Detecting prostatic adenocarcinoma from digitized histology using a multi-scale hierarchical classification approach

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn , Issue , 2006, Pages 4759-4762

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

^a RUTGERS UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

AdaBoost; Decision trees; Digitized histology; Hierarchical classifier; Prostate cancer

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DECISION TREES; HIERARCHICAL SYSTEMS; HISTOLOGY; PIXELS; TISSUE;

ADABOOST; DIGITIZED HISTOLOGY; HIERARCHICAL CLASSIFIERS; PROSTATE CANCER;

TUMORS;

ADENOCARCINOMA; ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; AUTOMATION; BIOPSY; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; DECISION SUPPORT SYSTEM; EQUIPMENT; HUMAN; IMAGE PROCESSING; MALE; METHODOLOGY; PATHOLOGY; PROSTATE TUMOR; REPRODUCIBILITY; STATISTICAL MODEL; THEORETICAL MODEL;

ADENOCARCINOMA; ALGORITHMS; AUTOMATION; BIOPSY; DECISION SUPPORT TECHNIQUES; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; MODELS, STATISTICAL; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; PROSTATIC NEOPLASMS; REPRODUCIBILITY OF RESULTS; SOFTWARE;

EID: 34047133289     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2006.260188     Document Type: Conference Paper

References (8)

1. Wetzel, A.W., et al., Evaluation of prostate tumor grades by content based image retrieval, Proc. of SPIE, 1999, pp 244-252.
2. Esgiar, A.N., et al., Microscopic image analysis for quantitative measurement and feature identification of normal and cancerous colonie mucosa, IEEE Trans. on Inf. Tech. in Biomedicine, 1998, pp 197-203.
3. Tabesh, A., et al., Automated prostate cancer diagnosis and Gleason grading of tissue microarrays, Proc. of SPIE, 2005, pp 58-70.
4. Viola, P., and Jones, M., Robust Real-Time Face Detection, Intl. J. of Computer Vision, vol. 57(2), 2004, pp 137-154.
5. Adelson, E.H., Burt, P.J., Image data compression with the Laplacian pyramid, Proc. of Patt. Recog. Inf. Proc., 1981, pp 218-223.
6. Freund, Y., and Schapire, R., Experiments with a new boosting algorithm, Proc. of Natural Conf. on Machine Learning, 1996, pp 148-156.
7. Quinlan, J.R., Bagging, Boosting, and C4.5, 13th Nat. Conf. on Artificial Intel., 1996, pp 725-730.
8. Duda, R.O., and Hart, P.E., Pattern Classification and Scene Analysis, NY, Wiley, 1973.