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Abstract #1904

Improving Segmentation Method with the Combination between Deep Learning and Uncertainties in Brain Tumor

Joohyun Lee1, Jongho Lee1, and Haejin Kim2
1Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea, 2Department of Basic Science and Technology, Hongik University, Sejong, Republic of Korea

Although segmentation using deep learning performs well, it often works poorly on small lesions or boundaries of lesion. This can occur the serious issues when applying in the medical images and the more reliable method is essential. In this study, we developed a deep learning process based on the uncertainty measurements that improves brain tumor segmentation. For selectively maximizing either precision or recall, two types of segmentation methods were presented.

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