Current Issue : April - June Volume : 2015 Issue Number : 2 Articles : 6 Articles
Tongue image with coating is of important clinical diagnostic meaning, but traditional tongue image extraction method is not\ncompetent for extraction of tongue imagewith thick coating. In this paper, a novel method is suggested,which appliesmultiobjective\ngreedy rules and makes fusion of color and space information in order to extract tongue image accurately. A comparative\nstudy of several contemporary tongue image extraction methods is also made from the aspects of accuracy and efficiency. As\nthe experimental results show, geodesic active contour is quite slow and not accurate, the other 3 methods achieve fairly good\nsegmentation results except in the case of the tongue with thick coating, our method achieves ideal segmentation results whatever\ntypes of tongue images are, and efficiency of our method is acceptable for the application of quantitative check of tongue image....
Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy\nis currently the ââ?¬Å?gold standardââ?¬Â technique for diagnosis of different pathologies of the intestinal tract. Wireless capsule\nendoscopy (WCE) has been developed in the 1990s as an alternative to videoendoscopy to allow direct examination of the\ngastrointestinal tractwithout any need for sedation.Nevertheless, the systematic postexamination by the specialist of the 50,000 (for\nthe small bowel) to 150,000 images (for the colon) of a complete acquisition usingWCE remains time-consuming and challenging\ndue to the poor quality ofWCE images. In this paper, a semiautomatic segmentation for analysis ofWCE images is proposed. Based\non active contour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that\ngives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are\nshown on different types of real-case examinations, from (multi)polyp(s) segmentation, to radiation enteritis delineation....
We propose amodified Perona-Malik diffusion (PMD) filter to enhance a coronary plaque boundary by considering the conditions\npeculiar to an intravascular ultrasound (IVUS) image. The IVUS image is commonly used for a diagnosis of acute coronary\nsyndrome (ACS). The IVUS image is however very grainy due to heavy speckle noise. When the normal PMD filter is applied\nfor speckle noise reduction in the IVUS image, the coronary plaque boundary becomes vague. For this problem, we propose a\nmodified PMD filter which is designed in special reference to the coronary plaque boundary detection. It can then not only reduce\nthe speckle noise but also enhance clearly the coronary plaque boundary. After applying the modifiedPMDfilter to the IVUS image,\nthe coronary plaque boundaries are successfully detected further by applying the Takagi-Sugeno fuzzy model. The accuracy of the\nproposed method has been confirmed numerically by the experiments....
We propose an ischemic stroke detection system with a computer-aided diagnostic ability using a four-step unsupervised feature\nperception enhancement method. In the first step, known as preprocessing, we use a cubic curve contrast enhancement method\nto enhance image contrast. In the second step, we use a series of methods to extract the brain tissue image area identified during\npreprocessing. To detect abnormal regions in the brain images, we propose using an unsupervised region growing algorithm to\nsegment the brain tissue area. The brain is centered on a horizontal line and the white matter of the brain�s inner ring is split\ninto eight regions. In the third step, we use a coinciding regional location method to find the hybrid area of locations where a\nstroke may have occurred in each cerebral hemisphere. Finally, we make corrections and mark the stroke area with red color. In\nthe experiment, we tested the system on 90 computed tomography (CT) images from 26 patients, and, with the assistance of two\nradiologists, we proved that our proposed system has computer-aided diagnostic capabilities. Our results show an increased stroke\ndiagnosis sensitivity of 83% in comparison to 31% when radiologists use conventional diagnostic images....
Conventional radar-based image reconstruction techniques fail when they are applied to heterogeneous breast tissue, since the\nunderlying in-breast relative permittivity is unknown or assumed to be constant.This results in a systematic error during the process\nof image formation. A recent trend in microwave biomedical imaging is to extract the relative permittivity from the object under\ntest to improve the image reconstruction quality and thereby to enhance the diagnostic assessment. In this paper, we present a novel\nradar-based methodology for microwave breast cancer detection in heterogeneous breast tissue integrating a 3D map of relative\npermittivity as a priori information. This leads to a novel image reconstruction formulation where the delay-and-sum focusing\ntakes place in time rather than range domain. Results are shown for a heterogeneous dense (class-4) and a scattered fibroglandular\n(class-2) numerical breast phantom using Bristol�s 31-element array configuration....
Breast cancer is the most common cancer among women worldwide and breast self-examination (BSE) is considered as the most\ncost-effective approach for early breast cancer detection.The general objective of this paper is to design and develop a computer\nvision algorithm to evaluate the BSE performance in real-time. The first stage of the algorithm presents a method for detecting and\ntracking the nipples in frames while a woman performs BSE; the second stage presents a method for localizing the breast region and\nblocks of pixels related to palpation of the breast, and the third stage focuses on detecting the palpated blocks in the breast region.\nThe palpated blocks are highlighted at the time of BSE performance. In a correct BSE performance, all blocks must be palpated,\nchecked, and highlighted, respectively. If any abnormality, such as masses, is detected, then this must be reported to a doctor to\nconfirm the presence of this abnormality and proceed to perform other confirmatory tests. The experimental results have shown\nthat the BSE evaluation algorithm presented in this paper provides robust performance....
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