Abdominal organ segmentation using texture transforms and a hopfield neural network

IEEE Transactions on Medical Imaging

Volumn 18, Issue 7, 1999, Pages 640-648

  Koss, J E ^a   Newman, F D ^a   Johnson, T K ^a   Kirch, D L ^a  

^a UNIVERSITY OF COLORADO   (United States)

Author keywords

Hopfield neural network; Organ segmentation; Texture analysis

Indexed keywords

COMPUTERIZED TOMOGRAPHY; IMAGE ANALYSIS; IMAGE SEGMENTATION; LYAPUNOV METHODS; MAGNETIC RESONANCE IMAGING; MATHEMATICAL TRANSFORMATIONS; NEURAL NETWORKS; OPTIMIZATION; PROBLEM SOLVING; STATISTICAL METHODS; TISSUE;

ABDOMINAL ORGAN SEGMENTATION; HARALICK TRANSFORMS; LYAPUNOV ENERGY FUNCTION;

MEDICAL IMAGING;

ABDOMINAL RADIOGRAPHY; ALGORITHM; ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; LETTER; METHODOLOGY;

ALGORITHMS; HUMANS; NEURAL NETWORKS (COMPUTER); RADIOGRAPHY, ABDOMINAL; TOMOGRAPHY, X-RAY COMPUTED;

EID: 0033153748     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/42.790463     Document Type: Article

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