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20042026
most citedJoint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

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39 papers · 1 filter

eess.IV2025★ 2 cited

MSA-UNet3+: Multi-Scale Attention UNet3+ with New Supervised Prototypical Contrastive Loss for Coronary DSA Image Segmentation

Rayan Merghani Ahmed, Adnan Iltaf, Mohamed Elmanna +5

Accurate segmentation of coronary Digital Subtraction Angiography (DSA) images is essential for diagnosing and treating coronary artery disease (CAD). Despite advances in deep lear…

eess.IV2025★ 1 cited

Benchmark of Segmentation Techniques for Pelvic Fracture in CT and X-ray: Summary of the PENGWIN 2024 Challenge

Yudi Sang, Yanzhen Liu, Sutuke Yibulayimu +33

The segmentation of pelvic fracture fragments in CT and X-ray images is crucial for trauma diagnosis, surgical planning, and intraoperative guidance. However, accurately and effici…

eess.IV2024★ 52 cited

DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency

Wenfang Yao, Kejing Yin, William K. Cheung +2

The combination of electronic health records (EHR) and medical images is crucial for clinicians in making diagnoses and forecasting prognosis. Strategically fusing these two data m…

eess.IV2024

Modality Exchange Network for Retinogeniculate Visual Pathway Segmentation

Hua Han, Cheng Li, Lei Xie +3

Accurate segmentation of the retinogeniculate visual pathway (RGVP) aids in the diagnosis and treatment of visual disorders by identifying disruptions or abnormalities within the p…

eess.IV2024

LESEN: Label-Efficient deep learning for Multi-parametric MRI-based Visual Pathway Segmentation

Alou Diakite, Cheng Li, Lei Xie +3

Recent research has shown the potential of deep learning in multi-parametric MRI-based visual pathway (VP) segmentation. However, obtaining labeled data for training is laborious a…

eess.IV2022★ 95 cited

High-Frequency Space Diffusion Models for Accelerated MRI

Chentao Cao, Zhuo-Xu Cui, Yue Wang +5

Diffusion models with continuous stochastic differential equations (SDEs) have shown superior performances in image generation. It can serve as a deep generative prior to solving t…