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Abstract #0744

An Explainable AI-based Motion Detection approach for MR images without requirement of motion annotated ground truth data

Subhashis Banerjee1, Dattesh Shanbhag1, and Sudhanya Chatterjee1
1GE HealthCare, Bengaluru, India

Synopsis

Keywords: Analysis/Processing, Artifacts, Motion, Motion Detection, MR value

Motivation: Motion is one of the leading causes of artifacts in MR images. Such images are often rendered non-diagnostic, and results in patient recall.

Goal(s): Objective is to detect motion in MRI scans and provide information on extent of motion so that MRI technologists can decide on whether to re-scan the subject.

Approach: The proposed AI-based method detects motion in MR images and provides a motion severity score, while not relying on real world annotated motion data.

Results: The proposed method was tested on a set of real-world MRI data with and without motion and provided an accuracy of 89.6%.

Impact: Reliable motion alert for MRI scans shall enable technologists to re-scan the subjects while in the scanning room. This will help in reducing the patient recalls due to motion artifact and hence reduce burden on the healthcare system.

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Keywords