Self-Supervised Learning Powered by Synthetic Data From Diffusion Models: Application to X-Ray Images
<p dir="ltr">Synthetic data offers a compelling solution to the challenges associated with acquiring high-quality medical data, which is often constrained by privacy concerns and limited accessibility. This study explores the efficacy of synthetic data generated using diffusion model...
محفوظ في:
| المؤلف الرئيسي: | Abdullah Hosseini (22466602) (author) |
|---|---|
| مؤلفون آخرون: | Ahmed Serag (2945643) (author) |
| منشور في: |
2025
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Dynamic model scaling based on segmented tumor size for breast cancer detection
حسب: Younes Akbari (16303286)
منشور في: (2025) -
Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review
حسب: Hazrat Ali (421019)
منشور في: (2022) -
Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
حسب: Tawsifur Rahman (14150523)
منشور في: (2020) -
A Diffusion-Based Probabilistic Ultra-Short-Term Solar Power Prediction Using the Sky Image Sequences
حسب: Razieh Rastgoo (22457767)
منشور في: (2025) -
FetSAM: Advanced Segmentation Techniques for Fetal Head Biometrics in Ultrasound Imagery
حسب: Mahmood Alzubaidi (15740693)
منشور في: (2024)