Unsupervised quality assurance for brain MR image rigid registration using latent shape representation

Yuan Xue; Lianrui Zuo; Samuel W. Remedios; Blake E. Dewey; Peiyu Duan; Yihao Liu; Rendong Zhang; Scott D. Newsome; Ellen M. Mowry; Aaron Carass; Jerry L. Prince

doi:10.1117/12.2647484

3 April 2023 Unsupervised quality assurance for brain MR image rigid registration using latent shape representation

Yuan Xue, Lianrui Zuo, Samuel W. Remedios, Blake E. Dewey, Peiyu Duan, Yihao Liu, Rendong Zhang, Scott D. Newsome, Ellen M. Mowry, Aaron Carass, Jerry L. Prince

Author Affiliations +

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124641G (2023) https://doi.org/10.1117/12.2647484
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Linear registration to a standard space is a crucial early step in the processing of magnetic resonance images (MRIs) of the human brain. Thus an accurate registration is essential for subsequent image processing steps, as well as downstream analyses. Registration failures are not uncommon due to poor image quality, irregular head shapes, and bad initialization. Traditional quality assurance (QA) for registration requires a substantial manual assessment of the registration results. In this paper, we propose an automatic quality assurance method for the rigid registration of brain MRIs. Without using any manual annotations in the model training, our proposed QA method achieved 99.1% sensitivity and 86.7% specificity in a pilot study on 537 T1-weighted scans acquired from multiple imaging centers.

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Yuan Xue, Lianrui Zuo, Samuel W. Remedios, Blake E. Dewey, Peiyu Duan, Yihao Liu, Rendong Zhang, Scott D. Newsome, Ellen M. Mowry, Aaron Carass, and Jerry L. Prince "Unsupervised quality assurance for brain MR image rigid registration using latent shape representation", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124641G (3 April 2023); https://doi.org/10.1117/12.2647484

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