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1.

001-es BibID:BIBFORM070522
Első szerző:Béres Mónika (képalkotó diagnoszta, eü. mérnökinformatikus)
Cím:2D and 3D texture analysis to differentiate brain metastases on MR images : proceed with caution / Béresová Monika, Larroza Andrés, Arana Estanislao, Varga József, Balkay László, Moratal David
Dátum:2018
ISSN:0968-5243
Megjegyzések:ObjectiveTo find structural differences between brain metastases of lung and breast cancer, computing their heterogeneity parameters by means of both 2D and 3D texture analysis (TA).Materials and methodsPatients with 58 brain metastases from breast (26) and lung cancer (32) were examined by MR imaging. Brain lesions were manually delineated by 2D ROIs on the slices of contrast-enhanced T1-weighted (CET1) images, and local binary patterns (LBP) maps were created from each region. Histogram-based (minimum, maximum, mean, standard deviation, and variance), and co-occurrence matrix-based (contrast, correlation, energy, entropy, and homogeneity) 2D, weighted average of the 2D slices, and true 3D TA were obtained on the CET1 images and LBP maps.ResultsFor LBP maps and 2D TA contrast, correlation, energy, and homogeneity were identified as statistically different heterogeneity parameters (SDHPs) between lung and breast metastasis. The weighted 3D TA identified entropy as an additional SDHP. Only two texture indexes (TI) were significantly different with true 3D TA: entropy and energy. All these TIs discriminated between the two tumor types significantly by ROC analysis. For the CET1 images there was no SDHP at all by 3D TA.ConclusionOur results indicate that the used textural analysis methods may help with discriminating between brain metastases of different primary tumors.
Tárgyszavak:Orvostudományok Egészségtudományok idegen nyelvű folyóiratközlemény külföldi lapban
Computer-assisted
Image processing
Texture analysis
Magnetic resonance imaging
Brain neoplasms
Metastasis
Breast cancer
Lung cancer
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine. - 31 : 2 (2018), p. 285-294. -
További szerzők:Larroza, Andrés Arana, Estanislao Varga József (1955-) (fizikus) Balkay László (1963-) (biofizikus) Moratal, David
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2.

001-es BibID:BIBFORM033467
Első szerző:Grüne, Matthias
Cím:Quantitative T*(2) and T'(2) maps during reversible focal cerebral ischemia in rats : separation of blood oxygenation from nonsusceptibility-based contributions / Grüne M., van Dorsten F. A., Schwindt W., Oláh L., Hoehn M.
Dátum:2000
Megjegyzések:Quantitative imaging contrast is evaluated which allows the selective measurement of the blood oxygenation state during cerebral ischemia within a multiparametric imaging study on rats. In a first step, the ambiguities arising in T*(2)-weighted images due to T*(2) heterogeneity are eliminated by calculating T*(2) maps. Then, 1/T'(2) maps are calculated according to 1/T'(2) = 1/T*(2) - 1/T(2) to eliminate nonsusceptibility-induced changes of 1/T*(2) after the induction of stroke. This is of particular importance in the presence of vasogenic edema. The changes Delta(1/T'(2)) after the onset of ischemia selectively quantify the variations of the deoxyhemoglobin content during the development of the infarct. The presented results are not available from conventionally recorded parameters of a stroke study and, together with perfusion-weighted images, form a powerful combination to analyze the oxygen consumption and the metabolism of the tissue.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Magnetic Resonance in Medicine. - 42 : 6 (2000), p. 1027-1032. -
További szerzők:van Dorsten, Ferdi A. Schwindt, Wolfram Oláh László (1967-) (neurológus) Hoehn, Mathias
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3.

001-es BibID:BIBFORM051496
Első szerző:Jakab András (radiológus)
Cím:Graph theoretical analysis of brain network efficiency and centrality in autism spectrum disorders : a multi-center study / A. Jakab, T. Spisák, E. L. Berényi, M. Emri
Dátum:2013
ISSN:0968-5243
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
Megjelenés:Magnetic Resonance Materials in Physics Biology and Medicine. - 26 : S1 (2013), p. 337. -
További szerzők:Spisák Tamás (1986-) (programtervező matematikus, informatikus) Berényi Ervin (1964-) (radiológus) Emri Miklós (1962-) (fizikus)
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4.

