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20222026
most citedSA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks

14 citations · 75 across the 19 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

eess.IV2023★ 10 cited

SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Xiangde Luo, Jia Fu, Yunxin Zhong +39

Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is c…

cs.CL2023★ 1 cited

Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies

Pengcheng Chen, Ziyan Huang, Zhongying Deng +6

OpenAI's latest large vision-language model (LVLM), GPT-4V(ision), has piqued considerable interest for its potential in medical applications. Despite its promise, recent studies a…

eess.IV2023★ 14 cited

SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks

Jin Ye, Junlong Cheng, Jianpin Chen +12

Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massiv…

cs.CV2023★ 11 cited

SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Haoyu Wang, Sizheng Guo, Jin Ye +11

Existing volumetric medical image segmentation models are typically task-specific, excelling at specific target but struggling to generalize across anatomical structures or modalit…

eess.IV2023★ 8 cited

A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation

Ziyan Huang, Zhongying Deng, Jin Ye +11

Although deep learning have revolutionized abdominal multi-organ segmentation, models often struggle with generalization due to training on small, specific datasets. With the recen…