Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training
paradigm, successfully introduces text supervision to vision models. It has shown promising …

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and
execute tasks with human cognitive abilities, engenders significant anticipation and intrigue …

Tumor synthesis enables the creation of artificial tumors in medical images facilitating the
training of AI models for tumor detection and segmentation. However success in tumor …

The Segment Anything Model (SAM) is a new image segmentation tool trained with the
largest available segmentation dataset. The model has demonstrated that, with prompts, it …

Image-based 2D/3D registration is a critical technique for fluoroscopic guided surgical
interventions. Conventional intensity-based 2D/3D registration approa-ches suffer from a …

Medical imaging is playing an important role in diagnosis and treatment of diseases.
Generative artificial intelligence (AI) have shown great potential in enhancing medical …

AI for cancer detection encounters the bottleneck of data scarcity, annotation difficulty, and
low prevalence of early tumors. Tumor synthesis seeks to create artificial tumors in medical …

Objective Given the importance AI in genomics and its potential impact on human health, the
American Medical Informatics Association—Genomics and Translational Biomedical …

Purpose: Interpreting chest radiographs (CXR) remains challenging due to the ambiguity of
overlapping structures such as the lungs, heart, and bones. To address this issue, we …

This study leverages synthetic data as a validation set to reduce overfitting and ease the
selection of the best model in AI development. While synthetic data have been used for …