Mitosis Detection in Breast Cancer Histological Images (MITOS dataset)
We propose a contest of mitosis detection in images of H&E stained slides of breast cancer. Mitotic count is an important parameter for the prognosis of breast cancer. However, mitosis detection is a challenging problem and has not been addressed well in the literature. Indeed, mitosis detection is very challenging since mitosis appear in image as small objects with a large variety of shapes, and they can thus be confused with some other objects or artefacts present in the image.
We add a further dimension to the contest by using two different slide scanners having different resolution to produce RGB images and a multi-spectral microscope producing images in 10 different spectral bands and 17 layers Z-stack.
The Journal of Pathology Informatics has published papers of four contestants in its Volume 4, Issue 1 on May 30th, 2013.
Ludovic Roux, Daniel Racoceanu, Nicolas Loménie, Maria Kulikova, Humayun Irshad, Jacques Klossa, Frédérique Capron, Catherine Genestie, Gilles Le Naour, Metin N. Gurcan, "Mitosis detection in breast cancer histological images: An ICPR 2012 contest"
Christopher D. Malon, Eric Cosatto, "Classification of mitotic figures with convolutional neural networks and seeded blob features"
Adnan Mujahid Khan, Hesham ElDaly, Nasir M. Rajpoot, "A gamma-gaussian mixture model for detection of mitotic cells in breast cancer histopathology images"
Publications Related to the Contest
- Ardhendu Shekhar Tripathi, Atin Mathur, Mohit Daga, Manohar Kuse, Oscar C. Au, "2-SiMDoM: A 2-Sieve Model for Detection of Mitosis in Multispectral Breast Cancer Imagery", Proceedings of IEEE ICIP, Melbourne, Australia, September 2013.
As of July 15th, 2012, there are 129 companies / research institutes / universities in 40 countries registered to the contest.
17 teams have sent their detection results.
New contest: MITOS & ATYPIA at ICPR 2014
We have launched an enhanced version of the contest entitled MITOS & ATYPIA to be hosted by conference ICPR 2014.
Highlights of this new contest:
- frames at x20 and x40 magnification
- list of mitosis annotated by two or three pathologists
- confidence degree for each mitosis according to pathologists agreement or disagreement
- scores for nuclear pleomorphism by two or three pathologists
- values of six criteria related to nuclear pleomorphism given by three pathologists
Contest AMIDA13 at MICCAI 2013
AMIDA13 is another contest on mitosis detection that was held during MICCAI 2013 conference.
Metin N. Gurcan, Laura E. Boucheron, Ali Can, Anant Madabhushi, Nasir M. Rajpoot, and Bulent Yener, "Histopathological Image Analysis: A Review", IEEE Reviews in Biomedical Engineering, vol. 2, pp 147-171, 2009.
"Breast Cancer Grading Poster", NHS Cancer Screening Programmes and The Royal College of Pathologists, 2005 (PDF file size: 1.3 MB).
"Pathology Reporting of Breast Disease", NHS Cancer Screening Programmes and The Royal College of Pathologists, 2005 (PDF file size: 3.1 MB).
Elston, C.W. and Ellis, I.O., "Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: Experience from a large study with long-term follow-up", Histopathology, vol. 19, pp 403-410, 1991.
|This contest is supported by the French National Research Agency ANR, project MICO under reference ANR-10-TECS-015.|