15. A computer program product for detecting and describing lesions automatically, the computer program product comprising a computer-readable storage medium having program code embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program code executable by a processor to cause the processor to: train a convolutional neural network (CNN) to detect features, and train fully connected layers of the CNN, to map detected features to semantic descriptors based on a data set comprising one or more lesions; receive a medical image to be analyzed for lesions; extract feature maps comprising detected features from medical image using the trained CNN; detect a region of interest via the trained CNN and generate a bounding box around the detected region of interest; reduce a dimension of the region of interest based on the feature maps; and generate a semantic description of the region of interest via the trained fully connected layers; and generate and display a diagnostic image comprising the medical image, the bounding box, and the semantic description.
15. A computer program product for detecting and describing lesions automatically, the computer program product comprising a computer-readable storage medium having program code embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program code executable by a processor to cause the processor to: train a convolutional neural network (CNN) to detect features, and train fully connected layers of the CNN, to map detected features to semantic descriptors based on a data set comprising one or more lesions; receive a medical image to be analyzed for lesions; extract feature maps comprising detected features from medical image using the trained CNN; detect a region of interest via the trained CNN and generate a bounding box around the detected region of interest; reduce a dimension of the region of interest based on the feature maps; and generate a semantic description of the region of interest via the trained fully connected layers; and generate and display a diagnostic image comprising the medical image, the bounding box, and the semantic description. 16. The computer program product of claim 15 , comprising program code executable by the processor to calculate a probability that the region of interest comprises a tumor.