156 citations · 355 across the 27 of their papers we have counts for
5 papers · 1 filter
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…
Decompose to manipulate: Manipulable Object Synthesis in 3D Medical Images with Structured Image Decomposition
Siqi Liu, Eli Gibson, Sasa Grbic +5
The performance of medical image analysis systems is constrained by the quantity of high-quality image annotations. Such systems require data to be annotated by experts with years…
Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Images
Zhoubing Xu, Yuankai Huo, JinHyeong Park +4
An abdominal ultrasound examination, which is the most common ultrasound examination, requires substantial manual efforts to acquire standard abdominal organ views, annotate the vi…
Select, Attend, and Transfer: Light, Learnable Skip Connections
Saeid Asgari Taghanaki, Aicha Bentaieb, Anmol Sharma +8
Skip connections in deep networks have improved both segmentation and classification performance by facilitating the training of deeper network architectures, and reducing the risk…
Learning to recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks
Sebastian Guendel, Sasa Grbic, Bogdan Georgescu +4
Chest X-ray is the most common medical imaging exam used to assess multiple pathologies. Automated algorithms and tools have the potential to support the reading workflow, improve…