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 …
work of Rohlfing, et al.(2004), Klein, et al.(2005), and Heckemann, et al.(2006), is becoming …
A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging
Cardiovascular magnetic resonance (CMR) has become a key imaging modality in clinical
cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac …
cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac …
An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement
This paper presents an open, multi-vendor, multi-field strength magnetic resonance (MR) T1-
weighted volumetric brain imaging dataset, named Calgary-Campinas-359 (CC-359). The …
weighted volumetric brain imaging dataset, named Calgary-Campinas-359 (CC-359). The …
Exploiting epistemic uncertainty of anatomy segmentation for anomaly detection in retinal OCT
Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical
images. Although supervised deep learning can perform accurate segmentation of …
images. Although supervised deep learning can perform accurate segmentation of …
Disentangling human error from ground truth in segmentation of medical images
Recent years have seen increasing use of supervised learning methods for segmentation
tasks. However, the predictive performance of these algorithms depends on the quality of …
tasks. However, the predictive performance of these algorithms depends on the quality of …
[HTML][HTML] STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation
MJ Cardoso, K Leung, M Modat, S Keihaninejad… - Medical image …, 2013 - Elsevier
Anatomical segmentation of structures of interest is critical to quantitative analysis in medical
imaging. Several automated multi-atlas based segmentation propagation methods that …
imaging. Several automated multi-atlas based segmentation propagation methods that …
[HTML][HTML] Robust whole-brain segmentation: application to traumatic brain injury
We propose a framework for the robust and fully-automatic segmentation of magnetic
resonance (MR) brain images called “Multi-Atlas Label Propagation with Expectation …
resonance (MR) brain images called “Multi-Atlas Label Propagation with Expectation …
Non-local statistical label fusion for multi-atlas segmentation
AJ Asman, BA Landman - Medical image analysis, 2013 - Elsevier
Multi-atlas segmentation provides a general purpose, fully-automated approach for
transferring spatial information from an existing dataset (“atlases”) to a previously unseen …
transferring spatial information from an existing dataset (“atlases”) to a previously unseen …
Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks
Manual annotation is considered to be the “gold standard” in medical imaging analysis.
However, medical imaging datasets that include expert manual segmentation are scarce as …
However, medical imaging datasets that include expert manual segmentation are scarce as …
[HTML][HTML] Learning from multiple annotators for medical image segmentation
Supervised machine learning methods have been widely developed for segmentation tasks
in recent years. However, the quality of labels has high impact on the predictive performance …
in recent years. However, the quality of labels has high impact on the predictive performance …