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Volumn 21, Issue 2, 2002, Pages 150-158
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A multiple circular path convolution neural network system for detection of mammographic masses
a
IEEE
(United States)
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Author keywords
[No Author keywords available]
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Indexed keywords
BREAST CANCER;
CONTEXTUAL BAYESIAN RELAXATION LABELING;
CONVOLUTION KERNELS;
FINITE GENERALIZED GAUSSIAN MIXTURE;
MAMMOGRAPHIC MASSES;
MORPHOLOGICAL ENHANCEMENT;
MULTIPLE CIRCULAR PATH CONVOLUTION NEURAL NETWORK;
REGION OF INTEREST;
ALGORITHMS;
FEATURE EXTRACTION;
FEEDFORWARD NEURAL NETWORKS;
IMAGE ANALYSIS;
IMAGE ENHANCEMENT;
IMAGE SEGMENTATION;
MAMMOGRAPHY;
MATHEMATICAL MODELS;
MEDICAL IMAGING;
ONCOLOGY;
TUMORS;
COMPUTER AIDED DIAGNOSIS;
ARTICLE;
ARTIFICIAL NEURAL NETWORK;
AUTOMATED PATTERN RECOGNITION;
BIOLOGICAL MODEL;
BREAST TUMOR;
CLASSIFICATION;
COMPARATIVE STUDY;
COMPUTER ASSISTED DIAGNOSIS;
FACTUAL DATABASE;
FEEDBACK SYSTEM;
FEMALE;
HUMAN;
IMAGE PROCESSING;
MAMMOGRAPHY;
METHODOLOGY;
RADIOGRAPHY;
REPRODUCIBILITY;
ROC CURVE;
SENSITIVITY AND SPECIFICITY;
STATISTICAL MODEL;
BREAST NEOPLASMS;
DATABASES, FACTUAL;
FEEDBACK;
FEMALE;
HUMANS;
IMAGE INTERPRETATION, COMPUTER-ASSISTED;
IMAGE PROCESSING, COMPUTER-ASSISTED;
MAMMOGRAPHY;
MODELS, BIOLOGICAL;
MODELS, STATISTICAL;
NEURAL NETWORKS (COMPUTER);
PATTERN RECOGNITION, AUTOMATED;
REPRODUCIBILITY OF RESULTS;
ROC CURVE;
SENSITIVITY AND SPECIFICITY;
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EID: 0036462557
PISSN: 02780062
EISSN: None
Source Type: Journal
DOI: 10.1109/42.993133 Document Type: Article |
Times cited : (84)
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References (31)
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