Multi-atlas segmentation of the hydrocephalus brain using an adaptive ventricle atlas

Muhan Shao; Aaron Carass; Xiang Li; Blake E. Dewey; Ari M. Blitz; Jerry L. Prince; Lotta M. Ellingsen

doi:10.1117/12.2295613

12 March 2018 Multi-atlas segmentation of the hydrocephalus brain using an adaptive ventricle atlas

Muhan Shao, Aaron Carass, Xiang Li, Blake E. Dewey, Ari M. Blitz, Jerry L. Prince, Lotta M. Ellingsen

Proceedings Volume 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging; 105780F (2018) https://doi.org/10.1117/12.2295613
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

Normal pressure hydrocephalus (NPH) is a brain disorder caused by disruption of the flow of cerebrospinal fluid (CSF). The dementia-like symptoms of NPH are often mistakenly attributed to Alzheimer’s disease. However, if correctly diagnosed, NPH patients can potentially be treated and their symptoms reversed through surgery. Observing the dilated ventricles through magnetic resonance imaging (MRI) is one element in diagnosing NPH. Diagnostic accuracy therefore benefits from accurate, automatic parcellation of the ventricular system into its sub-compartments. We present an improvement to a whole brain segmentation approach designed for subjects with enlarged and deformed ventricles. Our method incorporates an adaptive ventricle atlas from an NPH-atlas-based segmentation as a prior and uses a more robust relaxation scheme for the multi-atlas label fusion approach that accurately labels the four sub-compartments of the ventricular system. We validated our method on NPH patients, demonstrating improvement over state-of-the-art segmentation techniques.

Conference Presentation

Citation Download Citation

Muhan Shao, Aaron Carass, Xiang Li, Blake E. Dewey, Ari M. Blitz, Jerry L. Prince, and Lotta M. Ellingsen "Multi-atlas segmentation of the hydrocephalus brain using an adaptive ventricle atlas", Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 105780F (12 March 2018); https://doi.org/10.1117/12.2295613

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