Whole brain parcellation with pathology: Validation on ventriculomegaly patients

Aaron Carass*, Muhan Shao, Xiang Li, Blake E. Dewey, Ari M. Blitz, Snehashis Roy, Dzung L. Pham, Jerry L. Prince, Lotta M. Ellingsen

*Corresponding author for this work

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

10 Citations (Scopus)

Abstract

Numerous brain disorders are associated with ventriculomegaly; normal pressure hydrocephalus (NPH) is one example. NPH presents with dementia-like symptoms and is often misdiagnosed as Alzheimer’s due to its chronic nature and nonspecific presenting symptoms. However, unlike other forms of dementia NPH can be treated surgically with an over 80% success rate on appropriately selected patients. Accurate assessment of the ventricles, in particular its sub-compartments, is required to diagnose the condition. Existing segmentation algorithms fail to accurately identify the ventricles in patients with such extreme pathology. We present an improvement to a whole brain segmentation approach that accurately identifies the ventricles and parcellates them into four sub-compartments. Our work is a combination of patch-based tissue segmentation and multi-atlas registration-based labeling. We include a validation on NPH patients, demonstrating superior performance against state-of-the-art methods.

Original languageEnglish
Title of host publicationPatch-Based Techniques in Medical Imaging - 3rd International Workshop, Patch-MI 2017 Held in Conjunction with MICCAI 2017, Proceedings
EditorsYiqiang Zhan, Wenjia Bai, Guorong Wu, Pierrick Coupe, Brent C. Munsell, Gerard Sanroma
PublisherSpringer Verlag
Pages20-28
Number of pages9
ISBN (Print)9783319674339
DOIs
Publication statusPublished - 2017
Event3rd International Workshop on Patch-Based Techniques in Medical Imaging, Patch-MI 2017 held in conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 14 Sept 201714 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10530 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Patch-Based Techniques in Medical Imaging, Patch-MI 2017 held in conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period14/09/1714/09/17

Bibliographical note

Funding Information:
Acknowledgments. This work was supported by the NIH/NINDS under grant R21-NS096497. Support was also provided by the National Multiple Sclerosis Society grant RG-1507-05243 and the Dept. of Defense Center for Neuroscience and Regenerative Medicine.

Publisher Copyright:
© Springer International Publishing AG 2017.

Other keywords

  • Brain
  • Enlarged ventricles
  • Hydrocephalus
  • MRI

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