MICCAI 2015 Cell Detection using Proximity Score Regression

Watch the short video on YouTube for an overview of the method.

Bone Marrow Hematoxylin&Eosin Dataset Download

Download the image data and the ground truth annotations as compressed ZIP here.

Code Demo

Find the description of how to run the code in the code and demo directories.

Disclaimer

Cell Detection Application Code: Copyright (c) 2015-2016
Philipp Kainz, Martin Urschler, Samuel Schulter, Paul Wohlhart, Vincent Lepetit
Institute of Biophysics, Medical of University Graz, Austria.
Institute for Computer Graphics and Vision (ICG), Graz University of Technology, Austria.
All rights reserved.

Random Forest Framework Code: Copyright (c) 2011-2016
Samuel Schulter, Paul Wohlhart, Christian Leistner, Amir Saffari, Peter M. Roth, Horst Bischof.
Institute for Computer Graphics and Vision (ICG), Graz University of Technology, Austria.
All rights reserved.

Conditions of use

Permission to use this code is granted for non-commercial applications only!
P. Kainz, M. Urschler, S. Schulter, P. Wohlhart, and V. Lepetit. You should use regression to detect cells. In A. F. Frangi, J. Hornegger, N. Navab, and S. Wells, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, Lecture Notes in Computer Science, Munich, Germany, Oct. 5-9 2015. Springer.

@inproceedings{Kainz15,
  author = "P. Kainz and M. Urschler and S. Schulter and P. Wohlhart and V. Lepetit",
  title = {{You Should Use Regression to Detect Cells}},
  booktitle = {{International Conference on Medical Image Computing and Computer Assisted Intervention}},
  year = 2015
}

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