Literature DB >> 21985903

Efficient detection of cerebral microbleeds on 7.0 T MR images using the radial symmetry transform.

Hugo J Kuijf1, Jeroen de Bresser, Mirjam I Geerlings, Mandy M A Conijn, Max A Viergever, Geert Jan Biessels, Koen L Vincken.   

Abstract

Cerebral microbleeds (CMBs) are commonly detected on MRI and have recently received an increased interest, because they are associated with vascular disease and dementia. Identification and rating of CMBs on MRI images may be facilitated by semi-automatic detection, particularly on high-resolution images acquired at high field strength. For these images, visual rating is time-consuming and has limited reproducibility. We present the radial symmetry transform (RST) as an efficient method for semi-automated CMB detection on 7.0 T MR images, with a high sensitivity and a low number of false positives that have to be censored manually. The RST was computed on both echoes of a dual-echo T2*-weighted gradient echo 7.0 T MR sequence in 18 participants from the Second Manifestations of ARTerial disease (SMART) study. Potential CMBs were identified by combining the output of the transform on both echoes. Each potential CMB identified through the RST was visually checked by two raters to identify probable CMBs. The scoring time needed to manually reject false positives was recorded. The sensitivity of 71.2% is higher than that of individual human raters on 7.0 T scans and the required human rater time is reduced from 30 to 2 minutes per scan on average. The RST outperforms published semi-automated methods in terms of either a higher sensitivity or less false positives, and requires much less human rater time.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21985903     DOI: 10.1016/j.neuroimage.2011.09.061

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  23 in total

1.  Visual cerebral microbleed detection on 7T MR imaging: reliability and effects of image processing.

Authors:  J de Bresser; M Brundel; M M Conijn; J J van Dillen; M I Geerlings; M A Viergever; P R Luijten; G J Biessels
Journal:  AJNR Am J Neuroradiol       Date:  2012-02-16       Impact factor: 3.825

2.  Automated segmentation of chronic stroke lesions using LINDA: Lesion identification with neighborhood data analysis.

Authors:  Dorian Pustina; H Branch Coslett; Peter E Turkeltaub; Nicholas Tustison; Myrna F Schwartz; Brian Avants
Journal:  Hum Brain Mapp       Date:  2016-01-12       Impact factor: 5.038

3.  Toward Automatic Detection of Radiation-Induced Cerebral Microbleeds Using a 3D Deep Residual Network.

Authors:  Yicheng Chen; Javier E Villanueva-Meyer; Melanie A Morrison; Janine M Lupo
Journal:  J Digit Imaging       Date:  2019-10       Impact factor: 4.056

4.  Tracking of cell nuclei for assessment of in vitro uptake kinetics in ultrasound-mediated drug delivery using fibered confocal fluorescence microscopy.

Authors:  Marc Derieppe; Baudouin Denis de Senneville; Hugo Kuijf; Chrit Moonen; Clemens Bos
Journal:  Mol Imaging Biol       Date:  2014-10       Impact factor: 3.488

5.  Automated algorithm for counting microbleeds in patients with familial cerebral cavernous malformations.

Authors:  Xiaowei Zou; Blaine L Hart; Marc Mabray; Mary R Bartlett; Wei Bian; Jeffrey Nelson; Leslie A Morrison; Charles E McCulloch; Christopher P Hess; Janine M Lupo; Helen Kim
Journal:  Neuroradiology       Date:  2017-05-22       Impact factor: 2.804

Review 6.  Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease.

Authors:  François De Guio; Eric Jouvent; Geert Jan Biessels; Sandra E Black; Carol Brayne; Christopher Chen; Charlotte Cordonnier; Frank-Eric De Leeuw; Martin Dichgans; Fergus Doubal; Marco Duering; Carole Dufouil; Emrah Duzel; Franz Fazekas; Vladimir Hachinski; M Arfan Ikram; Jennifer Linn; Paul M Matthews; Bernard Mazoyer; Vincent Mok; Bo Norrving; John T O'Brien; Leonardo Pantoni; Stefan Ropele; Perminder Sachdev; Reinhold Schmidt; Sudha Seshadri; Eric E Smith; Luciano A Sposato; Blossom Stephan; Richard H Swartz; Christophe Tzourio; Mark van Buchem; Aad van der Lugt; Robert van Oostenbrugge; Meike W Vernooij; Anand Viswanathan; David Werring; Frank Wollenweber; Joanna M Wardlaw; Hugues Chabriat
Journal:  J Cereb Blood Flow Metab       Date:  2016-05-11       Impact factor: 6.200

Review 7.  Neuropathology of Vascular Brain Health: Insights From Ex Vivo Magnetic Resonance Imaging-Histopathology Studies in Cerebral Small Vessel Disease.

Authors:  Susanne J van Veluw; Konstantinos Arfanakis; Julie A Schneider
Journal:  Stroke       Date:  2022-01-10       Impact factor: 7.914

8.  Determination of detection sensitivity for cerebral microbleeds using susceptibility-weighted imaging.

Authors:  Sagar Buch; Yu-Chung N Cheng; Jiani Hu; Saifeng Liu; John Beaver; Rajasimhan Rajagovindan; E Mark Haacke
Journal:  NMR Biomed       Date:  2016-05-20       Impact factor: 4.044

9.  Perivascular spaces on 7 Tesla brain MRI are related to markers of small vessel disease but not to age or cardiovascular risk factors.

Authors:  Willem H Bouvy; Jaco J M Zwanenburg; Rik Reinink; Laura E M Wisse; Peter R Luijten; L Jaap Kappelle; Mirjam I Geerlings; Geert Jan Biessels
Journal:  J Cereb Blood Flow Metab       Date:  2016-05-06       Impact factor: 6.200

10.  DEEPMIR: a deep neural network for differential detection of cerebral microbleeds and iron deposits in MRI.

Authors:  Tanweer Rashid; Ahmed Abdulkadir; Ilya M Nasrallah; Jeffrey B Ware; Hangfan Liu; Pascal Spincemaille; J Rafael Romero; R Nick Bryan; Susan R Heckbert; Mohamad Habes
Journal:  Sci Rep       Date:  2021-07-08       Impact factor: 4.379

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