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Going deep in medical image analysis: concepts, methods, challenges, and future directions
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …
technology has recently attracted so much interest of the Medical Imaging Community that it …
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond
Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …
registration over the past decade. The initial developments, such as regression-based and U …
[HTML][HTML] The Allen mouse brain common coordinate framework: a 3D reference atlas
Recent large-scale collaborations are generating major surveys of cell types and
connections in the mouse brain, collecting large amounts of data across modalities, spatial …
connections in the mouse brain, collecting large amounts of data across modalities, spatial …
Voxelmorph: a learning framework for deformable medical image registration
We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical
image registration. Traditional registration methods optimize an objective function for each …
image registration. Traditional registration methods optimize an objective function for each …
Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces
Classical deformable registration techniques achieve impressive results and offer a rigorous
theoretical treatment, but are computationally intensive since they solve an optimization …
theoretical treatment, but are computationally intensive since they solve an optimization …
An unsupervised learning model for deformable medical image registration
We present a fast learning-based algorithm for deformable, pairwise 3D medical image
registration. Current registration methods optimize an objective function independently for …
registration. Current registration methods optimize an objective function independently for …
Fast symmetric diffeomorphic image registration with convolutional neural networks
Diffeomorphic deformable image registration is crucial in many medical image studies, as it
offers unique, special features including topology preservation and invertibility of the …
offers unique, special features including topology preservation and invertibility of the …
Recursive cascaded networks for unsupervised medical image registration
We present recursive cascaded networks, a general architecture that enables learning deep
cascades, for deformable image registration. The proposed architecture is simple in design …
cascades, for deformable image registration. The proposed architecture is simple in design …
Multi-atlas segmentation of biomedical images: a survey
Abstract Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering
work of Rohlfing, et al.(2004), Klein, et al.(2005), and Heckemann, et al.(2006), is becoming …
work of Rohlfing, et al.(2004), Klein, et al.(2005), and Heckemann, et al.(2006), is becoming …
Deformable medical image registration: A survey
Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …
its most important applications, one may cite: 1) multi-modality fusion, where information …