Literature DB >> 18029143

CT-perfusion imaging of the human brain: advanced deconvolution analysis using circulant singular value decomposition.

H J Wittsack1, A M Wohlschläger, E K Ritzl, R Kleiser, M Cohnen, R J Seitz, U Mödder.   

Abstract

According to indicator dilution theory tissue time-concentration curves have to be deconvolved with arterial input curves in order to get valid perfusion results. Our aim was to adapt and validate a deconvolution method originating from magnetic resonance techniques and apply it to the calculation of dynamic contrast enhanced computed tomography perfusion imaging. The application of a block-circulant matrix approach for singular value decomposition renders the analysis independent of tracer arrival time to improve the results.

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Year:  2008        PMID： 18029143     DOI： 10.1016/j.compmedimag.2007.09.004

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN： 0895-6111            Impact factor:   4.790


  14 in total

1.  Pre-and postoperative cerebral blood flow changes in patients with idiopathic normal pressure hydrocephalus measured by computed tomography (CT)-perfusion.

Authors:  Doerthe Ziegelitz; Jonathan Arvidsson; Per Hellström; Mats Tullberg; Carsten Wikkelsø; Göran Starck
Journal:  J Cereb Blood Flow Metab       Date:  2015-10-14       Impact factor: 6.200

2.  Long-term impact of perfusion CT data after subarachnoid hemorrhage.

Authors:  Christian Mathys; Daniel Martens; Dorothea C Reichelt; Julian Caspers; Joel Aissa; Rebecca May; Daniel Hänggi; Gerald Antoch; Bernd Turowski
Journal:  Neuroradiology       Date:  2013-09-13       Impact factor: 2.804

3.  Tissue-specific sparse deconvolution for low-dose CT perfusion.

Authors:  Ruogu Fang; Tsuhan Chen; Pina C Sanelli
Journal:  Med Image Comput Comput Assist Interv       Date:  2013

4.  Prediction of outcome after aneurysmal subarachnoid haemorrhage using data from patient admission.

Authors:  Christian Rubbert; Kaustubh R Patil; Kerim Beseoglu; Christian Mathys; Rebecca May; Marius G Kaschner; Benjamin Sigl; Nikolas A Teichert; Johannes Boos; Bernd Turowski; Julian Caspers
Journal:  Eur Radiol       Date:  2018-06-12       Impact factor: 5.315

5.  Towards robust deconvolution of low-dose perfusion CT: sparse perfusion deconvolution using online dictionary learning.

Authors:  Ruogu Fang; Tsuhan Chen; Pina C Sanelli
Journal:  Med Image Anal       Date:  2013-03-07       Impact factor: 8.545

6.  Using quantitative CT perfusion for evaluation of delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage.

Authors:  P C Sanelli; I Ugorec; C E Johnson; J Tan; A Z Segal; M Fink; L A Heier; A J Tsiouris; J P Comunale; M John; P E Stieg; R D Zimmerman; A I Mushlin
Journal:  AJNR Am J Neuroradiol       Date:  2011-09-29       Impact factor: 3.825

7.  The extent of the perihemorrhagic perfusion zone correlates with hematoma volume in patients with lobar intracerebral hemorrhage.

Authors:  Kerim Beseoglu; Nima Etminan; Bernd Turowski; Hans-Jakob Steiger; Daniel Hänggi
Journal:  Neuroradiology       Date:  2014-04-29       Impact factor: 2.804

8.  Sparsity-based deconvolution of low-dose perfusion CT using learned dictionaries.

Authors:  Ruogu Fang; Tsuhan Chen; Pina C Sanelli
Journal:  Med Image Comput Comput Assist Interv       Date:  2012

9.  Statistical properties of cerebral CT perfusion imaging systems. Part II. Deconvolution-based systems.

Authors:  Ke Li; Guang-Hong Chen
Journal:  Med Phys       Date:  2019-09-23       Impact factor: 4.071

10.  Biased visualization of hypoperfused tissue by computed tomography due to short imaging duration: improved classification by image down-sampling and vascular models.

Authors:  Irene Klærke Mikkelsen; P Simon Jones; Lars Riisgaard Ribe; Josef Alawneh; Josep Puig; Susanne Lise Bekke; Anna Tietze; Jonathan H Gillard; Elisabeth A Warburton; Salva Pedraza; Jean-Claude Baron; Leif Østergaard; Kim Mouridsen
Journal:  Eur Radiol       Date:  2015-04-17       Impact factor: 5.315
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