Deep Hourglass for Brain Tumor Segmentation

Benson, Eze; Pound, Michael P.; French, Andrew P.; Jackson, Aaron S.; Pridmore, Tony P.

Abstract

The segmentation of a brain tumour in an MRI scan is a challenging task, in this paper we present our results for this problem via the BraTS 2018 challenge, consisting of 210 high grade glioma (HGG) and 75 low grade glioma (LGG) volumes for training. We train and evaluate a convolutional neural network (CNN) encoder-decoder network based on a singular hourglass structure. The hourglass network is able to classify the whole tumour (WT), enhancing (ET) tumour and core tumour (TC) in one pass. We apply a small amount of preprocessing to the data before feeding it to the network but no post processing. We apply our method to two different unseen sets of volumes containing 66 and 191 volumes. We achieve an overall Dice coefficient of 92% on the training set. On the first unseen set our network achieves Dice coefficients of 0.66, 0.82 and 0.72 for ET, WT and TC. On the second unseen set our network achieves Dice coefficients of 0.62, 0.79 and 0.65 on ET, WT and TC.

Citation

Benson, E., Pound, M. P., French, A. P., Jackson, A. S., & Pridmore, T. P. (2019). Deep Hourglass for Brain Tumor Segmentation. In BrainLes 2018: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (419-428). Springer. https://doi.org/10.1007/978-3-030-11726-9_37

• Acceptance Date: Jan 1, 2019
• Online Publication Date: Jan 26, 2019
• Publication Date: 2019
• Deposit Date: May 16, 2019
• Publicly Available Date: May 16, 2019
• Journal: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Lecture Notes in Computer Science
• Print ISSN: 0302-9743
• Electronic ISSN: 1611-3349
• Publisher: Springer
• Pages: 419-428
• Series Title: Lecture Notes in Computer Science
• Series Number: 11384
• Series ISSN: 0302-9743
• Book Title: BrainLes 2018: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
• ISBN: 9783030117252
• DOI: https://doi.org/10.1007/978-3-030-11726-9_37
• Public URL: https://nottingham-repository.worktribe.com/output/2058382
• Publisher URL: https://link.springer.com/chapter/10.1007/978-3-030-11726-9_37
• Additional Information: First Online: 26 January 2019; Conference Acronym: BrainLes; Conference Name: International MICCAI Brainlesion Workshop; Conference City: Granada; Conference Country: Spain; Conference Year: 2018; Conference Start Date: 16 September 2018; Conference End Date: 16 September 2018; Conference Number: 4; Conference ID: iwb2018; Conference URL: http://www.brainlesion-workshop.org/; Type: Single-blind; Conference Management System: Microsoft CMT; Number of Submissions Sent for Review: 95; Number of Full Papers Accepted: 92; Number of Short Papers Accepted: 0; Acceptance Rate of Full Papers: 97% - The value is computed by the equation "Number of Full Papers Accepted / Number of Submissions Sent for Review * 100" and then rounded to a whole number.; Average Number of Reviews per Paper: 3; Average Number of Papers per Reviewer: 3; External Reviewers Involved: Yes