102 citations · 167 across the 7 of their papers we have counts for
5 papers · 1 filter
Emphysema Subtyping on Thoracic Computed Tomography Scans using Deep Neural Networks
Weiyi Xie, Colin Jacobs, Jean-Paul Charbonnier +2
Accurate identification of emphysema subtypes and severity is crucial for effective management of COPD and the study of disease heterogeneity. Manual analysis of emphysema subtypes…
Deep Clustering Activation Maps for Emphysema Subtyping
Weiyi Xie, Colin Jacobs, Bram van Ginneken
We propose a deep learning clustering method that exploits dense features from a segmentation network for emphysema subtyping from computed tomography (CT) scans. Using dense featu…
Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients
Weiyi Xie, Colin Jacobs, Jean-Paul Charbonnier +1
Automatic lesion segmentation on thoracic CT enables rapid quantitative analysis of lung involvement in COVID-19 infections. However, obtaining a large amount of voxel-level annota…
Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans
Weiyi Xie, Colin Jacobs, Jean-Paul Charbonnier +1
Pulmonary lobe segmentation in computed tomography scans is essential for regional assessment of pulmonary diseases. Recent works based on convolution neural networks have achieved…
2.75D: Boosting learning by representing 3D Medical imaging to 2D features for small data
Xin Wang, Ruisheng Su, Weiyi Xie +5
In medical-data driven learning, 3D convolutional neural networks (CNNs) have started to show superior performance to 2D CNNs in numerous deep learning tasks, proving the added val…