A Bi-directional, Multi-modality Framework for Segmentation of Brain Structures

Skylar S. Gay, Cenji Yu, Dong Joo Rhee, Carlos Sjogreen, Raymond P. Mumme, Callistus M. Nguyen, Tucker J. Netherton, Carlos E. Cardenas, Laurence E. Court

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Careful delineation of normal-tissue organs-at-risk is essential for brain tumor radiotherapy. However, this process is time-consuming and subject to variability. In this work, we propose a multi-modality framework that automatically segments eleven structures. Large structures used for defining the clinical target volume (CTV), such as the cerebellum, are directly segmented from T1-weighted and T2-weighted MR images. Smaller structures used in radiotherapy plan optimization are more difficult to segment, thus, a region of interest is first identified and cropped by a classification model, and then these structures are segmented from the new volume. This bi-directional framework allows for rapid model segmentation and good performance on a standardized challenge dataset when evaluated with volumetric and surface metrics.

Original languageEnglish (US)
Title of host publicationSegmentation, Classification, and Registration of Multi-modality Medical Imaging Data - MICCAI 2020 Challenges, ABCs 2020, L2R 2020, TN-SCUI 2020, Held in Conjunction with MICCAI 2020, Proceedings
EditorsNadya Shusharina, Mattias P. Heinrich, Ruobing Huang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages49-57
Number of pages9
ISBN (Print)9783030718268
DOIs
StatePublished - 2021
EventAnatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, ABCs 2020, Learn2Reg Challenge, L2R 2020 and Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge, TN-SCUI 2020 held in conjunction with 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 - Lima, Peru
Duration: Oct 4 2020Oct 8 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12587 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceAnatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, ABCs 2020, Learn2Reg Challenge, L2R 2020 and Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge, TN-SCUI 2020 held in conjunction with 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020
Country/TerritoryPeru
CityLima
Period10/4/2010/8/20

Keywords

  • ABCs
  • Deep learning
  • MICCAI 2020
  • Segmentation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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