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Published in:
2015 | OriginalPaper | Chapter
A Novel Cell Detection Method Using Deep Convolutional Neural Network and Maximum-Weight Independent Set
Authors : Fujun Liu, Lin Yang
Published in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
Publisher: Springer International Publishing
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Cell detection is an important topic in biomedical image analysis and it is often the prerequisite for the following segmentation or classification procedures. In this paper, we propose a novel algorithm for general cell detection problem: Firstly, a set of cell detection candidates is generated using different algorithms with varying parameters. Secondly, each candidate is assigned a score by a trained deep convolutional neural network (DCNN). Finally, a subset of best detection results are selected from all candidates to compose the final cell detection results. The subset selection task is formalized as a maximum-weight independent set problem, which is designed to find the heaviest subset of mutually non-adjacent nodes in a graph. Experiments show that the proposed general cell detection algorithm provides detection results that are dramatically better than any individual cell detection algorithm.