001-es BibID:BIBFORM039398
Első szerző:Jakab András (radiológus)
Cím:Pathological patterns of functional and structural brain connectivity in high functioning autistic adults / Jakab A., Spisák T., Szeman-Nagy A., Dobrai D., Molnar P., Berényi E., Emri M.
Dátum:2012
ISSN:0968-5243
Megjegyzések:Purpose/Introduction: High level functioning autism (HLFA) is a distinctentity among autism spectrum disorders (ASD) characterized by autistic traitsunaccompanied by mental retardation. Our aim was to employ resting statefunctional MRI (r-fMRI) and diffusion tensor imaging (DTI) augmentedwith a graph theoretical approach to describe the pathological connectomein HLFA subjects.Subjects and Methods: Subjects were sampled from the a public dataset(n=209). Inclusion criteria for the HLFA group were adult age, elevated AutismSpectrum Questionaire (ASSQ) values and a marked discrepancy between theperformance IQ and verbal IQ measurements, 9 such subjects were found.Controls (n=40) with normal ASSQ values were age and gender matched tothis group while preserving the criteria of the IQ mismatch. Using the func-tional connectivity of r-fMRI data, individual graphs were created. For eachbrain region, network properties (strength, efficiency) were calculated. DTIwas used to determine the diffusion anisotropy in cortical, subcortical andmajor white matter regions.Results: Anisotropy patterns were characterized by significantly elevated valuespredominantly in frontal, temporal regions, gyrus cinguli and the thalamus.Graph analysis revealed reduced local efficiency and strength of the associ-ated networks with a pattern similar to DTI results. No differences in globalnetwork parameters were found.Discussion/Conclusion: A widely accepted hypothesis is that the autisticconnectome is dominated by a reduction of long-range cortico-cortical con-nections and an excessive presence of short fibers. We provided a comparisonof local attributes of structural and functional connectivity. The spatial distribution of the HLFA connectome phenotype is in accordance with previouslysuggested models.
Tárgyszavak:Orvostudományok Elméleti orvostudományok idézhető absztrakt
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine 25 : S1 (2012), p. 27. -
További szerzők:Spisák Tamás (1986-) (programtervező matematikus, informatikus) Szemán-Nagy Anita (1979-) (pszichológus, klinikai szakpszichológus) Dobrai Dániel Molnár Péter (1942-2022) (orvos, klinikai szakpszichológus, pszichoterapeuta) Berényi Ervin (1964-) (radiológus) Emri Miklós (1962-) (fizikus)
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5.

001-es BibID:BIBFORM024864
Első szerző:Jakab András
Cím:Handedness and interhemispheric differences in the anatomical connectivity of perisylvian language areas : a network-based approach / A. Jakab, M. Béres, T. Spisák, S. A. Kis, M. Emri, E. Berényi
Dátum:2011
ISSN:0968-5243 1352-8661
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine 24 : Suppl. 1 (2011), 276. p. -
További szerzők:Béres Mónika (1982-) (képalkotó diagnoszta, eü. mérnökinformatikus) Spisák Tamás (1986-) (programtervező matematikus, informatikus) Kis Sándor Attila (1973-) (fizikus) Emri Miklós (1962-) (fizikus) Berényi Ervin (1964-) (radiológus)
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6.

001-es BibID:BIBFORM051497
Első szerző:Spisák Tamás (programtervező matematikus, informatikus)
Cím:Lost in translation : voxel-wise confounding effects of motion in resting-state fMRI and whole brain connectivity analysis / T. Spisák, A. Jakab, G. Opposits, S. A. Kis, E. L. Berényi, M. Emri
Dátum:2013
ISSN:0968-5243
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine. - 26 : S1 (2013), p. 302-404. -
További szerzők:Jakab András (1985-) (radiológus) Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Berényi Ervin (1964-) (radiológus) Emri Miklós (1962-) (fizikus)
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7.

