Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction

Autor: Mark Selles, Ruud H. H. Wellenberg, Derk J. Slotman, Ingrid M. Nijholt, Jochen A. C. van Osch, Kees F. van Dijke, Mario Maas, Martijn F. Boomsma

Publikováno v: European Radiology Experimental, Vol 8, Iss 1, Pp 1-11 (2024)

Abstract Background To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to

Externí odkaz: https://doaj.org/article/b7fb379f726a41a4b3351c1a0dbe1821

Diffusion-weighted MRI with deep learning for visualizing treatment results of MR-guided HIFU ablation of uterine fibroids

Autor: Derk J, Slotman, Lambertus W, Bartels, Aylene, Zijlstra, Inez M, Verpalen, Jochen A C, van Osch, Ingrid M, Nijholt, Edwin, Heijman, Miranda, van 't Veer-Ten Kate, Erwin, de Boer, Rolf D, van den Hoed, Martijn, Froeling, Martijn F, Boomsma

Publikováno v: European radiology.

No method is available to determine the non-perfused volume (NPV) repeatedly during magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) ablations of uterine fibroids, as repeated acquisition of contrast-enhanced T1-weighted (CE-T1w)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::9b072145f13500b966d4132c228ea69b
https://pubmed.ncbi.nlm.nih.gov/36472702

Bone visualization of the cervical spine with deep learning-based synthetic CT compared to conventional CT: A single-center noninferiority study on image quality

Autor: Brigitta Britt Y M, van der Kolk, Derk J Jorik, Slotman, Ingrid M, Nijholt, Jochen A C, van Osch, Tess J, Snoeijink, Martin, Podlogar, Boudewijn A A M, van Hasselt, Henk J, Boelhouwers, Marijn, van Stralen, Peter R, Seevinck, Niels W L, Schep, Mario, Maas, Martijn F, Boomsma

Publikováno v: European Journal of Radiology, 154:110414. Elsevier Ireland Ltd
van der Kolk, B Y M, Slotman, D J, Nijholt, I M, van Osch, J A C, Snoeijink, T J, Podlogar, M, van Hasselt, B A A M, Boelhouwers, H J, van Stralen, M, Seevinck, P R, Schep, N W L, Maas, M & Boomsma, M F 2022, ' Bone visualization of the cervical spine with deep learning-based synthetic CT compared to conventional CT : A single-center noninferiority study on image quality ', European Journal of Radiology, vol. 154, 110414 . https://doi.org/10.1016/j.ejrad.2022.110414

Purpose: To investigate whether the image quality of a specific deep learning-based synthetic CT (sCT) of the cervical spine is noninferior to conventional CT. Method: Paired MRI and CT data were collected from 25 consecutive participants (≥ 50 yea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9ff91100dd1a561d14daa4ce4f39bad
https://doi.org/10.1016/j.ejrad.2022.110414

Comparison of maximal Rubidium-82 activities for myocardial blood flow quantification between digital and conventional PET systems

Autor: Joris D. van Dijk, Jochen A. C. van Osch, Pieter L. Jager, Jorn A. van Dalen, Maryam Khodaverdi

Publikováno v: J Nucl Cardiol

PET-based myocardial blood flow (MBF) quantification can be inaccurate when using high tracer activities. Our aim was to derive the maximal Rubidium-82 activity for MBF assessment using a new digital PET system and compare the results with convention

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20580d16061dd211c12b2b182a49a33e
https://doi.org/10.1007/s12350-017-1156-9

Variation in Maximum Counting Rates During Myocardial Blood Flow Quantification Using

Autor: Joris D, van Dijk, Pieter L, Jager, Jochen A C, van Osch, Jorn A, van Dalen

Publikováno v: Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 58(3)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::4330d6601141b190ab2215918f19ff2e
https://pubmed.ncbi.nlm.nih.gov/28126892