607-02-010 ISMRM Abstract

Towards Universal AIF Detection: Neural Network Trained on Synthetic DCE-MRI Data

Primary: Analysis Methods - Segmentation and Detection

Secondary: Contrast Mechanisms - Perfusion

607-02-010 · Quantitative and Multi-Contrast MRI: Methods and Applications · Thursday, 14 May, 1:40 PM–3:30 PM · Meeting Room 1.40

Keywords: Machine learning DCE-MRI Synthetic data Deep Learning Segmentation

Accepted

Samuel Barnes ¹, Lucas Saca¹

¹Department of Radiology, Loma Linda University, Loma Linda, United States of America

Presenting Author: Samuel Barnes

Synopsis

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References

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2. Gopinath K, et al. Synthetic data in generalizable, learning-based neuroimaging. Imaging Neurosci. 2024;3:1-18. doi:10.1162/imag_a_00337 [doi]

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6. Jansen, Sunny, & Van Dyke, Terry. (2015). TCIA Mouse-Astrocytoma Collection (Mouse-Astrocytoma) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9TCIA.2017.SGW7CAQW [doi]

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Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/607-02-010