77 citations · 112 across the 6 of their papers we have counts for
6 papers · 1 filter
Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment
Florin C. Ghesu, Bogdan Georgescu, Eli Gibson +6
The interpretation of chest radiographs is an essential task for the detection of thoracic diseases and abnormalities. However, it is a challenging problem with high inter-rater va…
Multi-task Learning for Chest X-ray Abnormality Classification on Noisy Labels
Sebastian Guendel, Florin C. Ghesu, Sasa Grbic +4
Chest X-ray (CXR) is the most common X-ray examination performed in daily clinical practice for the diagnosis of various heart and lung abnormalities. The large amount of data to b…
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…
Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration
Yipeng Hu, Marc Modat, Eli Gibson +11
One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a…
Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks
Yipeng Hu, Eli Gibson, Tom Vercauteren +5
In this paper, we describe how a patient-specific, ultrasound-probe-induced prostate motion model can be directly generated from a single preoperative MR image. Our motion model al…