Recent advancement in learning methodology for segmenting brain tumor from magnetic resonance imaging -a review
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14857-5.pdf
Reference175 articles.
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3. Agravat RR, Raval MS (2019) Brain tumor segmentation and survival prediction. In: Crimi A, Bakas S (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2019. Lecture Notes in Computer Science, vol 11992. Springer, Cham. https://doi.org/10.1007/978-3-030-46640-4_32
4. Ahuja S, Panigrahi BK, Gandhi T (2020) Transfer learning-based brain tumor detection and segmentation using superpixel technique. In: 2020 international conference on contemporary computing and applications (IC3A), pp 244–249. https://doi.org/10.1109/IC3A48958.2020.233306
5. Akil M, Saouli R, Kachouri R (2020) Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy. Med Image Anal 63:101692
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