J
Johan M. Thijssen
Researcher at Radboud University Nijmegen
Publications - 149
Citations - 3814
Johan M. Thijssen is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Image segmentation & Segmentation. The author has an hindex of 36, co-authored 148 publications receiving 3640 citations. Previous affiliations of Johan M. Thijssen include Radboud University Nijmegen Medical Centre & Boston Children's Hospital.
Papers
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Performance evaluation of methods for two-dimensional displacement and strain estimation using ultrasound radio frequency data.
Richard G.P. Lopata,Maartje M. Nillesen,Hendrik H.G. Hansen,I. H. Gerrits,Johan M. Thijssen,Chris L. de Korte +5 more
TL;DR: A coarse-to-fine approach is favored using RF data on a fine scale, using envelope data for window sizes exceeding the theoretical upper bound for strain estimation and the use of 2D parabolic interpolation to obtain subsample displacement estimates.
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Texture of B-mode echograms: 3-D simulations and experiments of the effects of diffraction and scatterer density.
TL;DR: In this article, B-mode echograms were simulated by employing the impulse response method in transmission and reception using a discrete scatterer tissue model, with and without attenuation.
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Ultrasonic speckle formation, analysis and processing applied to tissue characterization
TL;DR: The effects of spatial, fixed and adaptive, filtering, as well as, of grey scale encoding on the detection of lesions are analytically described and illustrated with representative images.
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Ultrasound attenuation and texture analysis of diffuse liver disease methods and preliminary results
TL;DR: The mutual correlations between the estimated parameters were used to preselect parameters contributing independent information, and which can subsequently be used in a discriminant analysis to differentiate between the various diseased conditions.
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Objective performance testing and quality assurance of medical ultrasound equipment.
TL;DR: A test protocol that contains the minimum set of performance measurements for predicting the clinical performance of ultrasound equipment and that is based on objective assessments by computerized image analysis is developed.