Context aware 3D cnns for brain tumor segmentation

Siddhartha Chandra, Maria Vakalopoulou, Lucas Fidon, Enzo Battistella, Théo Estienne, Roger Sun, Charlotte Robert, Eric Deutsch, Nikos Paragios

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

    30 Citations (Scopus)

    Abstract

    In this work we propose a novel deep learning based pipeline for the task of brain tumor segmentation. Our pipeline consists of three primary components: (i) a preprocessing stage that exploits histogram standardization to mitigate inaccuracies in measured brain modalities, (ii) a first prediction stage that uses the V-Net deep learning architecture to output dense, per voxel class probabilities, and (iii) a prediction refinement stage that uses a Conditional Random Field (CRF) with a bilateral filtering objective for better context awareness. Additionally, we compare the V-Net architecture with a custom 3D Residual Network architecture, trained on a multi-view strategy, and our ablation experiments indicate that V-Net outperforms the 3D ResNet-18 with all bells and whistles, while fully connected CRFs as post processing, boost the performance of both networks. We report competitive results on the BraTS 2018 validation and test set.

    Original languageEnglish
    Title of host publicationBrainlesion
    Subtitle of host publicationGlioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers
    EditorsFarahani Keyvan, Spyridon Bakas, Hugo Kuijf, Mauricio Reyes, Alessandro Crimi, Theo van Walsum
    PublisherSpringer Verlag
    Pages299-310
    Number of pages12
    ISBN (Print)9783030117252
    DOIs
    Publication statusPublished - 1 Jan 2019
    Event4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018 - Granada, Spain
    Duration: 16 Sept 201820 Sept 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11384 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference4th International MICCAI Brainlesion Workshop, BrainLes 2018 held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2018
    Country/TerritorySpain
    CityGranada
    Period16/09/1820/09/18

    Keywords

    • 3-D fully convolutional CNNs
    • Brain tumor segmentation
    • Fully-connected CRFs

    Cite this