Challenge in mitotic figures detection in H&E stained breast cancer histopathology images

| April 9, 2013

Challenge in mitotic figures detection in H&E stained breast cancer histopathology images will be organized this September as part of MICCAI 2013 in Nagoya Japan:

Mitotic activity, expressed as the number of mitotic figures per tissue area, is one of the strongest prognosticators for invasive breast carcinoma.  Although it has strong prognostic value, it is a tedious task prone to observer variability. With the advent of digital imaging in pathology, which has enabled cost and time efficient digitization of whole histological slides, automatic image analysis has been suggested as a way to tackle these problems. The goal of this challenge is to evaluate and compare (semi-)automatic mitotic figure detection methods that work on regions extracted from whole-slide images. It is our strong belief that providing open access to a high quality annotated dataset can lead to major advancement in the development of a successful mitotic detection method.

Teams or individuals interested in participating in the challenge can register on the website: Upon registration,
the participants will be able to download the training set that they can use to develop their method. At the end of May 2013, a testing set will become available for download. The participants will be able to
run their method on the testing set and send their results for evaluation.

All participants will be invited to attend the challenge workshop on September 26th. After the workshop, a summary article describing the proposed methods and results will be written and sent to a high-impact
peer-reviewed journal.

===Important dates===

March 28th – Training set available for download;

May 27th – Testing set available for download;

July 22nd – Conference early bird registration deadline;

September 8th – Deadline for submission of results that will be
presented at the workshop;

September 26th – Workshop date



Mitko Veta, Max A. Viergever, Josien P.W. Pluim
Image Sciences Institute, University Medical Center Utrecht

Nikolaos Stathonikos, Paul J. van Diest
Pathology Department, University Medical Center Utrecht

Category: Advocacy, Anatomic Pathology, Clinical Laboratories, Conferences, Current Affairs, Digital Pathology News, Education, File format, Image Analysis, Medical Research, Pathology News

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