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MixMicrobleed: Multi-stage detection and segmentation of cerebral microbleeds

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arxiv 2108.02482 v1 pith:7HS6VAVH submitted 2021-08-05 eess.IV cs.CV

MixMicrobleed: Multi-stage detection and segmentation of cerebral microbleeds

Marta Girones Sanguesa , Denis Kutnar , Bas H.M. van der Velden , Hugo J. Kuijf This is my paper
classification eess.IV cs.CV
keywords microbleedsegmentationcerebraldetectionmicrobleedsmulti-stagepossiblework
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Cerebral microbleeds are small, dark, round lesions that can be visualised on T2*-weighted MRI or other sequences sensitive to susceptibility effects. In this work, we propose a multi-stage approach to both microbleed detection and segmentation. First, possible microbleed locations are detected with a Mask R-CNN technique. Second, at each possible microbleed location, a simple U-Net performs the final segmentation. This work used the 72 subjects as training data provided by the "Where is VALDO?" challenge of MICCAI 2021.

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