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 …
A survey of MRI-based medical image analysis for brain tumor studies
MRI-based medical image analysis for brain tumor studies is gaining attention in recent
times due to an increased need for efficient and objective evaluation of large amounts of …
times due to an increased need for efficient and objective evaluation of large amounts of …
f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks
Obtaining expert labels in clinical imaging is difficult since exhaustive annotation is time-
consuming. Furthermore, not all possibly relevant markers may be known and sufficiently …
consuming. Furthermore, not all possibly relevant markers may be known and sufficiently …
Automatic brain tumor segmentation using cascaded anisotropic convolutional neural networks
A cascade of fully convolutional neural networks is proposed to segment multi-modal
Magnetic Resonance (MR) images with brain tumor into background and three hierarchical …
Magnetic Resonance (MR) images with brain tumor into background and three hierarchical …
Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation
SK Warfield, KH Zou, WM Wells - IEEE transactions on medical …, 2004 - ieeexplore.ieee.org
Characterizing the performance of image segmentation approaches has been a persistent
challenge. Performance analysis is important since segmentation algorithms often have …
challenge. Performance analysis is important since segmentation algorithms often have …
Statistical validation of image segmentation quality based on a spatial overlap index1: scientific reports
KH Zou, SK Warfield, A Bharatha, CMC Tempany… - Academic radiology, 2004 - Elsevier
Rationale and Objectives. To examine a statistical validation method based on the spatial
overlap between two sets of segmentations of the same anatomy. Materials and Methods …
overlap between two sets of segmentations of the same anatomy. Materials and Methods …
State of the art survey on MRI brain tumor segmentation
N Gordillo, E Montseny, P Sobrevilla - Magnetic resonance imaging, 2013 - Elsevier
Brain tumor segmentation consists of separating the different tumor tissues (solid or active
tumor, edema, and necrosis) from normal brain tissues: gray matter (GM), white matter (WM) …
tumor, edema, and necrosis) from normal brain tissues: gray matter (GM), white matter (WM) …
A hybrid deep learning model for brain tumour classification
A brain tumour is one of the major reasons for death in humans, and it is the tenth most
common type of tumour that affects people of all ages. However, if detected early, it is one of …
common type of tumour that affects people of all ages. However, if detected early, it is one of …
Cortical thickness and central surface estimation
Several properties of the human brain cortex, eg, cortical thickness and gyrification, have
been found to correlate with the progress of neuropsychiatric disorders. The relationship …
been found to correlate with the progress of neuropsychiatric disorders. The relationship …
A survey of MRI-based brain tumor segmentation methods
Brain tumor segmentation aims to separate the different tumor tissues such as active cells,
necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM) …
necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM) …