fundusv3 Object Detection Dataset and Pre-Trained Model by prsworkspace

Images

482 images

Explore Dataset

Here are a few use cases for this project:

Medical Diagnosis Software: This computer vision model can be incorporated in medical diagnostic software to assist ophthalmologists in diagnosing various eye conditions such as glaucoma, macular degeneration, and diabetic retinopathy by identifying abnormalities in fundus images, such as microaneurysm and bleeding.
Research in Ophthalmology: Researchers can use this model for analysis in clinical studies related to eye diseases, improving their understanding of the pathogenesis and progression of these conditions.
Telemedicine: Fundusv3 can be used in telemedicine platforms where doctors could remotely diagnose eye conditions by analyzing the images using the model. This would be particularly helpful where access to ophthalmologists is limited.
Training Medical Students: The model can be used in educational settings to help medical students learn about various optic-image classes and related diseases.
Automated Screening Triage: Hospitals and clinics can use this model as a preliminary screening tool to prioritize patients based on the severity of potential eye conditions detected in the images, thereby optimizing the use of healthcare resources.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            fundusv3_dataset,
                            title = { fundusv3 Dataset },
                            type = { Open Source Dataset },
                            author = { prsworkspace },
                            howpublished = { \url{ https://universe.roboflow.com/prsworkspace/fundusv3 } },
                            url = { https://universe.roboflow.com/prsworkspace/fundusv3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-29 },
                            }