A boosting cascade for automated detection of prostate cancer from digitized histology

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

Volumn 4191 LNCS - II, Issue , 2006, Pages 504-511

  Doyle, Scott ^a   Madabhushi, Anant ^a   Feldman, Michael ^b   Tomaszeweski, John ^b  

^a RUTGERS UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BIOPSY; COMPUTER AIDED DIAGNOSIS; HISTOLOGY; IMAGE ANALYSIS; PATHOLOGY; TISSUE;

AUTOMATED DETECTION; DIGITIZED HISTOLOGY; PROSTATE CANCER; SLIDE DIGITAL SCANNERS;

TUMORS;

ADENOCARCINOMA; ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOPSY; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; MALE; METHODOLOGY; MICROSCOPY; PATHOLOGY; PROSTATE TUMOR; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; VALIDATION STUDY;

ADENOCARCINOMA; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOPSY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MALE; MICROSCOPY; PATTERN RECOGNITION, AUTOMATED; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 71749111270     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11866763_62     Document Type: Conference Paper

References (11)

1. Matlaga, B., Eskew, L., and McCullough, D.: Prostate Biopsy: Indications and Technique. The Journal of Urology, 169:1 (2003) 12-19
2. Madabhushi, A., et al.: Automated detection of prostatic adenocarcinoma from high resolution ex-vivo MRI. IEEE Trans. on Med. Imaging, 24:12 (2005) 1611-1625
3. Wetzel, A.W., et al.: Evaluation of prostate tumor grades by content based image retrieval. Proc. of SPIE Annual Meeting 3584 (1999) 244-252
4. Esgiar, A.N., et al.: Microscopic image analysis for quantitative measurement and feature identification of normal and cancerous colonic mucosa. IEEE Trans. on Information Tech. in Biomedicine 2:3 (1998) 197-203
5. Tabesh, A., et al.: Automated prostate cancer diagnosis and Gleason grading of tissue microarrays. Proc. of the SPIE 5747 (2005) 58-70
6. Viola, P., and Jones, M.: Rapid object detection using a boosted cascade of simple features. IEEE Conf. Comp. Vision and Pattern Recog 1 (2001) 511-518
7. Freund, Y., and Schapire, R.: Experiments with a new boosting algorithm. Proc. of the Natural Conf. on Machine Learning (1996) 148-156
8. Adelson, E.H., and Burt, P.J.: Image data compression with the Laplacian pyramid. Proc. of Pattern Recog. and Inf. Proc. Conf. (1981) 218-223
9. Duda, R.O., and Hart, P.E.: Pattern Classification and Scene Analysis. Wiley (1973)
10. Haralick, R.M., Shanmugan, K., and Dinstein, I.: Textural features for image classification. IEEE Trans, on Systems, Man, and Cybernetics SMC-3 (1973) 610-621
11. Manjunath, B.S., and Ma, W.Y.: Texture features for browsing and retrieval of image data. IEEE Trans. Pattern Anal. Machine Intell. 2 (1996) 837-842