The multimodal brain tumor image segmentation benchmark (BRATS)
In this paper we report the set-up and results of the Multimodal Brain Tumor Image
Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and …
Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and …
Multi-atlas segmentation of biomedical images: a survey
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 …
Hierarchical convolutional neural networks for segmentation of breast tumors in MRI with application to radiogenomics
Breast tumor segmentation based on dynamic contrast-enhanced magnetic resonance
imaging (DCE-MRI) is a challenging problem and an active area of research. Particular …
imaging (DCE-MRI) is a challenging problem and an active area of research. Particular …
Longitudinal brain tumor segmentation prediction in MRI using feature and label fusion
This work proposes a novel framework for brain tumor segmentation prediction in
longitudinal multimodal MRI scans, comprising two methods; feature fusion and joint label …
longitudinal multimodal MRI scans, comprising two methods; feature fusion and joint label …
Medial temporal lobe subregional morphometry using high resolution MRI in Alzheimer's disease
Autopsy studies of Alzheimer's disease (AD) have found that neurofibrillary tangle (NFT)
pathology of the medial temporal lobe (MTL) demonstrates selective topography with …
pathology of the medial temporal lobe (MTL) demonstrates selective topography with …
Deformable image registration by combining uncertainty estimates from supervoxel belief propagation
Discrete optimisation strategies have a number of advantages over their continuous
counterparts for deformable registration of medical images. For example: it is not necessary …
counterparts for deformable registration of medical images. For example: it is not necessary …
Evolution of multiorgan segmentation techniques from traditional to deep learning in abdominal CT images–A systematic review
H Kaur, N Kaur, N Neeru - Displays, 2022 - Elsevier
Abdominal organ segmentation is the crucial research direction in computer assisted
diagnostic systems. Segmentation of multiple organs in medical images is known as …
diagnostic systems. Segmentation of multiple organs in medical images is known as …
Automatic brain lesion segmentation on standard magnetic resonance images: a sco** review
Objectives Medical image analysis practices face challenges that can potentially be
addressed with algorithm-based segmentation tools. In this study, we map the field of …
addressed with algorithm-based segmentation tools. In this study, we map the field of …
Improved brain tumor segmentation by utilizing tumor growth model in longitudinal brain MRI
In this work, we propose a novel method to improve texture based tumor segmentation by
fusing cell density patterns that are generated from tumor growth modeling. To model tumor …
fusing cell density patterns that are generated from tumor growth modeling. To model tumor …
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 …