bb(frac) Computer Vision Project

bonefrac

Updated a year ago

142

views

8

downloads
Description

Here are a few use cases for this project:

  1. Medical Diagnostics: The "FractureBones" model can be used in healthcare centers and hospitals for diagnostic purposes, to automatically detect fractures from X-ray images, improving efficiency and accuracy in diagnosis.

  2. Remote Healthcare: In remote areas where professional medical help is not readily available, the model can assist healthcare workers, nurses, and general practitioners to identify fractures, thus enabling timely treatment.

  3. Training Medical Students: The model can be used in medical schools as a teaching aid for students learning about orthopedics, allowing them to understand various fracture classes more deeply.

  4. Sports Medicine: Sports professionals can use it to detect any fractures in an athlete's bones. This could expedite treatment and potentially decrease recovery time.

  5. Postoperative Assessment: Surgeons can use the "FractureBones" model as part of postoperative analysis, to assess whether or not a fracture has completely healed after treatment or surgery.

Supervision

Build Computer Vision Applications Faster with Supervision

Visualize and process your model results with our reusable computer vision tools.

Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            bb-frac_dataset,
                            title = { bb(frac) Dataset },
                            type = { Open Source Dataset },
                            author = { bonefrac },
                            howpublished = { \url{ https://universe.roboflow.com/bonefrac/bb-frac } },
                            url = { https://universe.roboflow.com/bonefrac/bb-frac },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-11-21 },
                            }