Artificial intelligence (ai) based parkinson's disease diagnosing apparatus and method

Abstract

The present invention relates to an artificial intelligence-based Parkinson's disease diagnosing apparatus and method. An artificial intelligence-based Parkinson's disease diagnosing apparatus which is an aspect of the present disclosure includes an image acquiring unit which acquires a first image related to a multi-echo magnitude and phase from an MRI obtained by capturing a brain of a patient; an image processing unit which post-processes the acquired first image so as to observe a substantia nigra and a nigrosome-1 region used as imaging biomarkers of the Parkinson's disease; an image analyzing unit which analyzes the post-processed first image to classify a second image including the nigrosome-1 region and detects the nigrosome-1 region from the classified second image; and a diagnosing unit which diagnoses whether the patient has the Parkinson's disease by analyzing whether the detected nigrosome-1 region is normal, in which the image processing unit generates a susceptibility map weighted imaging image by applying a quantitative susceptibility map mask to the first image based on a quantitative susceptibility mapping algorithm to perform the post-processing and the image processing unit further performs at least one operation of angle adjustment, image enlargement, and reslice, on the generated susceptibility map weighted imaging image.