activity
20182021
most citedRecursive Refinement Network for Deformable Lung Registration between Exhale and Inhale CT Scans

9 citations · 27 across the 7 of their papers we have counts for

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Showing eess.IVShow all

5 papers · 1 filter

eess.IV20219 cited

Recursive Refinement Network for Deformable Lung Registration between Exhale and Inhale CT Scans

Xinzi He, Jia Guo, Xuzhe Zhang +9

Unsupervised learning-based medical image registration approaches have witnessed rapid development in recent years. We propose to revisit a commonly ignored while simple and well-e…

eess.IV20204 cited

Simultaneous Left Atrium Anatomy and Scar Segmentations via Deep Learning in Multiview Information with Attention

Guang Yang, Jun Chen, Zhifan Gao +13

Three-dimensional late gadolinium enhanced (LGE) cardiac MR (CMR) of left atrial scar in patients with atrial fibrillation (AF) has recently emerged as a promising technique to str…

eess.IV20196 cited

Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction

Shuo Wang, Chengliang Dai, Yuanhan Mo +3

Gliomas are the most common malignant brain tumourswith intrinsic heterogeneity. Accurate segmentation of gliomas and theirsub-regions on multi-parametric magnetic resonance images…

eess.IV2019

Transfer Learning from Partial Annotations for Whole Brain Segmentation

Chengliang Dai, Yuanhan Mo, Elsa Angelini +2

Brain MR image segmentation is a key task in neuroimaging studies. It is commonly conducted using standard computational tools, such as FSL, SPM, multi-atlas segmentation etc, whic…

eess.IV2019

SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A novel approach to train Convolutional Neural Networks on lung CT scans using binary labels only

Mario Zusag, Sujal Desai, Marcello Di Paolo +3

Chronic Pulmonary Aspergillosis (CPA) is a complex lung disease caused by infection with Aspergillus. Computed tomography (CT) images are frequently requested in patients with susp…