Baris Turkbey
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Benchmarking AI-generated thin-slice CT under clinical reconstruction conditions: a multicohort study
Abstract Thin-slice CT provides finer anatomical depiction, but in some clinical settings, only thick-slice CT images are available, resulting in reduced visible anatomical detail. Simply resampling to a smaller through-plane spacing cannot alleviate partial-volume-related image degradation, motivating deep learning-based CT slice synthesis (CSS) as an auxiliary strategy.
Improving Prostate MRI: Lessons Learned from the American College of Radiology’s Prostate MR Image Quality Improvement CollaborativeRadioGraphics
Published In RadioGraphics Volume 46 • Number 1 • Jan 1 2026 Abbreviations ACR American College of Radiology ADC apparent diffusion coefficient DCE dynamic contrast-enhanced DWI diffusion-weighted imaging FOV field of view PI-QUAL Prostate Imaging Quality System PI-RADS Prostate Imaging Reporting and Data System PSA prostate-specific antigen SNR signal-to-noise ratio History Received: Apr 24 2025 Revision requested: May 27 2025 Revision received: Jun 29 2025 Accepted: Jul 1 2025 Published...
Faster and Sharper Prostate T2W MRI with Deep Learning
Get full text access Log in, subscribe or purchase for full access. REFERENCES 1. Ahdoot, M. ∙ Wilbur, A.R. ∙ Reese, S.E. ... MRI-targeted, systematic, and combined biopsy for prostate cancer diagnosis N Engl J Med. 2020; 382:917-928 2. Kasivisvanathan, V. ∙ Rannikko, A.S. ∙ Borghi, M. ... MRI-targeted or standard biopsy for prostate-cancer diagnosis N Engl J Med. 2018; 378:1767-1777 3. Turkbey, B. ∙ Purysko, A.S. PI-RADS: where next? Radiology. 2023; 307, e223128 4. Brown, A.M. ∙ Elbuluk, O. ∙ Mertan, F. ...
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