Brain MRI tissue classification based on local Markov random fields.

Magnetic Resonance Imaging
Jussi TohkaArthur W Toga

Abstract

A new method for tissue classification of brain magnetic resonance images (MRI) of the brain is proposed. The method is based on local image models where each models the image content in a subset of the image domain. With this local modeling approach, the assumption that tissue types have the same characteristics over the brain needs not to be evoked. This is important because tissue type characteristics, such as T1 and T2 relaxation times and proton density, vary across the individual brain and the proposed method offers improved protection against intensity non-uniformity artifacts that can hamper automatic tissue classification methods in brain MRI. A framework in which local models for tissue intensities and Markov Random Field (MRF) priors are combined into a global probabilistic image model is introduced. This global model will be an inhomogeneous MRF and it can be solved by standard algorithms such as iterative conditional modes. The division of the whole image domain into local brain regions possibly having different intensity statistics is realized via sub-volume probabilistic atlases. Finally, the parameters for the local intensity models are obtained without supervision by maximizing the weighted likelihood of a cert...Continue Reading

References

Dec 1, 1995·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·H Gudbjartsson, S Patz
Apr 1, 1997·IEEE Transactions on Medical Imaging·J C RajapakseJ L Rapoport
Jun 9, 1998·IEEE Transactions on Medical Imaging·J G SledA C Evans
Sep 15, 1998·IEEE Transactions on Medical Imaging·D L CollinsA C Evans
May 8, 1999·Journal of Magnetic Resonance Imaging : JMRI·J P WansapuraW S Ball
Aug 27, 1999·IEEE Transactions on Medical Imaging·C XuJ L Prince
Jan 11, 2000·IEEE Transactions on Medical Imaging·K Van LeemputP Suetens
Jan 11, 2000·IEEE Transactions on Medical Imaging·K Van LeemputP Suetens
Jan 11, 2000·IEEE Transactions on Medical Imaging·X ZengJ S Duncan
Jan 29, 2002·IEEE Transactions on Medical Imaging·B LikarF Pernus
Dec 11, 2002·IEEE Transactions on Medical Imaging·J L MarroquinA Fernandez-Bouzas
Dec 9, 2003·Journal of Neuroscience Methods·Umberto AmatoBruno Alfano
Oct 27, 2004·NeuroImage·Bruce FischlAnders M Dale
Jun 16, 2005·NeuroImage·John Ashburner, Karl J Friston
Nov 26, 2005·Medical Image Analysis·Boubakeur BelaroussiHugues Benoit-Cattin
Feb 10, 2006·NeuroImage·Kilian M PohlWilliam M Wells
Aug 22, 2006·Medical Image Analysis·Suyash P AwateRoss T Whitaker
Sep 14, 2006·IEEE Transactions on Medical Imaging·Hayit GreenspanJacob Goldberger
Mar 16, 2007·IEEE Transactions on Medical Imaging·Uros VovkBostjan Likar
May 1, 2007·Medical Image Analysis·José V ManjónMontserrat Robles
May 24, 2007·IEEE Transactions on Medical Imaging·Jussi TohkaArthur W Toga
Jan 1, 1995·IEEE Transactions on Medical Imaging·M KamberA C Evans
Jan 1, 1996·IEEE Transactions on Medical Imaging·W M WellsF A Jolesz
Jan 1, 1991·IEEE Transactions on Medical Imaging·H S ChoiY Kim
Jan 1, 1995·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·P Santago, H D Gage
Apr 19, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Richard SzeliskiCarsten Rother
Jun 1, 1984·IEEE Transactions on Pattern Analysis and Machine Intelligence·S Geman, D Geman

❮ Previous
Next ❯

Citations

Aug 27, 2013·Brain Imaging and Behavior·Ivo D DinovUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Nov 26, 2015·Magnetic Resonance Imaging·Fabio BaseliceVito Pascazio
Oct 3, 2015·NeuroImage·Alfiia GalimzianovaŽiga Špiclin
Jun 12, 2014·IEEE Transactions on Medical Imaging·S RibesO Caselles
Aug 24, 2011·IEEE Transactions on Medical Imaging·Thanh Minh Nguyen, Q M Jonathan Wu
Jan 25, 2014·Journal of Magnetic Resonance Imaging : JMRI·Sergi ValverdeXavier Lladó
Nov 16, 2010·NeuroImage·Carl LedermanJohn Darrell Van Horn
Jun 23, 2016·Journal of Neuroscience Methods·Sérgio PereiraCarlos A Silva
Jul 15, 2015·Journal of Medical Imaging·Nishant VermaMia K Markey
May 28, 2019·BMC Medical Imaging·Monan WangFengjie Liu
Oct 12, 2020·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Mahsa Dadar, D Louis Collins
Sep 22, 2018·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Junjie BaiXiaodong Wu

❮ Previous
Next ❯

Related Concepts

Trending Feeds

COVID-19

Coronaviruses encompass a large family of viruses that cause the common cold as well as more serious diseases, such as the ongoing outbreak of coronavirus disease 2019 (COVID-19; formally known as 2019-nCoV). Coronaviruses can spread from animals to humans; symptoms include fever, cough, shortness of breath, and breathing difficulties; in more severe cases, infection can lead to death. This feed covers recent research on COVID-19.

Blastomycosis

Blastomycosis fungal infections spread through inhaling Blastomyces dermatitidis spores. Discover the latest research on blastomycosis fungal infections here.

Nuclear Pore Complex in ALS/FTD

Alterations in nucleocytoplasmic transport, controlled by the nuclear pore complex, may be involved in the pathomechanism underlying multiple neurodegenerative diseases including Amyotrophic Lateral Sclerosis and Frontotemporal Dementia. Here is the latest research on the nuclear pore complex in ALS and FTD.

Applications of Molecular Barcoding

The concept of molecular barcoding is that each original DNA or RNA molecule is attached to a unique sequence barcode. Sequence reads having different barcodes represent different original molecules, while sequence reads having the same barcode are results of PCR duplication from one original molecule. Discover the latest research on molecular barcoding here.

Chronic Fatigue Syndrome

Chronic fatigue syndrome is a disease characterized by unexplained disabling fatigue; the pathology of which is incompletely understood. Discover the latest research on chronic fatigue syndrome here.

Evolution of Pluripotency

Pluripotency refers to the ability of a cell to develop into three primary germ cell layers of the embryo. This feed focuses on the mechanisms that underlie the evolution of pluripotency. Here is the latest research.

Position Effect Variegation

Position Effect Variagation occurs when a gene is inactivated due to its positioning near heterochromatic regions within a chromosome. Discover the latest research on Position Effect Variagation here.

STING Receptor Agonists

Stimulator of IFN genes (STING) are a group of transmembrane proteins that are involved in the induction of type I interferon that is important in the innate immune response. The stimulation of STING has been an active area of research in the treatment of cancer and infectious diseases. Here is the latest research on STING receptor agonists.

Microbicide

Microbicides are products that can be applied to vaginal or rectal mucosal surfaces with the goal of preventing, or at least significantly reducing, the transmission of sexually transmitted infections. Here is the latest research on microbicides.