Deep learning has shown encouraging performance for lesion detection, but it is limited due to the high requirement of data labeling. In the task of lumbar intervertebral disc herniation recognition, we proposed to develop a recognition method based on axial images, which include more anatomical information about the disc, using a convolutional network. And we attempt to provide possible pathological evidence from the weakly labeled training data (normal/herniated label on image level).
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