001-es BibID:BIBFORM039399
Első szerző:Spisák Tamás (programtervező matematikus, informatikus)
Cím:BrainMOD : 4-dimensional multimodal medical image analysis software / Tamás Spisák, Sándor Attila Kis, Gábor Opposits, Imre Lajtos, László Balkay, Miklós Emri
Dátum:2012
ISSN:0968-5243
Megjegyzések:Purpose of the softwareWithin the Central Nervous System Imaging project (http://www.eniac-csi.org/) of the ENIAC consortium, the need has emerged for a general multimodal visualization platform which facilitates the evaluation of data produced by new enhanced devices developed in the project. Taking advantage of multi-source post-processed data, this software aims to help interpreting complex intra-modal relationships. The modalities involved are PET, MRI, EEG, EIT.According to the project proposal, our purpose was to develop a software for interactive user-friendly 2D and 3D visualization of post-processed multi-modal medical imaging data. Important requirements were to manage dynamic image data and explicitly support the use of various enhanced brain imaging techniques.Methods / ImplementationThe input of the software are MR structural data, fMRI and PET dynamic data and activation maps (GLM, ICA), EEG/EIT based static functional maps and dynamic data, other EEG and fMRI related time series (eg. hemodynamic response functions, independent component analysis time courses), volumes-of-interests of segmentation data and EEG/EIT marker positions. Besides conventional 2D image fusion features, the software provides numerous ways to reveal intra-modal dynamic relationships. Volumes-of-interests can be delineated manually or automatically aided by various segmentation algorithms or brain atlases [1]. Time series curves can be generated from the image data and on these various operations can be performed (eg. resampling, filters, correlation, convolution).Three dimensional surfaces can be reconstructed, visualized and colored by multiple parameters (eg. dynamic functional information).The program is built upon the MultiModal Medical Imaging software library system (www.minipetct.com/m3i) and runs on Windows 7 and Windows Xp operation systems and various Linux distributions. The hardware requirements of the application match the current average PC configurations used in medical image analysis.The software system was implemented in C++.Features illustrated at the exhibitAt the exhibit the features of the software are illustrated by performing a comparsion analysis of EEG-fMRI activation maps vs. resected area and evaluating the overlap between fMRI parametric maps computed by Independent Component Analysis and standard resting-state network templates [2].References[1] T. Spisák, M. Koselák, G. Opposits, S. A. Kis, L. Trón, A. Jakab, E. Berényi, M. Emri, Region management toolkit for atlas-space image processing, MAGMA 24 (S1):543, 2011.[2] Shirer, WR and Ryali, S. and Rykhlevskaia, E. and Menon, V. and Greicius, MD,Decoding subject-driven cognitive states with whole-brain connectivity patterns, Cerebral Cortex, 22(1):158-162, 2012.
Tárgyszavak:Orvostudományok Elméleti orvostudományok idézhető absztrakt
multimodal
medical image processing
software
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine. - 25 : S1 (2012), p. 619. -
További szerzők:Kis Sándor Attila (1973-) (fizikus) Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Lajtos Imre (1986-) (fizikus) Balkay László (1963-) (biofizikus) Emri Miklós (1962-) (fizikus)
Pályázati támogatás:120209
FP7
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8.

