Current methods in medical image segmentation
▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by
automating or facilitating the delineation of anatomical structures and other regions of …
automating or facilitating the delineation of anatomical structures and other regions of …
A review of methods for correction of intensity inhomogeneity in MRI
U Vovk, F Pernus, B Likar - IEEE transactions on medical …, 2007 - ieeexplore.ieee.org
Medical image acquisition devices provide a vast amount of anatomical and functional
information, which facilitate and improve diagnosis and patient treatment, especially when …
information, which facilitate and improve diagnosis and patient treatment, especially when …
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
Y Zhang, M Brady, S Smith - IEEE transactions on medical …, 2001 - ieeexplore.ieee.org
The finite mixture (FM) model is the most commonly used model for statistical segmentation
of brain magnetic resonance (MR) images because of its simple mathematical form and the …
of brain magnetic resonance (MR) images because of its simple mathematical form and the …
Transfer learning improves supervised image segmentation across imaging protocols
A Van Opbroek, MA Ikram, MW Vernooij… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
The variation between images obtained with different scanners or different imaging
protocols presents a major challenge in automatic segmentation of biomedical images. This …
protocols presents a major challenge in automatic segmentation of biomedical images. This …
BrainSuite: an automated cortical surface identification tool
DW Shattuck, RM Leahy - Medical image analysis, 2002 - Elsevier
We describe a new magnetic resonance (MR) image analysis tool that produces cortical
surface representations with spherical topology from MR images of the human brain. The …
surface representations with spherical topology from MR images of the human brain. The …
Magnetic resonance image tissue classification using a partial volume model
DW Shattuck, SR Sandor-Leahy, KA Schaper… - NeuroImage, 2001 - Elsevier
We describe a sequence of low-level operations to isolate and classify brain tissue within T1-
weighted magnetic resonance images (MRI). Our method first removes nonbrain tissue …
weighted magnetic resonance images (MRI). Our method first removes nonbrain tissue …
Fast and robust parameter estimation for statistical partial volume models in brain MRI
Due to the finite spatial resolution of imaging devices, a single voxel in a medical image may
be composed of mixture of tissue types, an effect known as partial volume effect (PVE) …
be composed of mixture of tissue types, an effect known as partial volume effect (PVE) …
Medical image analysis: Progress over two decades and the challenges ahead
The analysis of medical images has been woven into the fabric of the pattern analysis and
machine intelligence (PAMI) community since the earliest days of these Transactions …
machine intelligence (PAMI) community since the earliest days of these Transactions …
Intensity non-uniformity correction in MRI: existing methods and their validation
Magnetic resonance imaging is a popular and powerful non-invasive imaging technique.
Automated analysis has become mandatory to efficiently cope with the large amount of data …
Automated analysis has become mandatory to efficiently cope with the large amount of data …
Retrospective correction of MR intensity inhomogeneity by information minimization
B Likar, MA Viergever, F Pernus - IEEE transactions on medical …, 2001 - ieeexplore.ieee.org
In this paper, the problem of retrospective correction of intensity inhomogeneity in magnetic
resonance (MR) images is addressed. A novel model-based correction method is proposed …
resonance (MR) images is addressed. A novel model-based correction method is proposed …