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Li J.,Shenzhen University | Li J.,Chinese University of Hong Kong | Zhou Y.,Shenzhen University | Zhou Y.,National Regional Key Technology Engineering Laboratory for Medical Ultrasound | And 3 more authors.
Ultrasonics | Year: 2015

Abstract Muscle force output is an essential index in rehabilitation assessment or physical exams, and could provide considerable insights for various applications such as load monitoring and muscle assessment in sports science or rehabilitation therapy. Besides direct measurement of force output using a dynamometer, electromyography has earlier been used in several studies to quantify muscle force as an indirect means. However, its spatial resolution is easily compromised as a summation of the action potentials from neighboring motor units of electrode site. To explore an alternative method to indirectly estimate the muscle force output, and with better muscle specificity, we started with an investigation on the relationship between architecture dynamics and force output of triceps surae. The muscular architecture dynamics is captured in ultrasonography sequences and estimated using a previously reported motion estimation method. Then an indicator named as the dorsoventrally averaged motion profile (DAMP) is employed. The performance of force output is represented by an instantaneous version of the rate of force development (RFD), namely I-RFD. From experimental results on ten normal subjects, there were significant correlations between the I-RFD and DAMP for triceps surae, both normalized between 0 and 1, with the sum of squares error at 0.0516±0.0224, R-square at 0.7929±0.0931 and root mean squared error at 0.0159±0.0033. The statistical significance results were less than 0.01. The present study suggested that muscle architecture dynamics extracted from ultrasonography during contraction is well correlated to the I-RFD and it can be a promising option for indirect estimation of muscle force output. © 2015 Elsevier B.V. Source


Li B.,Shenzhen University | Li B.,National Regional Key Technology Engineering Laboratory for Medical Ultrasound | Li B.,Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging | Xu G.,CAS Shenzhen Institutes of Advanced Technology | And 4 more authors.
Medical Physics | Year: 2015

Purpose:Wireless capsule endoscopy (WCE) opens a newdoor for the digestive tract examination and diagnosis. However, the examination of its video data is tedious. This study aims to assist a physician to interpret a WCE video by segmenting it into different anatomic parts in the digestive tract. Methods: A two level WCE video segmentation scheme is proposed to locate the boundary between the stomach, small intestine, and large intestine. In the rough level, the authors utilize color feature to draw a dissimilarity curve for a WCE video and obtain an approximate boundary. Meanwhile, training data for the fine level segmentation can be collected automatically between the two approximate boundaries of organs to overcome the difficulty of training data collection in traditional approaches. In the fine level, color histogram in the HSI color space is used to segment the stomach and small intestine. Then, color uniform local binary pattern (CULBP) algorithm is applied for discrimination of the small intestine and large intestine, which includes two patterns, namely, color norm and color angle pattern. The CULBP feature is robust to variation of illumination and discriminative for classification. In order to increase the performance of support vector machine, the authors integrate it with the Adaboost approach. Finally, the authors refine the classification results to segment a WCE video into different parts, that is, the stomach, small intestine, and large intestine. Results: The average precision and recall are 91.2% and 90.6% for the stomach/small intestine classification, 89.2% and 88.7% for the small/large intestine discrimination. Paired t-test also demonstrates a significant better performance of the proposed scheme compared to some traditional methods. The average segmentation error is 8 frames for the stomach/small intestine discrimination, and 14 frames for the small/large intestine segmentation. Conclusions: The results have demonstrated that the new video segmentation method can accurately locate the boundary between different organ regions in a WCE video. Such a segmentation result may enhance the efficiency of WCE examination. © 2015 American Association of Physicists in Medicine. Source


Chen X.,Shenzhen University | Chen X.,National Regional Key Technology Engineering Laboratory for Medical Ultrasound | Chen X.,Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging | Shen Y.,Shenzhen University | And 15 more authors.
Ultrasound in Medicine and Biology | Year: 2013

