M3D CLIP
M3D-CLIP is a CLIP model specifically designed for 3D medical imaging, achieving visual and language alignment through contrastive loss.
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Release Time : 4/25/2024
Model Overview
M3D-CLIP is a vision-language model based on the 3D ViT architecture, specifically designed for cross-modal retrieval and aligned feature extraction between 3D medical images and text.
Model Features
Specialized for 3D Medical Imaging
Designed specifically for 3D medical imaging, using a 3D ViT architecture to process 3D images of size 32*256*256.
Cross-modal Alignment
Achieves semantic alignment between 3D medical images and text through contrastive loss.
Strong Representation Features
Provides aligned strong representation features for downstream tasks.
Pre-training Advantage
The text-aligned visual encoder can serve as a high-quality pre-trained model for vision/multimodal tasks.
Model Capabilities
3D medical image feature extraction
Cross-modal retrieval for medical text and images
Semantic understanding of medical images
Multimodal representation learning
Use Cases
Medical Image Analysis
Medical Image Retrieval
Retrieve relevant 3D medical images based on text descriptions.
Efficient and accurate cross-modal retrieval capability.
Medical Report Generation
Generate descriptive text for 3D medical images.
Medical Image Classification
Perform image classification using aligned features.
Medical Research
Medical Knowledge Mining
Discover associative knowledge from large-scale medical image and text data.
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