Estimating a reference standard segmentation with spatially varying performance parameters: Local MAP STAPLE
O Commowick, A Akhondi-Asl… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
We present a new algorithm, called local MAP STAPLE, to estimate from a set of multi-label
segmentations both a reference standard segmentation and spatially varying performance …
segmentations both a reference standard segmentation and spatially varying performance …
Incorporating priors on expert performance parameters for segmentation validation and label fusion: a maximum a posteriori STAPLE
O Commowick, SK Warfield - … on Medical Image Computing and Computer …, 2010 - Springer
In order to evaluate the quality of segmentations of an image and assess intra-and inter-
expert variability in segmentation performance, an Expectation Maximization (EM) algorithm …
expert variability in segmentation performance, an Expectation Maximization (EM) algorithm …
Simultaneous truth and performance level estimation through fusion of probabilistic segmentations
A Akhondi-Asl, SK Warfield - IEEE transactions on medical …, 2013 - ieeexplore.ieee.org
Recent research has demonstrated that improved image segmentation can be achieved by
multiple template fusion utilizing both label and intensity information. However, intensity …
multiple template fusion utilizing both label and intensity information. However, intensity …
Family of boundary overlap metrics for the evaluation of medical image segmentation
V Yeghiazaryan, I Voiculescu - Journal of Medical Imaging, 2018 - spiedigitallibrary.org
All medical image segmentation algorithms need to be validated and compared, yet no
evaluation framework is widely accepted within the imaging community. None of the …
evaluation framework is widely accepted within the imaging community. None of the …
Medical image segmentation: a brief survey
Abstract Accurate segmentation of 2-D, 3-D, and 4-D medical images to isolate anatomical
objects of interest for analysis is essential in almost any computer-aided diagnosis system or …
objects of interest for analysis is essential in almost any computer-aided diagnosis system or …
Neighbor-constrained segmentation with level set based 3-D deformable models
A novel method for the segmentation of multiple objects from three-dimensional (3-D)
medical images using interobject constraints is presented. Our method is motivated by the …
medical images using interobject constraints is presented. Our method is motivated by the …
[图书][B] Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies: Volume 1
With the advances in image guided surgery for cancer treatment, the role of image
segmentation and registration has become very critical. The central engine of any image …
segmentation and registration has become very critical. The central engine of any image …
A generative model for image segmentation based on label fusion
We propose a nonparametric, probabilistic model for the automatic segmentation of medical
images, given a training set of images and corresponding label maps. The resulting …
images, given a training set of images and corresponding label maps. The resulting …
Validation of image segmentation by estimating rater bias and variance
SK Warfield, KH Zou, WM Wells - … , October 1-6, 2006. Proceedings, Part II …, 2006 - Springer
The accuracy and precision of segmentations of medical images has been difficult to
quantify in the absence of a “ground truth” or reference standard segmentation for clinical …
quantify in the absence of a “ground truth” or reference standard segmentation for clinical …
Multitalent: A multi-dataset approach to medical image segmentation
The medical imaging community generates a wealth of data-sets, many of which are openly
accessible and annotated for specific diseases and tasks such as multi-organ or lesion …
accessible and annotated for specific diseases and tasks such as multi-organ or lesion …