Graph embedding to improve supervised classification and novel class detection: Application to prostate cancer

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

Volumn 3749 LNCS, Issue , 2005, Pages 729-737

  Madabhushi, Anant ^a   Shi, Jianbo ^a   Rosen, Mark ^a   Tomaszeweski, John E ^a   Feldman, Michael D ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATABASE SYSTEMS; EMBEDDED SYSTEMS; GRAPH THEORY; MAGNETIC RESONANCE IMAGING; ONCOLOGY;

GRAPH EMBEDDING; PROSTATE CANCER; PROSTATIC ADENOCARCINOMA;

COMPUTER AIDED DIAGNOSIS;

ADENOCARCINOMA; ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; MALE; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PROSTATE TUMOR; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ADENOCARCINOMA; ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MALE; PATTERN RECOGNITION, AUTOMATED; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 33744803217     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11566465_90     Document Type: Conference Paper

References (7)

1. I. Dhillon, D. Modha, W. Spangler, "Class Visualization of high-dimensional data with applications", Computational Statistics & Data Analysis, 2002, vol. 41, pp. 59-90.
2. T. Iwata, K. Saito, et al., "Parametric Embedding for Class Visualization", NIPS, 2004.
3. A. Globerson, G. Chechik, et al., "Euclidean Embedding of Co-occurrence Data", NIPS, 2004.
4. H. Zhong, J. Shi and M. Visontai, Detecting Unusual Activity in Video, CVPR, 2004.
5. A. Madabhushi, M. Feldman, D. Metaxas, J. Tomaszeweski, D. Chute, Automated Detection of Prostatic Adenocarcinoma from High Resolution in vitro prostate MR studies, IEEE Trans. Med. Imag., Accepted.
6. R. Duda, P. Hart, Pattern Classification and Scene Analysis, New York Wiley, 1973.
7. T. Joliffe, Principal Component Analysis, Springer-Verlag, 1986.