An MRI lesion position detection method, comprising: inputting a training sample into a convolutional neural network and performing parameter training to obtain a detection model of a lesion position in MRI detection data (S1); inputting a sample under detection into the detection model and performing prediction, so as to predict a lesion position in the sample under detection (S2). The method is adopted to increase the accuracy of predicting a lesion position in MRI data. Further provided is an MRI lesion detection device, a computer apparatus, and a storage medium.
MRI LESION POSITION DETECTION METHOD, DEVICE, COMPUTER APPARATUS, AND STORAGE MEDIUM