Tbi lesion segmentation in head CT: Impact of preprocessing and data augmentation

Miguel Monteiro, Konstantinos Kamnitsas, Enzo Ferrante, Francois Mathieu, Steven McDonagh, Sam Cook, Susan Stevenson, Tilak Das, Aneesh Khetani, Tom Newman, Fred Zeiler, Richard Digby, Jonathan P. Coles, Daniel Rueckert, David K. Menon, Virginia F.J. Newcombe, Ben Glocker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Automatic segmentation of lesions in head CT provides key information for patient management, prognosis and disease monitoring. Despite its clinical importance, method development has mostly focused on multi-parametric MRI. Analysis of the brain in CT is challenging due to limited soft tissue contrast and its mono-modal nature. We study the under-explored problem of fine-grained CT segmentation of multiple lesion types (core, blood, oedema) in traumatic brain injury (TBI). We observe that preprocessing and data augmentation choices greatly impact the segmentation accuracy of a neural network, yet these factors are rarely thoroughly assessed in prior work. We design an empirical study that extensively evaluates the impact of different data preprocessing and augmentation methods. We show that these choices can have an impact of up to 18% DSC. We conclude that resampling to isotropic resolution yields improved performance, skull-stripping can be replaced by using the right intensity window, and affine-to-atlas registration is not necessary if we use sufficient spatial augmentation. Since both skull-stripping and affine-to-atlas registration are susceptible to failure, we recommend their alternatives to be used in practice. We believe this is the first work to report results for fine-grained multi-class segmentation of TBI in CT. Our findings may inform further research in this under-explored yet clinically important task of automatic head CT lesion segmentation.

Original languageEnglish
Title of host publicationBrainlesion
Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Revised Selected Papers
EditorsAlessandro Crimi, Spyridon Bakas
PublisherSpringer
Pages13-22
Number of pages10
ISBN (Print)9783030466398
DOIs
StatePublished - 2020
Externally publishedYes
Event5th International MICCAI Brainlesion Workshop, BrainLes 2019, held in conjunction with the Medical Image Computing for Computer Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 17 Oct 201917 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11992 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International MICCAI Brainlesion Workshop, BrainLes 2019, held in conjunction with the Medical Image Computing for Computer Assisted Intervention, MICCAI 2019
Country/TerritoryChina
CityShenzhen
Period17/10/1917/10/19

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