Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
365-03-013 ISMRM Abstract

AI-THiNR: A Modular AI Toolbox for Quantitative Multicontrast MRI of Head and Neck Tumors

Primary: Analysis Methods - Classification and Prediction
Secondary: Diffusion - Diffusion Software
365-03-013 · Body Diffusion MRI Methods · Monday, 11 May, 1:50 PM–2:45 PM · Digital Posters Row F
Keywords: Diffusion MRI Deep learning Physics-guided deep learning Quantitaitive diffusion imaging Head and Neck
Accepted
Muhammad Awais1, Ramesh Paudyal 1, Akash D Shah2, Vaios Hatzoglou2, Nora Katabi3, Eve LoCastro1, Richard J Wong4, Ashok Shaha4, R. M. Tuttle5, Nadeem Riaz6, Nancy Lee6, Lawrence H Schwartz2, Amita Shukla-Dave1,2
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, United States of America
2Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, United States of America
3Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, United States of America
4Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, United States of America
5Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, United States of America
6Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, United States of America
Presenting Author: Ramesh Paudyal

Synopsis

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References

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9. 9. LoCastro, E., et al., A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology. Tomography, 2023. 9(6): p. 2052-2066.
10. 10. Lu, Y., et al., Extension of the intravoxel incoherent motion model to non-gaussian diffusion in head and neck cancer. J Magn Reson Imaging, 2012. 36(5): p. 1088-96.
11. 11. Debus, C., et al., MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging - design, implementation and application on the example of DCE-MRI. BMC Bioinformatics, 2019. 20(1): p. 31.
12. 12. McGarry, S.D., et al., Multi-Site Concordance of Diffusion-Weighted Imaging Quantification for Assessing Prostate Cancer Aggressiveness. J Magn Reson Imaging, 2022. 55(6): p. 1745-1758.
13. 13. Norton, I., et al., SlicerDMRI: open source diffusion MRI software for brain cancer research. Cancer research, 2017. 77(21): p. e101-e103.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/365-03-013