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Lesion segmentation using U-Net network

2018-07-23 21:54:35
Adrien Motsch, Sebastien Motsch, Thibaut Saguet
arXiv_CV
         
Abstract

This paper explains the method used in the segmentation challenge (Task 1) in the International Skin Imaging Collaboration's (ISIC) Skin Lesion Analysis Towards Melanoma Detection challenge held in 2018. We have trained a U-Net network to perform the segmentation. The key elements for the training were first to adjust the loss function to incorporate unbalanced proportion of background and second to perform post-processing operation to adjust the contour of the prediction.

Abstract (translated)

本文解释了2018年举行的国际皮肤成像协作组织（ISIC）皮肤病变分析对黑色素瘤检测挑战中的分割挑战（任务1）中使用的方法。我们已经训练了一个U-Net网络来执行分割。培训的关键要素是首先调整损失函数以包含不平衡的背景比例，然后进行后处理操作以调整预测的轮廓。

URL

https://arxiv.org/abs/1807.08844

PDF

https://arxiv.org/pdf/1807.08844.pdf

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