About
ScolioVis is an automatic cobb angle measurement tool developed by B.S. in Computer Science students at West Visayas State University for their Undergraduate Thesis.
The finished product is this web application implementing a Keypoint RCNN model that performs multi-instance vertebra keypoint detection on spine images in order to extract the Cobb Angles automatically. The research is set to be published in early 2023.
Authors of ScolioVis
Carlo Antonio T. Taleon
Glecy S. Elizalde
Christopher Joseph T. Rubinos
Special Thanks to
👨🏫 Dr. Frank I. Elijorde - Our ever-supportive Thesis Adviser.
🤵 Dr. Bobby D. Gerardo - Our ever-supportive Thesis Co-Adviser.
👨🔬 Dr. Shuo Li - for giving us access to the SpineWeb Dataset 16
👩💼 Dr. Julie Ann Salido - for her expertise in computer vision research.
👨💼 Mr. Paolo Hilado - for his expertise in data science research.
👩⚕️ Dra. Jocelyn F. Villanueva - for her expertise in radiology.
👨⚕️ Dr. Christopher Barrera - for his expertise in radiology.
Important References
Wu, H., Bailey, Chris., Rasoulinejad, Parham., and Li, S., 2017. Automatic landmark estimation for adolescent idiopathic scoliosis assessment using boostnet. Medical Image Computing and Computer Assisted Intervention:127-135.
Interested in Collaborating?
Want to help us improve ScolioVis and make this a
medical-grade app? Contact us at: