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medical-images-segmentation
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3D Medical Images Segmentation by Effective Use of Unlabeled Data
, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdieh (Supervisor)
Abstract
Image segmentation in medical imaging, as one of the most important branches of medical image analysis, often faces the challenge of limited labeled data for application in deep learning methods. The high cost of data collection and the need for expertise in image segmentation, particularly in three-dimensional images such as MRI and CT or sequence images like CMR, have all contributed to this problem, even for popular networks like U-Net, which struggle to achieve high accuracy. As a result, research efforts have focused on semi-supervised learning approaches, weakly supervised learning, as well as multi-instance learning in medical image segmentation. Unfortunately, each of these methods...
Medical image segmentation for skin lesion detection via topological data analysis
, Article 16th International Conference on Ubiquitous Information Management and Communication, IMCOM 2022, 3 January 2022 through 5 January 2022 ; 2022 ; 9781665426787 (ISBN) ; Jazayeri, F ; Sajedi, H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
According to the WHO, two individuals die every hour from skin cancer and about 9500 people get skin cancer every day just in the United States. Various computer vision algorithms have been introduced for skin lesion detection, classification, and segmentation. This paper proposes a new segmentation-based algorithm in order to select target components using the persistence diagram of the input images. The results, in comparison with the existing seven different both clustering-and histogram-based segmentation methods using three metrics, show improved performance. Medical image segmentation is an essential task in computer-aided diagnosis. The main improvement of our method is to detect one...
A new fuzzy connectedness relation for image segmentation
, Article 2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications, ICTTA, Damascus, 7 April 2008 through 11 April 2008 ; 2008 ; 9781424417513 (ISBN) ; Kasaei, S ; Mohseni, H ; Sharif University of Technology
2008
Abstract
In the image segmentation field, traditional techniques do not completely meet the segmentation challenges mostly posed by inherently fuzzy images. Fuzzy connectedness and fuzzy clustering are considered as two well-known techniques for introducing fuzzy concepts to the problem of image segmentation. Fuzzy connectedness-based Segmentation methods consider spatial relation of image pixels by "hanging togetherness" a notion based on intensity homogeneity. But, they do not inherently utilize feature information of image pixels. On the other hand, as the segmentation domain of fuzzy clustering-based methods is the feature space they do not consider spatial relations among image pixels. Recently,...