A quantitative exploration of efficacy of gland morphology in prostate cancer grading

Proceedings of the IEEE Annual Northeast Bioengineering Conference, NEBEC

Volumn , Issue , 2007, Pages 58-59

  Naik, Shivang ^a   Madabhushi, Anant ^a   Tomaszeweski, John ^b   Feldman, Michael D ^b  

^a RUTGERS UNIVERSITY   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIMENSIONALITY REDUCTION; GRADING; MORPHOLOGY; SUPPORT VECTOR MACHINES; TISSUE; TISSUE ENGINEERING; UROLOGY; VECTOR SPACES;

AUTOMATED IMAGE ANALYSIS; BOUNDARY SEGMENTATION; HISTOLOGICAL IMAGES; LEVEL SET; MORPHOLOGICAL FEATURES; NONLINEAR DIMENSIONALITY REDUCTION; PROSTATE CANCERS; TISSUE ARCHITECTURE;

DISEASES;

EID: 48749115034     PISSN: 1071121X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NEBC.2007.4413278     Document Type: Conference Paper

References (5)

1. Montironi, et al., "Gleason grading of prostate cancer in needle biopsies or radical prostatectomy specimens," BJU Int., vol. 95[8], pp. 1146-1152, 2005.
2. Doyle, et al., "Automated grading of prostate cancer using architectural and textural image features," IEEE ISBI, 2007.
3. Li, et al., "Level set evolution without re-initialization" IEEE CVPR, vol.1, pp. 430-436, 2005.
4. Street, et al., "Nuclear feature extraction for breast tumor diagnosis." SPIE Elec. Imag., pp. 861-70, 1993.
5. Madabhushi, et al., "Graph embedding to improve supervised classification and novel class detection", MICCAI, pp. 729-37, 2005.