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20232026
most citedRadiology-Llama2: Best-in-Class Large Language Model for Radiology

30 citations · 125 across the 41 of their papers we have counts for

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16 papers · 1 filter

cs.CV2026

Thinking with Gaze: Sequential Eye-Tracking as Visual Reasoning Supervision for Medical VLMs

Yiwei Li, Yifan Zhou, Huaqin Zhao +6

Vision--language models (VLMs) process images as visual tokens, yet their intermediate reasoning is often carried out in text, which can be suboptimal for visually grounded radiolo…

cs.CV2025★ 3 cited

The SAGES Critical View of Safety Challenge: A Global Benchmark for AI-Assisted Surgical Quality Assessment

Deepak Alapatt, Jennifer Eckhoff, Zhiliang Lyu +38

Advances in artificial intelligence (AI) for surgical quality assessment promise to democratize access to expertise, with applications in training, guidance, and accreditation. Thi…

cs.CV2025

SAMed-2: Selective Memory Enhanced Medical Segment Anything Model

Zhiling Yan, Sifan Song, Dingjie Song +11

Recent "segment anything" efforts show promise by learning from large-scale data, but adapting such models directly to medical images remains challenging due to the complexity of m…

cs.CV2025★ 2 cited

Towards a general-purpose foundation model for fMRI analysis

Cheng Wang, Yu Jiang, Zhihao Peng +18

Functional MRI (fMRI) is crucial for studying brain function and diagnosing neurological disorders. However, existing analysis methods suffer from reproducibility and transferabili…

cs.CV2025

OWT: A Foundational Organ-Wise Tokenization Framework for Medical Imaging

Sifan Song, Siyeop Yoon, Pengfei Jin +10

Recent advances in representation learning often rely on holistic embeddings that entangle multiple semantic components, limiting interpretability and generalization. These issues…

cs.CV2025

MAST-Pro: Dynamic Mixture-of-Experts for Adaptive Segmentation of Pan-Tumors with Knowledge-Driven Prompts

Runqi Meng, Sifan Song, Pengfei Jin +9

Accurate tumor segmentation is crucial for cancer diagnosis and treatment. While foundation models have advanced general-purpose segmentation, existing methods still struggle with:…

cs.CV2025

Developing a PET/CT Foundation Model for Cross-Modal Anatomical and Functional Imaging

Yujin Oh, Robert Seifert, Yihan Cao +15

In oncology, Positron Emission Tomography-Computed Tomography (PET/CT) is widely used in cancer diagnosis, staging, and treatment monitoring, as it combines anatomical details from…

cs.CV2025★ 1 cited

Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data

Yucheng Shi, Quanzheng Li, Jin Sun +2

Large Multimodal Models (LMMs), or Vision-Language Models (VLMs), have shown impressive capabilities in a wide range of visual tasks. However, they often struggle with fine-grained…

cs.CV2024

EchoFM: Foundation Model for Generalizable Echocardiogram Analysis

Sekeun Kim, Pengfei Jin, Sifan Song +6

Foundation models have recently gained significant attention because of their generalizability and adaptability across multiple tasks and data distributions. Although medical found…

cs.CV2024

High-Fidelity 3D Lung CT Synthesis in ARDS Swine Models Using Score-Based 3D Residual Diffusion Models

Siyeop Yoon, Yujin Oh, Xiang Li +3

Acute respiratory distress syndrome (ARDS) is a severe condition characterized by lung inflammation and respiratory failure, with a high mortality rate of approximately 40%. Tradit…

cs.CV2024★ 4 cited

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos

Zhiling Yan, Weixiang Sun, Rong Zhou +8

Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in…

cs.CV2024★ 3 cited

Bora: Biomedical Generalist Video Generation Model

Weixiang Sun, Xiaocao You, Ruizhe Zheng +5

Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for medical AI development. Diffusion models can now generate re…

cs.CV2024

Biomedical Visual Instruction Tuning with Clinician Preference Alignment

Hejie Cui, Lingjun Mao, Xin Liang +5

Recent advancements in multimodal foundation models have showcased impressive capabilities in understanding and reasoning with visual and textual information. Adapting these founda…

cs.CV2024

Prompt-driven Universal Model for View-Agnostic Echocardiography Analysis

Sekeun Kim, Hui Ren, Peng Guo +5

Echocardiography segmentation for cardiac analysis is time-consuming and resource-intensive due to the variability in image quality and the necessity to process scans from various…

cs.CV2024

Medical Image Synthesis via Fine-Grained Image-Text Alignment and Anatomy-Pathology Prompting

Wenting Chen, Pengyu Wang, Hui Ren +4

Data scarcity and privacy concerns limit the availability of high-quality medical images for public use, which can be mitigated through medical image synthesis. However, current me…

cs.CV2023★ 8 cited

MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation

Cheng Chen, Juzheng Miao, Dufan Wu +10

The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation ta…