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20192023
most cited3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

114 citations · 230 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023★ 1 cited

Treatment Outcome Prediction for Intracerebral Hemorrhage via Generative Prognostic Model with Imaging and Tabular Data

Wenao Ma, Cheng Chen, Jill Abrigo +6

Intracerebral hemorrhage (ICH) is the second most common and deadliest form of stroke. Despite medical advances, predicting treat ment outcomes for ICH remains a challenge. This pa…

cs.CV2023★ 114 cited

3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

Shizhan Gong, Yuan Zhong, Wenao Ma +5

Despite that the segment anything model (SAM) achieved impressive results on general-purpose semantic segmentation with strong generalization ability on daily images, its demonstra…

cs.CV2023

Diffusion Model based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification

Shizhan Gong, Cheng Chen, Yuqi Gong +5

Brain midline shift (MLS) is one of the most critical factors to be considered for clinical diagnosis and treatment decision-making for intracranial hemorrhage. Existing computatio…

cs.CV2022

Rapid model transfer for medical image segmentation via iterative human-in-the-loop update: from labelled public to unlabelled clinical datasets for multi-organ segmentation in CT

Wenao Ma, Shuang Zheng, Lei Zhang +2

Despite the remarkable success on medical image analysis with deep learning, it is still under exploration regarding how to rapidly transfer AI models from one dataset to another f…

cs.CV2021★ 1 cited

Consistent Posterior Distributions under Vessel-Mixing: A Regularization for Cross-Domain Retinal Artery/Vein Classification

Chenxin Li, Yunlong Zhang, Zhehan Liang +3

Retinal artery/vein (A/V) classification is a critical technique for diagnosing diabetes and cardiovascular diseases. Although deep learning based methods achieve impressive result…

cs.CV2019★ 1 cited

Uncertainty-Guided Domain Alignment for Layer Segmentation in OCT Images

Jiexiang Wang, Cheng Bian, Meng Li +6

Automatic and accurate segmentation for retinal and choroidal layers of Optical Coherence Tomography (OCT) is crucial for detection of various ocular diseases. However, because of…