Cervical Spine Fracture Detection Using Pytorch

Cervical spine fractures are one of the severe varieties and most typical spinal cord injury. The cervical spine is fragile and well-assembled structure of stacked bones, ligaments, nerves and muscles. It consists of seven stacked vertebrae labelled as C1 to C7 settling exactly below the skull. The injury to any of the vertebrae can result in tetraplegia or quadriplegia which means the absent feeling or movement below the neck. Trauma is the prevalent cause of injury as a result of motor vehicle accidents, falls, sports related such as diving injuries. Non traumatic causes composed of arthritis, cancer, osteoporosis comprehending compression fractures and inflammations of spinal cord. Computer Tomography (CT) has been emerging as best quality of care imaging diagnosis approach especially evaluating the c-spine. Deep convolution neural network is built to extricate the radiological factors from each slice of the CT scan. The features that are extracted down the CT scans are processed and the fractures are identified with the generated probabilities from the prediction. The model was trained and evaluated with 2019 CT scans each consists of more than 200 2D image slices. The outcome of the model suit with the observations and performance of radiologist on the test set in the physical world process of diagnosis.