Brain Tumor segmentation and parsing on MRIs using multiresolution neural networks
Silvana Castillo L, Alexandra Daza L, Rivera LC, Arbelaez P (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Verlag
Book Volume: 10670 LNCS
Pages Range: 332-343
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Quebec City, QC
ISBN: 9783319752372
DOI: 10.1007/978-3-319-75238-9_29
Abstract
Brain lesion segmentation is a critical application of computer vision to the biomedical image analysis. The difficulty is derived from the great variance between instances, and the high computational cost of processing three dimensional data. We introduce a neural network for brain tumor semantic segmentation that parses their internal structures and is capable of processing volumetric data from multiple MRI modalities simultaneously. As a result, the method is able to learn from small training datasets. We develop an architecture that has four parallel pathways with residual connections. It receives patches from images with different spatial resolutions and analyzes them independently. The results are then combined using fully-connected layers to obtain a semantic segmentation of the brain tumor. We evaluated our method using the 2017 BraTS Challenge dataset, reaching average dice coefficients of 89 %, 88 % and 86 % over the training, validation and test images, respectively.
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APA:
Silvana Castillo, L., Alexandra Daza, L., Rivera, L.C., & Arbelaez, P. (2018). Brain Tumor segmentation and parsing on MRIs using multiresolution neural networks. In Bjoern Menze, Alessandro Crimi, Hugo Kuijf, Mauricio Reyes, Spyridon Bakas (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 332-343). Quebec City, QC, CA: Springer Verlag.
MLA:
Silvana Castillo, Laura, et al. "Brain Tumor segmentation and parsing on MRIs using multiresolution neural networks." Proceedings of the 3rd International Workshop on Brainlesion, BrainLes 2017 Held in Conjunction with Medical Image Computing for Computer Assisted Intervention , MICCAI 2017, Quebec City, QC Ed. Bjoern Menze, Alessandro Crimi, Hugo Kuijf, Mauricio Reyes, Spyridon Bakas, Springer Verlag, 2018. 332-343.
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