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https://github.com/blankeos/scoliovis
🦴 Automated Cobb Angle Measurement on Anterior-Posterior Spine X-Rays using Multi-Instance Keypoint Detection with Keypoint RCNN Thesis Package
https://github.com/blankeos/scoliovis
computer-vision fastapi machine-learning pytorch react webapp
Last synced: 4 days ago
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🦴 Automated Cobb Angle Measurement on Anterior-Posterior Spine X-Rays using Multi-Instance Keypoint Detection with Keypoint RCNN Thesis Package
- Host: GitHub
- URL: https://github.com/blankeos/scoliovis
- Owner: Blankeos
- Created: 2022-11-17T04:13:00.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-10T16:47:21.000Z (about 1 year ago)
- Last Synced: 2024-05-15T15:31:42.916Z (6 months ago)
- Topics: computer-vision, fastapi, machine-learning, pytorch, react, webapp
- Language: TypeScript
- Homepage: https://scoliovis.app
- Size: 42.9 MB
- Stars: 6
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
✨ ScolioVis ✨
Automated Cobb Angle Measurement on Anterior-Posterior Spine X-Rays using Multi-Instance Keypoint Detection with Keypoint RCNN
## 📖 Summary
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:
- [x] Read our research manuscript.
- [x] Understand our project.
- [x] Try our live, deployed demo on [scoliovis.app](https://scoliovis.app/)
- [x] Try running our project locally.
- [x] Recreate our research/project.
## 📑 Contents
- [:book: About](#book-about)
- [:toolbox: Setup Instructions](#toolbox-setup-instructions)
- [:ledger: Colab Notebooks](#ledger-colab-notebooks)
- [:brain: Models](#brain-models)
- [:scroll: Important References](#scroll-important-references)
- [:trophy: Acknowledgements](#trophy-acknowledgements)
- [:writing_hand: Cite our Project](#writing_hand-cite-our-project)
## :book: About
**ScolioVis** is a tool for automatically measuring the Cobb Angle—the 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](http://spineweb.digitalimaginggroup.ca/Index.php?n=Main.Datasets#Dataset_16.3A_609_spinal_anterior-posterior_x-ray_images). 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](https://aasce19.grand-challenge.org/Task/). 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](https://scoliovis.app/).
## :toolbox: Setup Instructions
👉 Go to [/src](/src) for detailed instructions on how to setup this project on your machine.
Source Repositories:
1. `🎨` [scoliovis-web](https://github.com/Blankeos/scoliovis-web) - Front End Repo
2. `⚡` [scoliovis-api](https://github.com/Blankeos/scoliovis-api) - Back End Repo
3. `🏋️♂️` [scoliovis-training](https://github.com/Blankeos/scoliovis-training) - Model Training Repository
## :ledger: Colab Notebooks
1. [Dataset Preprocessing for Keypoint RCNN](https://colab.research.google.com/drive/1Rlt43PWo6NYREuDsGT8K5tRg5QqfFdVc?usp=sharing)
1. [Keypoint RCNN Training](https://colab.research.google.com/drive/1aaTWt2rZ-M7YlqIus7aC-84SorjNwl8G?usp=sharing)
1. [Cobb Angle Calculation](https://colab.research.google.com/drive/1Cm32oftsMpsqMH5kLHgr0RtsfLAfiJnF?usp=sharing)
## :brain: Models
- [scoliovis-training/releases/keypointsrcnn-weights.pt](https://github.com/Blankeos/scoliovis-training/releases/download/latest/keypointsrcnn_weights.pt)
## :scroll: Important References
- Any 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 `📄 Thesis Manuscript` and `📘 User Manual` are available on [/doc](/doc).
## :trophy: Acknowledgements
| Name | Contributions |
| ------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| [👨🏫 Dr. Frank I. Elijorde](https://scholar.google.com.ph/citations?user=MbegV1wAAAAJ&hl=en) | Our ever-supportive Thesis Adviser. |
| [🤵 Dr. Bobby D. Gerardo](https://scholar.google.com.ph/citations?user=JNlh9WMAAAAJ&hl=en) | Our ever-supportive Thesis Co-Adviser. |
| [👨🔬 Dr. Shuo Li](http://www.digitalimaginggroup.ca/members/Shuo/MICCAIAutomatic.pdf) | For giving us access to the [SpineWeb Dataset 16](http://spineweb.digitalimaginggroup.ca/Index.php?n=Main.Datasets#Dataset_16.3A_609_spinal_anterior-posterior_x-ray_images). |
| [👩💼 Dr. Julie Ann Salido](https://scholar.google.com/citations?user=xeoUxA0AAAAJ&hl=en) | For her expertise in computer vision research. |
| [👨💼 Mr. Paolo Hilado](https://www.researchgate.net/profile/Paolo-Hilado-2) | For his expertise in data science research. |
| 👩⚕️ Dra. Jocelyn F. Villanueva | For her expertise in radiology. |
| 👨⚕️ Dr. Christopher Barrera | For his expertise in radiology. |
## :writing_hand: Cite Our Project
Convert the following `bibtex` to
APA | MLA
(Credits to bibtex.online)
```bibtex
@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 © Taleon, Elizalde, Rubinos (BSCS4A) - West Visayas State University - College of Information and Communications Technology. All Rights Reserved.