Swallowing dynamic MRI 2023 Object Detection Dataset and Pre-Trained Model by SwallE2023ClaireYo

Images

359 images

Explore Dataset

Here are a few use cases for this project:

Medical Diagnostics: The "Hyoid epiglottis pharynx 2023" can be used for analyzing medical images, such as X-rays or MRIs, to identify abnormalities or potential issues related to the hyoid bone, epiglottis, and pharynx. This could help doctors in diagnosing underlying conditions and improving patient care.
Surgical Planning and Assistance: Surgeons can utilize this computer vision model to plan and simulate complex surgeries involving the hyoid bone, epiglottis, and pharyngeal areas. Furthermore, it could potentially be integrated with robotic surgical systems, allowing for precise and efficient surgical procedures.
Dysphagia Assessment: This model could be employed to analyze swallow studies or videofluoroscopic swallow study (VFSS) images, helping speech-language pathologists and other healthcare professionals identify swallowing difficulties and determine the most appropriate treatment for patients experiencing dysphagia.
Sleep Apnea Analysis: The "Hyoid epiglottis pharynx 2023" model can analyze images of patients’ airways to identify possible anatomical issues related to sleep apnea, such as obstructions or narrow airways. This could aid in the early diagnosis of sleep apnea and contribute to the development of effective treatment plans.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            swallowing-dynamic-mri-2023_dataset,
                            title = { Swallowing dynamic MRI 2023 Dataset },
                            type = { Open Source Dataset },
                            author = { SwallE2023ClaireYo },
                            howpublished = { \url{ https://universe.roboflow.com/swalle2023claireyo/swallowing-dynamic-mri-2023 } },
                            url = { https://universe.roboflow.com/swalle2023claireyo/swallowing-dynamic-mri-2023 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { feb },
                            note = { visited on 2024-05-04 },
                            }