Vision-Language Medical Models
CLIP-based Architecture for Medical Imaging and Report Generation
Overview
This project develops custom CLIP-based architectures specifically designed for medical imaging applications, enabling zero-shot classification and automated report generation.
By adapting vision-language models to the medical domain, the system can understand and describe medical images in natural language, assist radiologists in report writing, and provide preliminary diagnoses without task-specific fine-tuning.
Key Features
Zero-Shot Classification
Classify medical conditions without explicit training on specific diseases.
Report Generation
Automatically generate preliminary radiology reports from medical images.
Multimodal Understanding
Joint understanding of medical images and clinical text.
Clinical Integration
Designed for integration into clinical workflows.
Technologies Used
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