Ultrasound elastography, based on shear wave propagation, enables the quantitative and non-invasive assessment of liver mechanical properties such as stiffness and has been found to be feasible for and useful in the diagnosis of hepatic fibrosis. Most ultrasound elastographic methods use a purely elastic model to describe liver mechanical properties. However, to describe tissue that is dispersive and to obtain an accurate measure of tissue elasticity, the viscoelasticity of the tissue should be examined. The objective of this study was to investigate the shear viscoelastic characteristics, as measured by ultrasound elastography, of liver fibrosis in a rat model and to evaluate the diagnostic accuracy of viscoelasticity for staging liver fibrosis. Liver fibrosis was induced in 37 rats using carbon tetrachloride (CCl4); 6 rats served as controls. Liver viscoelasticity was measured invitro using shear waves induced by acoustic radiation force. The measured mean values of liver elasticity and viscosity ranged from 0.84 to 3.45kPa and from 1.12 to 2.06Pa·s for fibrosis stages F0-F4, respectively. Spearman correlation coefficients indicated that stage of fibrosis was well correlated with elasticity (0.88) and moderately correlated with viscosity (0.66). The areas under receiver operating characteristic curves were 0.97 (≥F2), 0.91 (≥F3) and 1.00(F4) for elasticity and 0.91 (≥F2), 0.79 (≥F3) and 0.74 (F4) for viscosity, respectively. The results confirmed that shear wave velocity was dispersive in frequency, suggesting a viscoelastic model to describe liver fibrosis. The study finds that although viscosity is not as good as elasticity for staging fibrosis, it is important to consider viscosity to make an accurate estimation of elasticity; it may also provide other mechanical insights into liver tissues. © 2013 World Federation for Ultrasound in Medicine & Biology. Source


Zhang L.,Shenzhen University | Zhang L.,National Regional Key Technology Engineering Laboratory for Medical Ultrasound | Zhang L.,Guangdong Key Laboratory of Biomedical Information Detection and Ultrasound Imaging | Kong H.,Massachusetts Institute of Technology | And 9 more authors.
Bio-Medical Materials and Engineering | Year: 2014

This paper proposes a method to segment the cytoplasm in cervical cell images using graph cut-based algorithm. First, the A* channel in CIE LAB color space is extracted for contrast enhancement. Then, in order to effectively extract cytoplasm boundaries when image histograms present non-bimodal distribution, Otsu multiple thresholding is performed on the contrast enhanced image to generate initial segments, based on which the segments are refined by the multi-way graph cut method. We use 21 cervical cell images with non-ideal imaging condition to evaluate cytoplasm segmentation performance. The proposed method achieved a 93% accuracy which outperformed state-of-the-art works. © 2014 - IOS Press and the authors. All rights reserved. Source


Zhang L.,Shenzhen University | Zhang L.,University of Iowa | Zhang L.,National Regional Key Technology Engineering Laboratory for Medical Ultrasound | Zhang L.,Guangdong Key Laboratory of Biomedical Information Detection | And 12 more authors.
Computerized Medical Imaging and Graphics | Year: 2014

Automation-assisted reading (AAR) techniques have the potential to reduce errors and increase productivity in cervical cancer screening. The sensitivity of AAR relies heavily on automated segmentation of abnormal cervical cells, which is handled poorly by current segmentation algorithms. In this paper, a global and local scheme based on graph cut approach is proposed to segment cervical cells in images with a mix of healthy and abnormal cells. For cytoplasm segmentation, the multi-way graph cut is performed globally on the a* channel enhanced image, which can be effective when the image histogram presents a non-bimodal distribution. For segmentation of nuclei, especially when they are abnormal, we propose to use graph cut adaptively and locally, which allows the combination of intensity, texture, boundary and region information. Two concave points-based approaches are integrated to split the touching-nuclei. As part of an ongoing clinical trial, preliminary validation results obtained from 21 cervical cell images with non-ideal imaging condition and pathology show that our segmentation method achieved 93% accuracy for cytoplasm, and 88.4% F-measure for abnormal nuclei, outperforming state of the art methods in terms of accuracy. Our method has the potential to improve the sensitivity of AAR in screening for cervical cancer. © 2014 Elsevier Ltd. Source

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