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 …
Medical image registration: a review
This paper presents a review of automated image registration methodologies that have been
used in the medical field. The aim of this paper is to be an introduction to the field, provide …
used in the medical field. The aim of this paper is to be an introduction to the field, provide …
SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry
Every year, millions of brain magnetic resonance imaging (MRI) scans are acquired in
hospitals across the world. These have the potential to revolutionize our understanding of …
hospitals across the world. These have the potential to revolutionize our understanding of …
Quicksilver: Fast predictive image registration–a deep learning approach
This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver
registration for image-pairs works by patch-wise prediction of a deformation model based …
registration for image-pairs works by patch-wise prediction of a deformation model based …
The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics
Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …
reported results from either private institutional data or publicly available datasets. However …
Within-subject template estimation for unbiased longitudinal image analysis
Longitudinal image analysis has become increasingly important in clinical studies of normal
aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the …
aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the …
Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment
We evaluate a fully automatic technique for labeling hippocampal subfields and cortical
subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs …
subregions in the medial temporal lobe in in vivo 3 Tesla MRI. The method performs …
A reproducible evaluation of ANTs similarity metric performance in brain image registration
The United States National Institutes of Health (NIH) commit significant support to open-
source data and software resources in order to foment reproducibility in the biomedical …
source data and software resources in order to foment reproducibility in the biomedical …
Unbiased average age-appropriate atlases for pediatric studies
Spatial normalization, registration, and segmentation techniques for Magnetic Resonance
Imaging (MRI) often use a target or template volume to facilitate processing, take advantage …
Imaging (MRI) often use a target or template volume to facilitate processing, take advantage …
Multi-atlas segmentation with joint label fusion
Multi-atlas segmentation is an effective approach for automatically labeling objects of
interest in biomedical images. In this approach, multiple expert-segmented example images …
interest in biomedical images. In this approach, multiple expert-segmented example images …