Fast SMWI : Optimizing Classifier with FOV reduction simulation

Abstract

Motivation: SMWI is an advanced SWI method capable of detecting nigral hyperintensity in the substantia nigra. Due to the long scan time, a reduced FOV sequence was proposed to decrease the scan time from 4min 15sec to 2min 45sec, along with the application of denoising techniques. However, when evaluated with the original classifier, the results showed changes, reporting increased FN, which may be a problem in clinic. Goal(s): Maintaining diagnostic results for the reduced FOV with denoised SMWI images. Approach: Optimizing classifier to denoised FOV-simulated SMWI images. Results: The diagnostic result of denoised FOV 64.5% SMWI images is comparable to FOV 100% SMWI images. Impact: The diagnostic result of denoised FOV 64.5% SMWI images is comparable to FOV 100% SMWI images with the optimizing classifier based on denoised FOV-simulated SMWI images.