the proposed algorithm, RFA experiments on in vitro porcine liver samples (total n = 15) were performed using ablation powers of 10, 15, and 20 W. During RFA, a clinical ultrasound system equipped with a 7.5-MHz linear transducer was used to collect backscattered signals for ultrasound temperature imaging using the constant- and adaptive-k algorithms. Concurrently, an infrared imaging system and thermocouples were used to measure surface temperature distribution of the sample and internal ablation temperatures for comparisons with ultrasound estimates. Experimental results demonstrated that the proposed adaptive-k method improved the performance in visualizing the temperature distribution. In particular, the estimation errors were also reduced even when the temperature of the tissue is higher than 50°C. The proposed adaptive-k ultrasound temperature imaging strategy has potential to serve as a thermal dosage evaluation tool for monitoring high-temperature RFA.

Adaptive ultrasound temperature imaging for monitoring radiofrequency ablation.

Voice disorder such as vocal fatigue is a common and complex multifaceted clinical problem that presents a significant impact on quality of life. In this study, the functional near-infrared diffuse optical technique (fNIRS-DOT) was proposed as a novel approach for human vocal cords oxidative metabolism detection and acoustic assessment simultaneously to provide a multidimensional assessment of voice disorder. A totally of 60 healthy subjects included 30 male and 30 female adults of age-matched were recruited and performed a vocal loading task to trigger a mild inflammation of the vocal cords in this study. In the results of oxidative metabolism, the vocal cords expressed hypoxia after vocal loading task in both male and female groups that could provide relevant information on the relationship between tissue oxygen consumption and supply for vocal cords diagnosis. Additionally, the results of optical acoustic assessment revealed the worse/changes voice quality after vocal loading task. Therefore, integration of non-invasive oxidative metabolism detection and acoustic assessment by using optical technique could provide more relevant information for diagnosis of voice disorders. The multi-functional vocal cords detection system could provide a good feasibility for clinical applications such as diagnosis and therapeutic monitoring of voice disorder.

A feasibility study on non-invasive oxidative metabolism detection and acoustic assessment of human vocal cords by using optical technique.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to diagnose breast disease. Obtaining anatomical information from DCE-MRI requires the skin be manually removed so that blood vessels and tumors can be clearly observed by physicians and radiologists; this requires considerable manpower and time. We develop an automated skin segmentation algorithm where the surface skin is removed rapidly and correctly. The rough skin area is segmented by the active contour model, and analyzed in segments according to the continuity of the skin thickness for accuracy. Blood vessels and mammary glands are retained, which remedies the defect of removing some blood vessels in active contours. After three-dimensional imaging, the DCE-MRIs without the skin can be used to see internal anatomical information for clinical applications. The research showed the Dice's coefficients of the 3D reconstructed images using the proposed algorithm and the active contour model for removing skins are 93.2% and 61.4%, respectively. The time performance of segmenting skins automatically is about 165 times faster than manually. The texture information of the tumors position with/without the skin is compared by the paired t-test yielded all p < 0.05, which suggested the proposed algorithm may enhance observability of tumors at the significance level of 0.05.

Article	Year
Diffuser-aided time-domain diffuse optical imaging: a phantom study. Journal of biomedical optics\| PubMed ID: 24723113	2014
Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding. Scientific reports\| PubMed ID: 28145474	2017
Adaptive ultrasound temperature imaging for monitoring radiofrequency ablation. PloS one\| PubMed ID: 28837584	2017
A feasibility study on non-invasive oxidative metabolism detection and acoustic assessment of human vocal cords by using optical technique. Scientific reports\| PubMed ID: 29208920	2017
An automated skin segmentation of Breasts in Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Scientific reports\| PubMed ID: 29670156	2018

Chia-Yen Lee

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