Keywords: Prostate, AI/ML Software, Scan Planning
Motivation: Optimal protocol selection is key to achieve high-quality diagnostic images. Less-experienced technologist often have to repeat acquisition, leading to wasted scan-time.
Goal(s): Demonstrate an approach that can inform or alert technologist of risk of low-SNR in high-resolution image, before the high-resolution images are acquired; thus, reducing time wastage due to repeats.
Approach: Leverage patient-specific anatomical descriptors that are derived from localizer images to learn its relationship to quality of acquired images.
Results: We find statistically significant relationship between estimated SNR and body-contour distance. Based on our analysis, we recommend alerting technologist of low-SNR risk in prostate when body-contour distance >140mm.
Impact: The study demonstrates that image-quality of high-resolution image can be reliably predicted in-advance using descriptors derived from patient's localizer images. This will be useful for alerting technologist to make informed choice for protocol selection.
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