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OverviewSevere pathologies, such as the diffuse liver diseases or tumors, can lead to the significant degradation of the human health and sometimes to lethal stages. The most reliable methods for the diagnosis of these affections, such as the classical biopsy or surgery, are invasive and dangerous. Advanced computerized methods are urgently needed to reduce invasiveness and enhance the information derived from medical images as much as possible by unveiling their subtle aspects, conducting to a virtual biopsy. Computer Vision and Machine Learning can be successfully employed to achieve this target. Thus, advanced image analysis combined with conventional machine learning, as well as the deep learning techniques, can lead to a highly accurate automatic diagnosis process. The corresponding features, together with the classification, segmentation, fusion of multiple image modalities, and 3D reconstruction techniques, can be involved in the achievement of appropriate 2D and 3D models for the considered affections, which are helpful in computer-aided diagnosis and surgery. The purpose of the special issue ""Deep Learning for Pathology Detection and Diagnosis in Medical Imaging"" is that of offering the opportunity to disseminate valuable and original results achieved in the corresponding field, surprising the latest, deep-learning techniques, eventually compared and combined with conventional methods. Full Product DetailsAuthor: Sergiu Nedevschi , Delia-Alexandrina MitreaPublisher: Mdpi AG Imprint: Mdpi AG Dimensions: Width: 17.00cm , Height: 1.90cm , Length: 24.40cm Weight: 0.676kg ISBN: 9783725820412ISBN 10: 3725820414 Pages: 220 Publication Date: 25 September 2024 Audience: General/trade , General Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |