Going deep in medical image analysis: concepts, methods, challenges, and future directions

F Altaf, SMS Islam, N Akhtar, NK Janjua - IEEE access, 2019‏ - ieeexplore.ieee.org
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 …

A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond

J Chen, Y Liu, S Wei, Z Bian, S Subramanian… - Medical Image …, 2024‏ - Elsevier
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 …

[HTML][HTML] The Allen mouse brain common coordinate framework: a 3D reference atlas

Q Wang, SL Ding, Y Li, J Royall, D Feng, P Lesnar… - Cell, 2020‏ - cell.com
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 …

Voxelmorph: a learning framework for deformable medical image registration

G Balakrishnan, A Zhao, MR Sabuncu… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical
image registration. Traditional registration methods optimize an objective function for each …

Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces

AV Dalca, G Balakrishnan, J Guttag, MR Sabuncu - Medical image analysis, 2019‏ - Elsevier
Classical deformable registration techniques achieve impressive results and offer a rigorous
theoretical treatment, but are computationally intensive since they solve an optimization …

An unsupervised learning model for deformable medical image registration

G Balakrishnan, A Zhao, MR Sabuncu… - Proceedings of the …, 2018‏ - openaccess.thecvf.com
We present a fast learning-based algorithm for deformable, pairwise 3D medical image
registration. Current registration methods optimize an objective function independently for …

Fast symmetric diffeomorphic image registration with convolutional neural networks

TCW Mok, A Chung - … of the IEEE/CVF conference on …, 2020‏ - openaccess.thecvf.com
Diffeomorphic deformable image registration is crucial in many medical image studies, as it
offers unique, special features including topology preservation and invertibility of the …

Recursive cascaded networks for unsupervised medical image registration

S Zhao, Y Dong, EI Chang, Y Xu - Proceedings of the IEEE …, 2019‏ - openaccess.thecvf.com
We present recursive cascaded networks, a general architecture that enables learning deep
cascades, for deformable image registration. The proposed architecture is simple in design …

Multi-atlas segmentation of biomedical images: a survey

JE Iglesias, MR Sabuncu - Medical image analysis, 2015‏ - Elsevier
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 …

Deformable medical image registration: A survey

A Sotiras, C Davatzikos… - IEEE transactions on …, 2013‏ - ieeexplore.ieee.org
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 …