Spine Vision X-Ray Image based GUI Planning of Pedicle Screws Using Enhanced YOLOv5 for Vertebrae Segmentation
<|reference_start|>Spine Vision X-Ray Image based GUI Planning of Pedicle Screws Using Enhanced YOLOv5 for Vertebrae Segmentation: In this paper, we propose an innovative Graphical User Interface (GUI) aimed at improving preoperative planning and intra-operative guidance for precise spinal screw placement through vertebrae segmentation. The methodology encompasses both front-end and back-end computations. The front end comprises a GUI that allows surgeons to precisely adjust the placement of screws on X-Ray images, thereby improving the simulation of surgical screw insertion in the patient's spine. On the other hand, the back-end processing involves several steps, including acquiring spinal X-ray images, performing pre-processing techniques to reduce noise, and training a neural network model to achieve real-time segmentation of the vertebrae. The integration of vertebral segmentation in the GUI ensures precise screw placement, reducing complications like nerve injury and ultimately improving surgical outcomes. The Spine-Vision provides a comprehensive solution with innovative features like synchronous AP-LP planning, accurate screw positioning via vertebrae segmentation, effective screw visualization, and dynamic position adjustments. This X-ray image-based GUI workflow emerges as a valuable tool, enhancing precision and safety in spinal screw placement and planning procedures.<|reference_end|>
@article{rao2024spine,
    title={Spine Vision X-Ray Image based GUI Planning of Pedicle Screws Using
  Enhanced YOLOv5 for Vertebrae Segmentation},
    author={Yashwanth Rao, Gaurisankar S, Durga R, Aparna Purayath, Vivek Maik,
  Manojkumar Lakshmanan, and Mohanasankar Sivaprakasm},
    journal={arXiv preprint arXiv:2407.08349},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.08349},
    primaryClass={cs.CV}
}