Disclosed are a dynamic multidimensional disease diagnosis device and method based on medical image information deep learning. According to an embodiment of the present invention, the dynamic multidimensional disease diagnosis method based on medical image information deep learning can comprise the following steps of: extracting an automated image including a lesion from an endoscopy image; generating a plurality of training data for the automated image through pre-processing; creating n convolutional layers (n is a natural number of 2 or more) by filtering the plurality of training data; selectively using the n convolutional layers and integrating the same into m fully connected layers (m is a natural number of 2 or more); and configuring a sequential combination of the n convolutional layers and the m fully connected layers to output an optimal structure layer including classification information for the lesion in the automated image.
METHOD AND DEVICE FOR CONFIRMING DYNAMIC MULTIDIMENSIONAL LESION LOCATION BASED ON DEEP LEARNING IN MEDICAL IMAGE INFORMATION