Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection

arXiv:2403.12748v1 Announce Type: new
Abstract: Brain tumor image segmentation is a challenging research topic in which deep-learning models have presented the best results. However, the traditional way of training those models from many pre-annotated images leaves several unanswered questions. Hence methodologies, such as Feature Learning from Image Markers (FLIM), have involved an expert in the learning loop to reduce human effort in data annotation and build models sufficiently deep for a given problem. FLIM has been successfully used to create …

abstract arxiv brain building cs.ai cs.cv feature filter however image images networks questions research results segmentation training type