Literature DB >> 10576724

Comparison of automated and visual texture analysis in MRI: characterization of normal and diseased skeletal muscle.

S Herlidou1, Y Rolland, J Y Bansard, E Le Rumeur, J D de Certaines.   

Abstract

Automated magnetic resonance imaging (MRI) texture analysis was compared with visual MRI analysis for the diagnosis of skeletal muscle dystrophy in 14 healthy and 17 diseased subjects. MRI texture analysis was performed on 8 muscle regions of interest (ROI) using four statistical methods (histogram, co-occurrence matrix, gradient matrix, runlength matrix) and one structural (mathematical morphology) method. Nine senior radiologists assessed full leg transverse slice images and proposed a diagnosis. The 59 extracted texture parameters for each ROI were statistically analyzed by Correspondence Factorial Analysis. Non-parametric tests were used to compare diagnoses based on automated texture analysis and visual analysis. Texture analysis methods discriminated between healthy volunteers and patients with a sensitivity of 70%, and a specificity of 86%. Comparison with visual analysis of MR images suggests that texture analysis can provide useful information contributing to the diagnosis of skeletal muscle disease.

Entities:  

Mesh:

Year:  1999        PMID: 10576724     DOI: 10.1016/s0730-725x(99)00066-1

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  19 in total

1.  Texture analysis improves level set segmentation of the anterior abdominal wall.

Authors:  Zhoubing Xu; Wade M Allen; Rebeccah B Baucom; Benjamin K Poulose; Bennett A Landman
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

2.  A computerized MRI biomarker quantification scheme for a canine model of Duchenne muscular dystrophy.

Authors:  Jiahui Wang; Zheng Fan; Krista Vandenborne; Glenn Walter; Yael Shiloh-Malawsky; Hongyu An; Joe N Kornegay; Martin A Styner
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-01-09       Impact factor: 2.924

3.  A texture analysis method for MR images of airway dilator muscles: a feasibility study.

Authors:  P Kölhi; J Järnstedt; M Sikiö; J Viik; P Dastidar; T Peltomäki; H Eskola
Journal:  Dentomaxillofac Radiol       Date:  2014-04-29       Impact factor: 2.419

4.  Gestational and lactational exposure to dichlorinated bisphenol A induces early alterations of hepatic lipid composition in mice.

Authors:  Dounia El Hamrani; Amandine Chepied; William Même; Marc Mesnil; Norah Defamie; Sandra Même
Journal:  MAGMA       Date:  2018-02-20       Impact factor: 2.310

5.  Role of quantitative computed tomography texture analysis in the differentiation of primary lung cancer and granulomatous nodules.

Authors:  Carole Dennie; Rebecca Thornhill; Vineeta Sethi-Virmani; Carolina A Souza; Hamid Bayanati; Ashish Gupta; Donna Maziak
Journal:  Quant Imaging Med Surg       Date:  2016-02

6.  Real-time texture analysis for identifying optimum microbubble concentration in 2-D ultrasonic particle image velocimetry.

Authors:  Lili Niu; Ming Qian; Liang Yan; Wentao Yu; Bo Jiang; Qiaofeng Jin; Yanping Wang; Robin Shandas; Xin Liu; Hairong Zheng
Journal:  Ultrasound Med Biol       Date:  2011-06-17       Impact factor: 2.998

7.  Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 Tesla endorectal, in vivo T2-weighted MR imagery.

Authors:  Satish E Viswanath; Nicholas B Bloch; Jonathan C Chappelow; Robert Toth; Neil M Rofsky; Elizabeth M Genega; Robert E Lenkinski; Anant Madabhushi
Journal:  J Magn Reson Imaging       Date:  2012-02-15       Impact factor: 4.813

8.  Texture analysis using T1-weighted images for muscles in Charcot-Marie-Tooth disease patients and volunteers.

Authors:  Ji Hyun Lee; Young Cheol Yoon; Hyun Su Kim; Jae-Hun Kim; Byung-Ok Choi
Journal:  Eur Radiol       Date:  2020-10-30       Impact factor: 5.315

9.  Characteristics of magnetic resonance imaging biomarkers in a natural history study of golden retriever muscular dystrophy.

Authors:  Zheng Fan; Jiahui Wang; Mihye Ahn; Yael Shiloh-Malawsky; Nizar Chahin; Sandra Elmore; C Robert Bagnell; Kathy Wilber; Hongyu An; Weili Lin; Hongtu Zhu; Martin Styner; Joe N Kornegay
Journal:  Neuromuscul Disord       Date:  2013-10-30       Impact factor: 4.296

10.  Non-Hodgkin lymphoma response evaluation with MRI texture classification.

Authors:  Lara C V Harrison; Tiina Luukkaala; Hannu Pertovaara; Tuomas O Saarinen; Tomi T Heinonen; Ritva Järvenpää; Seppo Soimakallio; Pirkko-Liisa I Kellokumpu-Lehtinen; Hannu J Eskola; Prasun Dastidar
Journal:  J Exp Clin Cancer Res       Date:  2009-06-22
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