Γ-Convergence approximation to piecewise smooth medical image segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4792 LNCS, Issue PART 2, 2007, Pages 495-502

  An, Jungha ^a,b   Rousson, Mikael ^b   Xu, Chenyang ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ACQUISITION; IMAGE QUALITY; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; NUMERICAL ANALYSIS; TWO DIMENSIONAL;

ACQUISITION PROTOCOL; CONVERGENCE APPROXIMATION; GAUSSIAN CONVOLUTIONS; IMAGE INTENSITY;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; LIVER; MATHEMATICAL COMPUTING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LIVER; MAGNETIC RESONANCE IMAGING; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 79551681348     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75759-7_60     Document Type: Conference Paper

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