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Conference material: "Proceedings of the International Conference on Computer Graphics and Vision Graphicon (19-21 September 2023, Moscow)"
Authors: Yakovlev N., Khvostikov A.V., Krylov A.S.
Method for automatic initialization of trainable active contours for instance segmentation in histological images
The method of trainable active contour is one of the semi-automatic segmentation methods that can be applied to segment glands in histological images. In this paper, we propose a method for automatic initialization of trainable active contour model, which makes the segmentation method fully automatic. Using a U-Net like architecture, a preprocessed image segmentation masks is predicted for the input image, from which initial approximations of contours are calculated for each gland. The proposed method correctly marks 96.2 % part for the glands on the test set of the PATH-DT-MSU S1-v2 dataset. As a result, we get initial approximations located inside each gland in the image.
Glands segmentation, active contours, convolution neural networks, histological images, instance segmentation
Publication language: english,  pages: 11 (p. 598-608)
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About authors:
  • Yakovlev Nikita, Moscow State University
  • Khvostikov Alexander Vladimirovich, Moscow State University
  • Krylov Andrey Serdjevich, Moscow State University