Convolutional neural network-based automated segmentation and labeling of the lumbar spine X-ray

Conclusion: The results of the instance segmentation models on lumbar spine X-ray perform superior to semantic segmentation models in the recognition rates even by images of severe diseased spines by allowing the segmentation of overlapping vertebrae, in contrary to the semantic models where such differentiation cannot be performed due to the fused binary mask of the overlapping instances. These models can be incorporated into further clinical decision support pipelines.
Source: Journal of Craniovertebral Junction and Spine - Category: Orthopaedics Authors: Source Type: research