Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges
This paper presents a comprehensive systematic review of generative models (GANs, VAEs,
DMs, and LLMs) used to synthesize various medical data types, including imaging …
DMs, and LLMs) used to synthesize various medical data types, including imaging …
Transfer learning for improved electrocardiogram diagnosis of cardiac disease: exploring the potential of pre-trained models
Predicting the onset of cardiovascular disease (CVD) has been a hot topic for researchers
for years, and recently, the concept of transfer learning has been gaining traction in this field …
for years, and recently, the concept of transfer learning has been gaining traction in this field …
AI in MRI: Computational frameworks for a faster, optimized, and automated imaging workflow
Over the last decade, artificial intelligence (AI) has made an enormous impact on a wide
range of fields, including science, engineering, informatics, finance, and transportation. In …
range of fields, including science, engineering, informatics, finance, and transportation. In …
A review of self‐supervised, generative, and few‐shot deep learning methods for data‐limited magnetic resonance imaging segmentation
Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with
applications in disease diagnostics, intervention, and treatment planning. Accurate MRI …
applications in disease diagnostics, intervention, and treatment planning. Accurate MRI …
Toward Lightweight Diabetic Retinopathy Classification: A Knowledge Distillation Approach for Resource-Constrained Settings
Diabetic retinopathy (DR), a consequence of diabetes, is one of the prominent contributors
to blindness. Effective intervention necessitates accurate classification of DR; this is a need …
to blindness. Effective intervention necessitates accurate classification of DR; this is a need …
Artificial Intelligence in Image-based Cardiovascular Disease Analysis: A Comprehensive Survey and Future Outlook
Recent advancements in Artificial Intelligence (AI) have significantly influenced the field of
Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our paper …
Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our paper …
The Role of Artificial Intelligence in Cardiac Imaging
C Onnis, M van Assen, E Muscogiuri… - Radiologic …, 2024 - radiologic.theclinics.com
Cardiovascular disease (CVD) remains the number one cause of death worldwide, and the
number of annual deaths is expected to increase in the near future 1; thus it is not surprising …
number of annual deaths is expected to increase in the near future 1; thus it is not surprising …
An Improved Approach for Cardiac MRI Segmentation based on 3D UNet Combined with Papillary Muscle Exclusion
Left ventricular ejection fraction (LVEF) is the most important clinical parameter of
cardiovascular function. The accuracy in estimating this parameter is highly dependent upon …
cardiovascular function. The accuracy in estimating this parameter is highly dependent upon …