Classification of breast-tissue microarray spots using colour and local invariants

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Volumn , Issue , 2008, Pages 999-1002

  Amaral, Telmo ^a   McKenna, Stephen ^a   Robertson, Katherine ^a   Thompson, Alastair ^a  

^a UNIVERSITY OF DUNDEE   (United Kingdom)

Author keywords

Biological tissues; Image texture analysis

Indexed keywords

BIOASSAY; CHEMOTHERAPY; CHLORINE COMPOUNDS; COLOR; COMPUTER NETWORKS; DEBRIS; LABELING; LABELS; MICROARRAYS; OPTICAL PROPERTIES; PROBABILITY; RISK ASSESSMENT; TECHNICAL PRESENTATIONS; TUMORS;

BIOLOGICAL TISSUES; BIOMEDICAL IMAGING; IMAGE TEXTURE ANALYSIS; INTERNATIONAL SYMPOSIUM;

PIXELS;

EID: 51049094185     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2008.4541167     Document Type: Conference Paper

References (12)

1. J. Kononen, L. Bubendorf, A. Kallionimeni, M. Bärlund, P. Schraml, S. Leighton, J. Torhorst, M. Mihatsch, G. Sauter, and O. Kallionimeni, "Tissue microarrays for high-throughput molecular profiling of tumor specimens," Nature Med., vol. 4, no. 7, pp. 844-847, 1998.
2. R. Camp, L. Charette, and D. Rimm, "Validation of tissue microarray technology in breast carcinoma," Lab. Investigation, vol. 80, no. 12, pp. 1943-1949, 2000.
3. C. Schmid and R. Mohr, "Matching by local invariants," Tech. Rep. RR-2644, INRIA, 1995.
4. C. Schmid and R. Mohr, "Local grayvalue invariants for image retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 5, pp. 530-535, 1997.
5. J. Koenderink and A. van Doom, "Representation of local geometry in the visual system," Biological Cybernetics, vol. 55, no. 6, pp. 367-375, 1987.
6. A. Tabesh and M. Teverovskiy, "Tumor classification in histological images of prostate using color texture," in Asilomar Conference on Signals, Systems and Computers. 2006, pp. 841-845, IEEE, Inc.
7. S. Doyle, M. Hwang, K. Shah, A. Madabhushi, M. Feldman, and J. Tomaszeweski, "Automated grading of prostate cancer using architectural and textural image features," in IEEE ISBI, 2007, pp. 1284-1287.
8. M. Ranzato, P. Taylor, J. House, R. Flagan, Y. LeCun, and P. Perona, "Automatic recognition of biological particles in microscopic images," Pattern Recognition Letters, vol. 28, no. 1, pp. 31-39, 2007.
9. Adjuvant Breast Cancer Trials Collaborative Group, "Polychemotherapy for early breast cancer: Results from the international adjuvant breast cancer chemotherapy randomized trial," J. National Cancer Institute, vol. 99, no. 7, pp. 506-515, 2007.
10. S. Detre, G. Saccani Jotti, and M. Dowsett, "A " quickscore" method for immunohistochemical semiquantitation: validation for oestrogen receptor in breast carcinomas," Journal of Clinical Pathology, vol. 48, no. 9, pp. 876-878, September 1995.
11. I. Nabney, NETLAB: algorithms for pattern recognition, Springer-Verlag, New York, 2002.
12. G. Ramakrishnan, K. Chitrapura, R. Krishnapuram, and P. Bhattacharyya, "A model for handling approximate, noisy or incomplete labeling in text classification," in ICML, New York, 2005, pp. 681-688, ACM.