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Judul Deep Learning for Pathology Detection and Diagnosis in Medical Imaging / Sergiu Nedevschi ; Delia-Alexandrina Mitrea
Pengarang Nedevschi, Sergiu
Mitrea, Delia-Alexandrina
Penerbitan Switzerland : MDPI - Multidisciplinary Digital Publishing Institute, 2024
Deskripsi Fisik 240 p. :ilus.
ISBN 978-3-7258-2042-9
Subjek PATHOLOGY
VIRTUAL BIOPSY
DEEP LEARNING
Catatan Severe 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
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Lokasi Akses Online https://www.mdpi.com/books/reprint/9901-deep-learning-for-pathology-detection-and-diagnosis-in-medical-imaging

 
No Barcode No. Panggil Akses Lokasi Ketersediaan
178026192 617.522 07 Dee Baca Online Perpustakaan Pusat - Online Resources
Ebook
Tersedia
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020 # # $a 978-3-7258-2042-9
035 # # $a 0010-0226001111
082 # # $a 617.522 07
084 # # $a 617.522 07 Dee
245 # # $a Deep Learning for Pathology Detection and Diagnosis in Medical Imaging /$c Sergiu Nedevschi ; Delia-Alexandrina Mitrea
260 # # $a Switzerland :$b MDPI - Multidisciplinary Digital Publishing Institute,$c 2024
300 # # $a 240 p. : $b ilus.
505 # # $a Severe 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.
650 # # $a DEEP LEARNING
650 # # $a PATHOLOGY
650 # # $a VIRTUAL BIOPSY
700 1 # $a Mitrea, Delia-Alexandrina
700 1 # $a Nedevschi, Sergiu
856 # # $a https://www.mdpi.com/books/reprint/9901-deep-learning-for-pathology-detection-and-diagnosis-in-medical-imaging
990 # # $a 178026192
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