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Jul, 2018
仅使用草图监督学习医学图像分割
Learning to Segment Medical Images with Scribble-Supervision Alone
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Yigit B. Can, Krishna Chaitanya, Basil Mustafa, Lisa M. Koch, Ender Konukoglu...
TL;DR
本文探讨使用草图注释来训练医学图像分割网络的参数的训练策略,并在公共心脏(ACDC)和前列腺(NCI-ISBI)分割数据集上进行评估,结果表明,草图训练的网络与使用完整注释训练的网络相比,其Dice系数的下降仅为2.9%(心脏)和4.5%(前列腺)。
Abstract
semantic segmentation
of
medical images
is a crucial step for the quantification of healthy anatomy and diseases alike. The majority of the current state-of-the-art segmentation algorithms are based on
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