Investigation of probability maps in deep-learning-based brain ventricle parcellation

Yuli Wang; Anqi Feng; Yuan Xue; Muhan Shao; Ari M. Blitz; Mark D. Luciano; Aaron Carass; Jerry L. Prince

doi:10.1117/12.2653999

3 April 2023 Investigation of probability maps in deep-learning-based brain ventricle parcellation

Yuli Wang, Anqi Feng, Yuan Xue, Muhan Shao, Ari M. Blitz, Mark D. Luciano, Aaron Carass, Jerry L. Prince

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124642G (2023) https://doi.org/10.1117/12.2653999
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

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Abstract

Normal Pressure Hydrocephalus (NPH) is a brain disorder associated with ventriculomegaly. Accurate segmentation of the ventricle system into its sub-compartments from magnetic resonance images (MRIs) could help evaluate NPH patients for surgical intervention. In this paper, we modify a 3D U-net utilizing probability maps to perform accurate ventricle parcellation, even with grossly enlarged ventricles and post-surgery shunt artifacts, from MRIs. Our method achieves a mean dice similarity coefficient (DSC) on whole ventricles for healthy controls of 0.864 ± 0.047 and 0.961 ± 0.024 for NPH patients. Furthermore, with the benefit of probability maps, the proposed method provides superior performance on MRI with grossly enlarged ventricles (mean DSC value of 0.965 ± 0.027) or post-surgery shunt artifacts (mean DSC value of 0.964 ± 0.031). Results indicate that our method provides a high robust parcellation tool on the ventricular systems which is comparable to other state-of-the-art methods.

Citation Download Citation

Yuli Wang, Anqi Feng, Yuan Xue, Muhan Shao, Ari M. Blitz, Mark D. Luciano, Aaron Carass, and Jerry L. Prince "Investigation of probability maps in deep-learning-based brain ventricle parcellation", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124642G (3 April 2023); https://doi.org/10.1117/12.2653999

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