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Multimodalxray

Developed by eduardofarina
This model is trained on frontal view samples from the CheXpert dataset, combining ViT and GPT2 architectures for generating draft radiology reports.
Image-to-Text
Transformers
Open Source License:Apache-2.0#Medical Imaging Report Generation#ViT-GPT2 Hybrid Architecture#Chest X-ray Analysis
Downloads 14
Release Time : 6/3/2023

Model Overview

This model integrates Vision Transformer (ViT) and GPT2 architectures, specifically designed to generate draft radiology reports from frontal view chest X-rays.

Model Features

Multimodal Architecture
Combines Vision Transformer (ViT) for image processing and GPT2 for text generation, enabling image-to-text conversion.
Specialized Domain Application
Specifically designed for the radiology field, capable of generating professional medical report drafts.
Efficient Training
Trained exclusively on frontal view samples, optimizing model efficiency.

Model Capabilities

Medical Image Analysis
Radiology Report Generation
Image-to-Text Conversion

Use Cases

Medical Assistance
Radiology Report Assistance
Assists radiologists in quickly generating preliminary diagnostic reports.
Improves report writing efficiency and reduces physician workload.
Medical Education
Used for medical student training to demonstrate report writing for typical cases.
Helps medical students learn standardized radiology report formats.
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