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. 2021 Jan 20;10:586292. doi: 10.3389/fonc.2020.586292

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Copyright © 2021 Zormpas-Petridis, Noguera, Ivankovic, Roxanis, Jamin and Yuan

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Representative examples of the SLIC superpixels segmentation and ground-truth annotations in TCGA melanoma samples (A) Whole-slide image segmentation using the SLIC superpixels algorithm. Note how the superpixels adhere to the boundaries of the different components of the tumor with each superpixel containing a single type of tissue (B) Ground-truth annotations are provided by the pathologists by marking samples of the region components (the different colors represent different regions) without the need for delineating the boundaries of the tumor components.