Latest Research in Multimodal Foundation Models

Top Research Topics in Multimodal Foundation Models

• Computer Vision and Pattern Recognition — 18 papers
• COVID-19 diagnosis using AI — 6 papers
• Medical Imaging Techniques and Applications — 5 papers
• Image and Video Processing — 4 papers
• Advanced Neural Network Applications — 2 papers
• Colorectal Cancer Screening and Detection — 2 papers
• Advanced Radiotherapy Techniques — 2 papers
• AI in cancer detection — 2 papers
• Lung Cancer Diagnosis and Treatment — 1 papers
• Artificial Intelligence in Healthcare and Education — 1 papers

Highest-Cited Papers

1. Benchmarking foundation models for tumor segmentation across multiple cancer types
2. NAHFormer: Neighborhood self-attention and hierarchical feature fusion transformer for image medical segmentation
3. FreqDINO++: A Frequency-Guided Multi-Task Routing Vision Foundation Model for Universal Ultrasound Analysis
4. Robustness of deep learning-based denoising 4DCBCT methods
5. Automatic segmentation of malignant pulmonary nodules on LUNA16 subsets using an attention-guided 3D U-Net framework
6. LOCUS-Diff: Location-Controlled Thyroid Ultrasound Synthesis for Advancing Nodule Detection
7. Synthetic Mammography Image Generation Using DCGANs: Toward Self-Training of Artificial Intelligence Models
8. The Gate Does Not Choose: An Expert-Initialised Mixture-of-Experts Outperforms Training-Free Consensus under the Official BraTS-2023 Metrics
9. Beyond Performance Metrics: Uncertainty Mapping of Label Ambiguity in Fazekas Score Prediction
10. Scaling vision models does not consistently improve localisation-based explanation quality
11. From visual saliency to anatomical explanation: generating textual diagnostic reports from brain MRIs with saliency-grounded LLMs
12. VLSI-Accelerated Chest X-Ray Image Segmentation using Adaptive Hybrid Clustering: MATLAB–FPGA Co-Design and Performance Evaluation
13. TRACE: Two-Stage Detector-Response Estimation With Angular Cosine Expansion for Ring Artifact Correction in Photon-Counting CT
14. TotalSynth: Robust Whole-Body Synthetic CT from MRI and CBCT
15. Parameter-Efficient Fine-Tuning of Foundation Models for Liver Tumor Segmentation in CT
16. Beyond Accuracy: Uncertainty-Guided Boundary Refinement for Reliable Biomedical Image Segmentation
17. Unified CT and MRI Pancreas Segmentation for Label-Efficient Cross-Modality Subregion Transfer
18. ASAM2-UNet: An Attention-Enhanced SAM2 U-Net for Polyp Segmentation
19. Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection (3 citations)
20. DINO-Med: A Unified Patch-Based Adaptation Framework for Multi-Modal Medical Image Analysis Applied to Liver Fibrosis Staging

Sub-Regions

• Computer Vision and Pattern Recognition — 18 papers
• COVID-19 diagnosis using AI — 11 papers
• Machine Learning — 11 papers
• Lung Cancer Diagnosis and Treatment — 8 papers
• Advanced Neural Network Applications — 7 papers
• Glioma Diagnosis and Treatment — 6 papers