Abstract #2016

Application of Deep Leaning Model for Quality Control of Short-echo 7T MRSI with Various Disease Types

Huawei Liu¹, Emily Xie¹, Helene Ratiney², Michael Sdika², and Yan Li¹

¹Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Univ. Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, Lyon, France

In this project, we adapted the model with various inputs combinations, such as using different tiles, including tissue information and magnitude spectra as additional channels. These variant models were trained and tested in a comprehensive cohort of in-vivo 7T MRSI datasets of various patient types. In our test, an AUC of 0.966 was consistently achieved for the multiple type datasets.

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