3D deformable registration of longitudinal abdominopelvic CT images using unsupervised deep learning

Deep learning in medical image registration: a survey

(2020) Grant Haskins et al.   MACHINE VISION AND APPLICATIONS

Correlating Radiomic Features of Heterogeneity on CT with Circulating Tumor DNA in Metastatic Melanoma

(2020) Andrew B Gill et al.   Cancers

Learning a Probabilistic Model for Diffeomorphic Registration

(2019) Julian Krebs et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

VoxelMorph: A Learning Framework for Deformable Medical Image Registration

(2019) Guha Balakrishnan et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Texture analysis of apparent diffusion coefficient maps for treatment response assessment in prostate cancer bone metastases—A pilot study

(2018) Carolin Reischauer et al.   EUROPEAN JOURNAL OF RADIOLOGY

Weakly-supervised convolutional neural networks for multimodal image registration

(2018) Yipeng Hu et al.   MEDICAL IMAGE ANALYSIS

Fully Automatic Brain Tumor Segmentation using End-to-End Incremental Deep Neural Networks in MRI images

(2018) Mostefa Ben naceur et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Enhanced detection of circulating tumor DNA by fragment size analysis

(2018) Florent Mouliere et al.   Science Translational Medicine

A deep learning framework for unsupervised affine and deformable image registration

(2018) Bob D. de Vos et al.   MEDICAL IMAGE ANALYSIS

Pulmonary CT Registration Through Supervised Learning With Convolutional Neural Networks

(2018) Koen A. J. Eppenhof et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Quicksilver: Fast predictive image registration – A deep learning approach

(2017) Xiao Yang et al.   NEUROIMAGE

A mixed-scale dense convolutional neural network for image analysis

(2017) Daniël M. Pelt et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Quantitative Imaging in Cancer Clinical Trials

(2016) T. E. Yankeelov et al.   CLINICAL CANCER RESEARCH

Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT

(2016) Zhoubing Xu et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

(2016) Guorong Wu et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Combining split-and-merge and multi-seed region growing algorithms for uterine fibroid segmentation in MRgFUS treatments

(2015) Leonardo Rundo et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements

(2014) Nicholas J. Tustison et al.   NEUROIMAGE

Assessment of Treatment Response by Total Tumor Volume and Global Apparent Diffusion Coefficient Using Diffusion-Weighted MRI in Patients with Metastatic Bone Disease: A Feasibility Study

(2014) Matthew D. Blackledge et al.   PLoS One

Automated Detection of Sclerotic Metastases in the Thoracolumbar Spine at CT

(2013) Joseph E. Burns et al.   RADIOLOGY

Automatic Patient Table Removal in CT Images

(2012) Yang-Ming Zhu et al.   JOURNAL OF DIGITAL IMAGING

Fast free-form deformation using graphics processing units

(2009) Marc Modat et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

elastix: A Toolbox for Intensity-Based Medical Image Registration

(2009) S. Klein et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets

(2009) Richard Castillo et al.   PHYSICS IN MEDICINE AND BIOLOGY

Diffeomorphic demons: Efficient non-parametric image registration

(2008) Tom Vercauteren et al.   NEUROIMAGE

Evaluating the influence of the Siemens IGRT carbon fibre tabletop in head and neck IMRT

(2008) Emiliano Spezi et al.   RADIOTHERAPY AND ONCOLOGY

Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain

(2007) B AVANTS et al.   MEDICAL IMAGE ANALYSIS