MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning.

ABSTRACT: Segmentation of organs or lesions from medical images plays an essential role in many clinical applications such as diagnosis and treatment planning. Though Convolutional Neural Networks (CNN) have achieved the state-of-the-art performance for automatic segmentation, they are often limited by the lack of clinically acceptable accuracy and robustness in complex cases. Therefore, interactive segmentation is a practical alternative to these methods. However, traditional interactive segmentation methods require a large number of user interactions, and recently proposed CNN-based interactive segmentation methods are limited by poor performance on previously unseen objects. To solve these problems, we propose a novel deep learning-based interactive segmentation method that not only has high effi

SUBMITTER: Luo X 

PROVIDER: S-EPMC7613452 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature