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Deformable MRI Sequence Registration for AI-based Prostate Cancer Diagnosis
April 16, 2024, 4:48 a.m. | Alessa Hering, Sarah de Boer, Anindo Saha, Jasper J. Twilt, Derya Yakar, Maarten de Rooij, Henkjan Huisman, Joeran S. Bosma
cs.CV updates on arXiv.org arxiv.org
Abstract: The PI-CAI (Prostate Imaging: Cancer AI) challenge led to expert-level diagnostic algorithms for clinically significant prostate cancer detection. The algorithms receive biparametric MRI scans as input, which consist of T2-weighted and diffusion-weighted scans. These scans can be misaligned due to multiple factors in the scanning process. Image registration can alleviate this issue by predicting the deformation between the sequences. We investigate the effect of image registration on the diagnostic performance of AI-based prostate cancer diagnosis. …
abstract algorithms arxiv cai cancer cancer detection cancer diagnosis challenge cs.cv detection diagnosis diagnostic diffusion eess.iv expert imaging mri multiple process q-bio.qm registration scans type
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