Automated Cobb Angle Measurement on Anterior-Posterior Spine X-Rays using Multi-Instance Keypoint Detection with Keypoint RCNN
This repository serves as the compiled package of our undergraduate research for West Visayas State University - College of Information and Communications Technology entitled: "ScolioVis: Automated Cobb Angle Measurement on Anterior-Posterior Spine X-Rays using Multi-Instance Keypoint Detection with Keypoint RCNN"
In this repo, you can:
ScolioVis is a tool for automatically measuring the Cobb Angleβthe standard measurement to assess Scoliosis. We harness the power of computer vision and machine learning to extract the cobb angles of an anterior-posterior Spine x-ray image. We built this application from the ground-up to an actual implementation in a usable web app.
We trained a Keypoint RCNN model on the SpineWeb Dataset 16. Boasting a performance of 93% AP at IoU=0.50 on object detections and 57% AP at IoU=0.50 on keypoint detections. The dataset is also part of the Accurate Automated Spinal Curvature Estimation (AASCE) 2019 Grand Challenge. Atlhough we aren't competing, using the performance metric of the challenge, we have achieved an SMAPE of 8.97 in cobb angle calculation which means ScolioVis as a whole is able to predict cobb angles at 91.03% accuracy.
A live deployed version of the application is available at scoliovis.app.
π Go to /src for detailed instructions on how to setup this project on your machine.
Source Repositories:
π¨
scoliovis-web - Front End Repoβ‘
scoliovis-api - Back End RepoποΈββοΈ
scoliovis-training - Model Training RepositoryAny Paper that uses the SpineWeb Dataset 16, must cite the following:
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. Retrieved from http://www.digitalimaginggroup.ca/members/Shuo/MICCAIAutomatic.pdf
Our π Thesis Manuscript
and π User Manual
are available on /doc.
Name | Contributions |
---|---|
π¨βπ« Dr. Frank I. Elijorde | Our ever-supportive Thesis Adviser. |
π€΅ Dr. Bobby D. Gerardo | Our ever-supportive Thesis Co-Adviser. |
π¨βπ¬ Dr. Shuo Li | For giving us access to the SpineWeb Dataset 16. |
π©βπΌ Dr. Julie Ann Salido | For her expertise in computer vision research. |
π¨βπΌ Mr. Paolo Hilado | For his expertise in data science research. |
π©ββοΈ Dra. Jocelyn F. Villanueva | For her expertise in radiology. |
π¨ββοΈ Dr. Christopher Barrera | For his expertise in radiology. |
Convert the following bibtex
to
APA | MLA
(Credits to bibtex.online)
@article{article,
type={Bachelor's Thesis},
author = {Taleon, Carlo Antonio and Elizalde, Glecy and Rubinos, Christopher Joseph},
title = {ScolioVis: Automated Cobb Angle Measurement on Anterior-Posterior Spine X-Rays using Multi-Instance Keypoint Detection with Keypoint RCNN},
journal = {West Visayas State University College of Information and Communications Technology},
address = {La Paz, Iloilo City, Iloilo, Philippines},
year = {2023}
}
2023 Β© Taleon, Elizalde, Rubinos (BSCS4A) - West Visayas State University - College of Information and Communications Technology. All Rights Reserved.