Current Issue : April - June Volume : 2014 Issue Number : 2 Articles : 5 Articles
Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there\r\nis an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing\r\nthe structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, largescale\r\ncortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense\r\nIndividualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of\r\nthe brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI)\r\ndata. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the stateof-\r\nthe-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition,\r\nwe compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free\r\ngene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local\r\ngraph properties. Our experimental results suggest that among the seven theoretical graphmodels compared in this study, STICKY\r\nand SF-GD models have better performances in characterizing the structural human brain network....
Image-guided radiotherapy (IGRT), adaptive radiotherapy (ART), and online reoptimization rely on accurate mapping of the\r\nradiation beamisocenter(s) fromplanning to treatment space. This mapping involves rigid and/or nonrigid registration of planning\r\n(pCT) and intratreatment (tCT) CT images. The purpose of this study was to retrospectively compare a fully automatic approach,\r\nincluding a non-rigid step, against a user-directed rigid method implemented in a clinical IGRT protocol for prostate cancer.\r\nIsocenters resulting from automatic and clinical mappings were compared to reference isocenters carefully determined in each\r\ntCT. Comparison was based on displacements from the reference isocenters and prostate dose-volume histograms (DVHs). Ten\r\npatients with a total of 243 tCTs were investigated. Fully automatic registration was found to be as accurate as the clinical protocol\r\nbutmore precise for all patients.The average of the unsigned ??, ??, and ?? offsets and the standard deviations (??) of the signed offsets\r\ncomputed over all images were (avg. �± ??(mm)): 1.1 �± 1.4, 1.8 �± 2.3, 2.5 �± 3.5 for the clinical protocol and 0.6 �± 0.8, 1.1 �± 1.5 and 1.1\r\n�± 1.4 for the automatic method. No failures or outliers from automatic mapping were observed, while 8 outliers occurred for the\r\nclinical protocol....
Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma.\r\nWe review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, preprocessing,\r\nsegmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics\r\nand results from the most important implementations reported to date. We compared the performance of several classifiers\r\nspecifically developed for skin lesion diagnosis and discussed the corresponding findings.Whenever available, indication of various\r\nconditions that affect the technique�s performance is reported.We suggest a framework for comparative assessment of skin cancer\r\ndiagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted\r\nand suggestions for future research are provided....
We propose a method for improving image quality in medical images by using a wavelet-based approach. The proposed method\r\nintegrates two components: image denoising and image enhancement. In the first component, a modified undecimated discrete\r\nwavelet transform is used to eliminate the noise. In the second component, a wavelet coefficient mapping function is applied to\r\nenhance the contrast of denoised images obtained fromthe first component. This methodology can be used not only as a means for\r\nimproving visual quality of medical images but also as a preprocessing module for computer-aided detection/diagnosis systems\r\nto improve the performance of screening and detecting regions of interest in images. To confirm its superiority over existing\r\nstate-of-the-art methods, the proposed method is experimentally evaluated via 30 mammograms and 20 chest radiographs. It\r\nis demonstrated that the proposed method can further improve the image quality of mammograms and chest radiographs, as\r\ncompared to two other methods in the literature.These results reveal the effectiveness and superiority of the proposed method....
One of the most commonmodalities to examine the human eye is the eye-fundus photograph.Theevaluation of fundus photographs\r\nis carried out by medical experts during time-consuming visual inspection. Our aim is to accelerate this process using computer\r\naided diagnosis. As a first step, it is necessary to segment structures in the images for tissue differentiation. As the eye is the only\r\norgan, where the vasculature can be imaged in an in vivo and noninterventional way without using expensive scanners, the vessel\r\ntree is one of the most interesting and important structures to analyze. The quality and resolution of fundus images are rapidly\r\nincreasing.Thus, segmentation methods need to be adapted to the new challenges of high resolutions. In this paper, we present a\r\nmethod to reduce calculation time, achieve high accuracy, and increase sensitivity compared to the original Frangi method. This\r\nmethod contains approaches to avoid potential problems like specular reflexes of thick vessels. The proposed method is evaluated\r\nusing the STARE and DRIVE databases and we propose a new high resolution fundus database to compare it to the state-of-theart\r\nalgorithms.The results show an average accuracy above 94% and low computational needs.This outperforms state-of-the-art\r\nmethods....
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