477 citations · 664 across the 6 of their papers we have counts for
6 papers
Collaborative Quantization Embeddings for Intra-Subject Prostate MR Image Registration
Ziyi Shen, Qianye Yang, Yuming Shen +9
Image registration is useful for quantifying morphological changes in longitudinal MR images from prostate cancer patients. This paper describes a development in improving the lear…
Morphological Change Forecasting for Prostate Glands using Feature-based Registration and Kernel Density Extrapolation
Qianye Yang, Tom Vercauteren, Yunguan Fu +7
Organ morphology is a key indicator for prostate disease diagnosis and prognosis. For instance, In longitudinal study of prostate cancer patients under active surveillance, the vol…
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…
Adversarial Deformation Regularization for Training Image Registration Neural Networks
Yipeng Hu, Eli Gibson, Nooshin Ghavami +6
We describe an adversarial learning approach to constrain convolutional neural network training for image registration, replacing heuristic smoothness measures of displacement fiel…
Label-driven weakly-supervised learning for multimodal deformable image registration
Yipeng Hu, Marc Modat, Eli Gibson +7
Spatially aligning medical images from different modalities remains a challenging task, especially for intraoperative applications that require fast and robust algorithms. We propo…
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…