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 …
3D whole brain segmentation using spatially localized atlas network tiles
Detailed whole brain segmentation is an essential quantitative technique in medical image
analysis, which provides a non-invasive way of measuring brain regions from a clinical …
analysis, which provides a non-invasive way of measuring brain regions from a clinical …
Consistent cortical reconstruction and multi-atlas brain segmentation
Whole brain segmentation and cortical surface reconstruction are two essential techniques
for investigating the human brain. Spatial inconsistences, which can hinder further …
for investigating the human brain. Spatial inconsistences, which can hinder further …
Anatomical context improves deep learning on the brain age estimation task
Deep learning has shown remarkable improvements in the analysis of medical images
without the need for engineered features. In this work, we hypothesize that deep learning is …
without the need for engineered features. In this work, we hypothesize that deep learning is …
Hippocampal network modularity is associated with relational memory dysfunction in schizophrenia
Background Functional dysconnectivity has been proposed as a major pathophysiological
mechanism for cognitive dysfunction in schizophrenia. The hippocampus is a focal point of …
mechanism for cognitive dysfunction in schizophrenia. The hippocampus is a focal point of …
Disrupted habituation in the early stage of psychosis
Background Learning and memory are impaired in schizophrenia. Some theories have
proposed that one form of memory, habituation, is particularly impaired. Preliminary …
proposed that one form of memory, habituation, is particularly impaired. Preliminary …
Multi-atlas learner fusion: An efficient segmentation approach for large-scale data
We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately
replicating the highly accurate, yet computationally expensive, multi-atlas segmentation …
replicating the highly accurate, yet computationally expensive, multi-atlas segmentation …
Hierarchical performance estimation in the statistical label fusion framework
AJ Asman, BA Landman - Medical image analysis, 2014 - Elsevier
Label fusion is a critical step in many image segmentation frameworks (eg, multi-atlas
segmentation) as it provides a mechanism for generalizing a collection of labeled examples …
segmentation) as it provides a mechanism for generalizing a collection of labeled examples …
Stable habituation deficits in the early stage of psychosis: a 2-year follow-up study
Neural habituation, the decrease in brain response to repeated stimuli, is a fundamental,
highly conserved mechanism that acts as an essential filter for our complex sensory …
highly conserved mechanism that acts as an essential filter for our complex sensory …
OpenMAP-T1: A Rapid Deep Learning Approach to Parcellate 280 Anatomical Regions to Cover the Whole Brain
This study introduces OpenMAP-T1, a deep-learning-based method for rapid and accurate
whole-brain parcellation in T1-weighted brain MRI, which aims to overcome the limitations of …
whole-brain parcellation in T1-weighted brain MRI, which aims to overcome the limitations of …