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20242026
most citedVISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging

6 citations · 16 across the 17 of their papers we have counts for

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eess.IV2024

Text-Driven Tumor Synthesis

Xinran Li, Yi Shuai, Chen Liu +11

Tumor synthesis can generate examples that AI often misses or over-detects, improving AI performance by training on these challenging cases. However, existing synthesis methods, wh…

cs.CV2024★ 1 cited

VILA-M3: Enhancing Vision-Language Models with Medical Expert Knowledge

Vishwesh Nath, Wenqi Li, Dong Yang +22

Generalist vision language models (VLMs) have made significant strides in computer vision, but they fall short in specialized fields like healthcare, where expert knowledge is esse…

eess.IV2024★ 3 cited

MAISI: Medical AI for Synthetic Imaging

Pengfei Guo, Can Zhao, Dong Yang +8

Medical imaging analysis faces challenges such as data scarcity, high annotation costs, and privacy concerns. This paper introduces the Medical AI for Synthetic Imaging (MAISI), an…

cs.CV2024

A Short Review and Evaluation of SAM2's Performance in 3D CT Image Segmentation

Yufan He, Pengfei Guo, Yucheng Tang +7

Since the release of Segment Anything 2 (SAM2), the medical imaging community has been actively evaluating its performance for 3D medical image segmentation. However, different stu…

eess.IV2024★ 4 cited

HoloHisto: End-to-end Gigapixel WSI Segmentation with 4K Resolution Sequential Tokenization

Yucheng Tang, Yufan He, Vishwesh Nath +11

In digital pathology, the traditional method for deep learning-based image segmentation typically involves a two-stage process: initially segmenting high-resolution whole slide ima…

cs.CV2024★ 6 cited

VISTA3D: A Unified Segmentation Foundation Model For 3D Medical Imaging

Yufan He, Pengfei Guo, Yucheng Tang +11

Foundation models for interactive segmentation in 2D natural images and videos have sparked significant interest in building 3D foundation models for medical imaging. However, the…