Segmentation and Diagnosis of Liver Carcinoma Based on Adaptive Scale-Kernel Fuzzy Clustering Model for CT Images

Medical image analysis plays an important role in computer-aided liver-carcinoma diagnosis. Aiming at the existing image fuzzy clustering segmentation being not suitable to segment CT image with non-uniform background, a fast robust kernel space fuzzy clustering segmentation algorithm is proposed. F...

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Vydané v:	Journal of medical systems Ročník 43; číslo 11; s. 322
Hlavný autor:	Cai, Jianhong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.11.2019 Springer Nature B.V
Predmet:	Algorithms Clustering Computed tomography Decision support systems Diagnosis Diagnosis, Computer-Assisted Distributed Analytics and Deep Learning in Health Care Euclidean geometry Euclidean space Fuzzy Logic Health Informatics Health Sciences Histograms Humans Image & Signal Processing Image analysis Image filters Image processing Image Processing, Computer-Assisted - methods Image segmentation Iterative methods Kernel functions Lagrange multiplier Liver Liver cancer Liver Neoplasms - diagnostic imaging Liver Neoplasms - pathology Manufacturing cells Medical diagnosis Medical imaging Medicine Medicine & Public Health Pixels Robustness (mathematics) Statistics for Life Sciences Tomography, X-Ray Computed - methods Tumors Lagrange multiplier Liver carcinoma Fuzzy clustering Non-uniform background Linear weighted filtering European space Scale-kernel space
ISSN:	0148-5598, 1573-689X, 1573-689X
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