18 citations · 44 across the 11 of their papers we have counts for
6 papers · 1 filter
Automated Multi-Process CTC Detection using Deep Learning
Elena Alexander, Kam W. Leong, Andrew F. Laine
Circulating Tumor Cells (CTCs) bear great promise as biomarkers in tumor prognosis. However, the process of identification and later enumeration of CTCs require manual labor, which…
Novel Subtypes of Pulmonary Emphysema Based on Spatially-Informed Lung Texture Learning
Jie Yang, Elsa D. Angelini, Pallavi P. Balte +5
Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes previously identified on autops…
Class-Aware Adversarial Lung Nodule Synthesis in CT Images
Jie Yang, Siqi Liu, Sasa Grbic +7
Though large-scale datasets are essential for training deep learning systems, it is expensive to scale up the collection of medical imaging datasets. Synthesizing the objects of in…
Discriminative analysis of the human cortex using spherical CNNs - a study on Alzheimer's disease diagnosis
Xinyang Feng, Jie Yang, Andrew F. Laine +1
In neuroimaging studies, the human cortex is commonly modeled as a sphere to preserve the topological structure of the cortical surface. Cortical neuroimaging measures hence can be…
Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules
Xinyang Feng, Jie Yang, Andrew F. Laine +1
Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis. Existing supervised approaches for auto…
Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study
Jie Yang, Elsa D. Angelini, Benjamin M. Smith +5
Pulmonary emphysema is traditionally subcategorized into three subtypes, which have distinct radiological appearances on computed tomography (CT) and can help with the diagnosis of…