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20162023
most citedReview of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

1k citations · 1.6k across the 27 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

eess.IV2019

Deep Local Global Refinement Network for Stent Analysis in IVOCT Images

Yuyu Guo

Implantation of stents into coronary arteries is a common treatment option for patients with cardiovascular disease. Assessment of safety and efficacy of the stent implantation occ…

eess.IV2019

Synthesis and Inpainting-Based MR-CT Registration for Image-Guided Thermal Ablation of Liver Tumors

Dongming Wei, Sahar Ahmad, Jiayu Huo +7

Thermal ablation is a minimally invasive procedure for treat-ing small or unresectable tumors. Although CT is widely used for guiding ablation procedures, the contrast of tumors ag…

eess.IV2019★ 3 cited

Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis

Dong Nie, Lei Xiang, Qian Wang +1

Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and risk, the acquisition of certain image modalities c…

eess.IV2019★ 2 cited

Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization

Xuhua Ren, Lichi Zhang, Qian Wang +1

Medical image segmentation is challenging especially in dealing with small dataset of 3D MR images. Encoding the variation of brain anatomical struc-tures from individual subjects…

cs.CV2019★ 27 cited

Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation

Xuhua Ren, Lichi Zhang, Sahar Ahmad +5

Semantic segmentation is essentially important to biomedical image analysis. Many recent works mainly focus on integrating the Fully Convolutional Network (FCN) architecture with s…

cs.CV2019★ 2 cited

Deep Morphological Simplification Network (MS-Net) for Guided Registration of Brain Magnetic Resonance Images

Dongming Wei, Zhengwang Wu, Gang Li +3

Objective: Deformable brain MR image registration is challenging due to large inter-subject anatomical variation. For example, the highly complex cortical folding pattern makes it…