R01DE033512/NH/NIH HHS/United States[Grants and Funding] - Search Results

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Machine learning in image-based outcome prediction after radiotherapy: A review.

Yuan X, Ma C, Hu M, Qiu RLJ, Salari E, Martini R, Yang X. Yuan X, et al. J Appl Clin Med Phys. 2024 Nov 18:e14559. doi: 10.1002/acm2.14559. Online ahead of print. J Appl Clin Med Phys. 2024. PMID: 39556691 Review.

Prediction of early recurrence of adult-type diffuse gliomas following radiotherapy using multi-modal magnetic resonance images.

Salari E, Chen X, Wynne JF, Qiu RLJ, Roper J, Shu HK, Yang X. Salari E, et al. Med Phys. 2024 Nov;51(11):8638-8648. doi: 10.1002/mp.17382. Epub 2024 Sep 2. Med Phys. 2024. PMID: 39221589

Using a patient-specific diffusion model to generate CBCT-based synthetic CTs for CBCT-guided adaptive radiotherapy.

Chen X, Qiu RLJ, Wang T, Chang CW, Chen X, Shelton JW, Kesarwala AH, Yang X. Chen X, et al. Med Phys. 2024 Oct 14. doi: 10.1002/mp.17463. Online ahead of print. Med Phys. 2024. PMID: 39401286

Deep learning based apparent diffusion coefficient map generation from multi-parametric MR images for patients with diffuse gliomas.

Eidex Z, Safari M, Wynne J, Qiu RLJ, Wang T, Hernandez DV, Shu HK, Mao H, Yang X. Eidex Z, et al. Med Phys. 2024 Nov 8. doi: 10.1002/mp.17509. Online ahead of print. Med Phys. 2024. PMID: 39514841

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