RCMed: Towards Precise Medical Vision-Language Model with Reinforced Correlation Between Vision and Language
RCMed is a breakthrough medical vision-language framework that bridges the gap between AI and human clinical expertise. By integrating multimodal alignment in both input and output, RCMed enables precise anatomical delineation, accurate lesion localization, and reliable diagnosis through hierarchical vision-language grounding.
RCMed Can Recognize and Localize Targets
Text output: This is a pathology image with capillaries.
Recognition results: Capillaries
Localization results
Text output: This is a pathology image with nuclei.
Recognition results: Nuclei
Localization results
Text output: This is a pathology image with gland.
Recognition results: Gland
Localization results
RCMed Can Do Fine-grained Analysis across 9 Modalities
CT (Computed Tomography) Aorta
Segmentation of the aorta for cardiovascular analysis
CT (Computed Tomography) Pelvic
Pelvic structure segmentation for surgical planning
CT (Computed Tomography) Spine
Spine segmentation for orthopedic assessment
Dermoscopy Skin Lesion
Skin lesion analysis for dermatological diagnosis
Endoscopy Polyp
Polyp detection and segmentation in colonoscopy
Fundus Photography Lesion
Lesion detection and analysis
MR (Magnetic Resonance) Brain Tumor
Brain tumor segmentation for treatment planning
Pathology Arterioles
Arteriole analysis in pathological samples
Pathology Gland
Glandular structure segmentation in histology
PET (Positron Emission Tomography) Lesion
Lesion detection and analysis
Ultrasound Brachial Plexus
Brachial plexus nerve identification
Ultrasound Breast Cancer
Breast cancer detection and analysis
X-ray Pneumothorax
Pneumothorax detection in chest X-rays