001-es BibID:BIBFORM039400
Első szerző:Spisák Tamás (programtervező matematikus, informatikus)
Cím:BrainCON : software tool for graph theory based multimodal brain connectivity analysis and visualization / Tamás Spisák, Gábor Opposits, Sándor Attila Kis, Béla Clemens, Miklós Emri
Dátum:2012
ISSN:0968-5243
Megjegyzések:Purpose of the software: Graph theory based structural and functional brainconnectivity analysis is a novel method providing new insights into the dynam-ics and complexity of the brain by modeling it's regional interactions[1]. Dueto the heterogeneity and dynamic development of the applied mathematicalmodels and analysis techniques the software support of this field is still poorlyaccomplished[2].Our purpose was to develop a user friendly software system dedicated for theanalysis and visualization of multimodal brain connectivity data based onEEG, fMRI and DTI data.Methods/Implementation: The software system has modular architecturewhich provides the opportunity to rapidly follow the latest improvements ofconnectivity analysis and visualization methods by incremental development.Reconstruction of brain networks is modality dependent and can be performedwith various state-of-the-art software tools, eg. BrainLOC[3], Matlab and R forfMRI, FSL or Matlab softwares for DTI and NeuroGuide for EEG-LORETAdata. These software tools can be easily fitted into the processing pipeline of thesystem. The resulting connectivity matrices can be displayed and thresholdedinteractively. Various interchangeable components are present for global (eg.small-worldness), modular (eg. community detection, modularity scores)and nodal (eg. various hub-scores) analysis of binary and weighted graphs inboth individual and population level[4]. Cost-integration[5] technique wasimplemented to solve the problem of thresholding networks. Interpreting theresults is aided by real-time 2D and 3D "galss brain" visualization techniquesand various plots.The program is built upon the MultiModal Medical Imaging software librarysystem(www.minipetct.com/m3i) and runs on Windows 7 and Windows Xpoperation systems and various Linux distributions (www.minipetct.com/braincon). The hardware requirements of the application match the currentaverage PC configurations used in medical image analysis.The software system was implemented mainly in C++ and partly in R.Features illustrated at the exhibit: At the exhibit connectivity data analysisis demonstrated using variuos modalities.Different methods are evaluated on the same data, connectivity patterns andhub-scores corresponding to brain regions are visualized in 3D.References:[1] Sporns, O., The human connectome: a complex network, Annals of theNew York Academy of Sciences, 1224(1):109-125, 2011. [2] Leergaard et.al., Mapping the Connectome: Multi-Level Analysis of Brain Connectivity,Frontiers in Neuroinformatics, 6, 2012. [3] Spisák, T. et. al., Region manage-ment toolkit for atlas-space image processing, MAGMA 24 (S1):543, 2011.[4] Rubinov, et. al., Complex network measures of brain connectivity: usesand interpretations, Neuroimage, 52(3):1059-1069, 2010. [5] Ginestet et. al.,Brain network analysis: separating cost from topology using cost-integration,PloS1, 6(7):e21570, 2011.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
brain connectivity
graph theory
software
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine. - 25 : S1 (2012), p. 616. -
További szerzők:Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Clemens Béla (1950-) (neurológus) Emri Miklós (1962-) (fizikus)
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9.

001-es BibID:BIBFORM024836
Első szerző:Spisák Tamás (programtervező matematikus, informatikus)
Cím:Region management toolkit for atlas-space image processing / T. Spisák, M. Koselák, G. Opposits, S. A. Kis, L. Trón, A. Jakab, E. Berényi, M. Emri
Dátum:2011
ISSN:0968-5243 1352-8661
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
Megjelenés:Magnetic Resonance Materials In Physics Biology And Medicine 24 : Suppl. 1 (2011), p. 543-543. -
További szerzők:Koselák Mihály (1986-) (informatikus) Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Trón Lajos (1941-) (biofizikus) Jakab András (1985-) Berényi Ervin (1964-) (radiológus) Emri Miklós (1962-) (fizikus)
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10.

001-es BibID:BIBFORM033453
Első szerző:van Dorsten, Ferdi A.
Cím:Dynamic changes of ADC, perfusion, and NMR relaxation parameters in transient focal ischemia of rat brain / van Dorsten F. A., Oláh L., Schwindt W., Grüne M., Uhlenküken U., Pillekamp F., Hossmann K. A., Hoehn M.
Dátum:2002
ISSN:0740-3194
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Magnetic Resonance In Medicine. - 47 : 1 (2002), p. 97-104. -
További szerzők:Oláh László (1967-) (neurológus) Schwindt, Wolfram Grüne, Matthias Uhlenküken, U. Pillekamp, F. Hossmann, Konstantin-Alexander Hoehn, Mathias
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