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2021 | OriginalPaper | Buchkapitel

MultiATTUNet: Brain Tumor Segmentation and Survival Multitasking

verfasst von : Diedre Carmo, Leticia Rittner, Roberto Lotufo

Erschienen in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

Verlag: Springer International Publishing

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Abstract

Segmentation of Glioma from three dimensional magnetic resonance imaging (MRI) is useful for diagnosis and surgical treatment of patients with brain tumor. Manual segmentation is expensive, requiring medical specialists. In the recent years, the Brain Tumor Segmentation Challenge (BraTS) has been calling researchers to submit automated glioma segmentation and survival prediction methods for evaluation and discussion over their public, multimodality MRI dataset, with manual annotations. This work presents an exploration of different solutions to the problem, using 3D UNets and self attention for multitasking both predictions and also training (2D) EfficientDet derived segmentations, with the best results submitted for the official challenge leaderboard. We show that end-to-end multitasking survival and segmentation, in this case, led to better results.

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Metadaten
Titel
MultiATTUNet: Brain Tumor Segmentation and Survival Multitasking
verfasst von
Diedre Carmo
Leticia Rittner
Roberto Lotufo
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-72084-1_38

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