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Patient-Specific Semi-supervised Learning for Postoperative Brain Tumor Segmentation
[chapter]
2014
Lecture Notes in Computer Science
In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semisupervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre-and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image
doi:10.1007/978-3-319-10404-1_89
fatcat:3u3th5fcj5bjldtv66hxv56qau