Deep learning-based head and neck segmentation in CT angiography

Prakhar Prakash; Theodore Colwell; Mara Noskowiak; Michail Fanariotis; Sandeep Dutta

doi:10.1117/12.3006798

2 April 2024 Deep learning-based head and neck segmentation in CT angiography

Prakhar Prakash, Theodore Colwell, Mara Noskowiak, Michail Fanariotis, Sandeep Dutta

Author Affiliations +

Proceedings Volume 12930, Medical Imaging 2024: Clinical and Biomedical Imaging; 1293003 (2024) https://doi.org/10.1117/12.3006798
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Abstract

The identification of pathologies in CT Angiography (CTA) is a laborious process. Even with the use of advanced post-processing techniques (such as Maximum Intensity Projection (MIP) and Volume Rendering (VR)) the analysis of the head and neck vasculature is a challenging task due to the interference from the surrounding osseous anatomy. To address these issues, we introduce an innovative solution in the form of an Artificial Intelligence (AI) reconstruction system. This system is supported by a 3D convolutional neural network, specially trained to automate the process of CTA reconstruction in healthcare services. In this study, we demonstrate a novel solution based on Deep Learning (DL) for the purpose of automatically segmenting skeletal structures, calcified plaque, and arterial vessels within CTA images. The advanced DL segmentation models that have been developed can perform accurately across different anatomies, scans, and reconstruction settings and allow superior visualization of vascular anatomy and pathology compared to other conventional techniques. These models have shown remarkable performance with a mean dice score of 0.985 for the bone structures. This high score, attained on an independent validation dataset that was kept separate during the training process, reflects the model's strength and potential for reliable application in real-world settings.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Prakhar Prakash, Theodore Colwell, Mara Noskowiak, Michail Fanariotis, and Sandeep Dutta "Deep learning-based head and neck segmentation in CT angiography", Proc. SPIE 12930, Medical Imaging 2024: Clinical and Biomedical Imaging, 1293003 (2 April 2024); https://doi.org/10.1117/12.3006798

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