Authors
Shen, Chen
Wang, Chenglong
Oda, Masahiro
Mori, Kensaku
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Issue Date
2019
Publisher
University of Minnesota Libraries Publishing
Type
Article
Abstract
Segmentation is one of the most important tasks in medical image analysis. With the development of deep leaning, fully convolutional networks (FCNs) have become the dominant approach for this task and their extension to 3D achieved considerable improvements for automated organ segmentation in volumetric imaging data. In this paper we demonstrate a coarse-to-fine segmentation method using FCNs for Kits 2019 challenge.
Identifiers
doi: 10.24926/548719.072