Spine Region Computer Vision Project
Updated 2 years ago
690
37
Metrics
Here are a few use cases for this project:
-
Medical Diagnosis Assistance: The 'Spine Region' model could be used by healthcare professionals to assist in diagnosing spinal disorders or conditions like scoliosis, spinal disc herniation, or osteoporosis by automatically identifying and highlighting any abnormalities present in the spine region of x-ray images.
-
Posture Check Applications: A posture check application can integrate the 'Spine Region' model to assess a person's posture and provide personalized recommendations to improve it, which could be beneficial in preventing or managing chronic back pain.
-
Physiotherapy and Rehabilitation: Physiotherapists can use this model to track patient progress by comparing changes in the spinal region over time in patients undergoing rehabilitation for spinal injuries or conditions.
-
Biomechanics Research: Researchers studying human locomotion and biomechanics could use this model to analyze different spine conditions, and how they affect a person's movement and balance.
-
Personal Training & Sport Coaching: Personal trainers or coaches could use the AI model to help athletes gain insight into their spinal alignment and understand how it impacts their performance, as well as make alterations in training regimens to minimize the risk of injury.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
spine-region_dataset,
title = { Spine Region Dataset },
type = { Open Source Dataset },
author = { CADMA },
howpublished = { \url{ https://universe.roboflow.com/cadma/spine-region } },
url = { https://universe.roboflow.com/cadma/spine-region },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { nov },
note = { visited on 2024-11-21 },
}