APPARATUS FOR LEARNING BRAIN DISEASE MODEL APPARATUS FOR DETECTING BRAIN DISEASE USING THE BRAIN DISEASE MODEL METHOD FOR LEARNING BRAIN DISEASE MODEL AND METHOD FOR DETECTING BRAIN DISEASE USING THE BRAIN DISEASE MODEL

摘要

According to one aspect of the present disclosure, provided is an apparatus for learning a cerebrovascular disease. The apparatus for learning a cerebrovascular disease comprises: a maximum intensity projection (MIP) magnetic resonance angiography (MRA) configuration unit receiving input of three-dimensional time-of-flight magnetic resonance angiography (3D TOF MRA) and constituting MIP MRA including a plurality of image frames; a spatial characteristic learning unit constructing a spatial characteristic learning model based on a convolutional neural network (CNN) learning method, wherein the spatial characteristic learning model learns spatial characteristics of each of the plurality of image frames; a frame characteristic learning unit receiving input of the spatial characteristics and building a frame characteristic learning model based on a recurrent neural network (RNN) learning method, wherein the frame characteristic learning model learns frame characteristics indicating characteristics between the plurality of image frames; and a lesion characteristic learning unit receiving input of the frame characteristics and building a lesion characteristic learning model based on the CNN learning method, wherein the lesion characteristic learning model learns lesion characteristics with respect to each of the plurality of image frames. According to the present invention, it is possible to quickly and accurately learn an area required to diagnose a cerebrovascular disease or an area on which the cerebrovascular disease occurs.