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20192025
most citedHeterogeneous Memory Enhanced Multimodal Attention Model for Video Question Answering

35 citations · 38 across the 5 of their papers we have counts for

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7 papers · 1 filter

cs.CV2024

Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment

Yankai Jiang, Wenhui Lei, Xiaofan Zhang +1

Recent advancements in medical vision-language pre-training models have driven significant progress in zero-shot disease recognition. However, transferring image-level knowledge to…

cs.CV20242 cited

MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications

Yongrui Yu, Yannian Gu, Shaoting Zhang +1

Diffusion models have achieved significant success in both natural image and medical image domains, encompassing a wide range of applications. Previous investigations in medical im…

cs.CV2023

ZePT: Zero-Shot Pan-Tumor Segmentation via Query-Disentangling and Self-Prompting

Yankai Jiang, Zhongzhen Huang, Rongzhao Zhang +2

The long-tailed distribution problem in medical image analysis reflects a high prevalence of common conditions and a low prevalence of rare ones, which poses a significant challeng…

cs.CV2023

Efficient Subclass Segmentation in Medical Images

Linrui Dai, Wenhui Lei, Xiaofan Zhang

As research interests in medical image analysis become increasingly fine-grained, the cost for extensive annotation also rises. One feasible way to reduce the cost is to annotate w…

cs.CV2023

KiUT: Knowledge-injected U-Transformer for Radiology Report Generation

Zhongzhen Huang, Xiaofan Zhang, Shaoting Zhang

Radiology report generation aims to automatically generate a clinically accurate and coherent paragraph from the X-ray image, which could relieve radiologists from the heavy burden…

cs.CV20221 cited

Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation

Ran Gu, Jiangshan Lu, Jingyang Zhang +4

Efficiently utilizing discriminative features is crucial for convolutional neural networks to achieve remarkable performance in medical image segmentation and is also important for…