Zobrazeno 1 - 10
of 117
pro vyhledávání: '"M. Fabel"'
Publikováno v:
Insights into Imaging, Vol 3, Iss 4, Pp 355-371 (2012)
Abstract Background Among the modalities for lung imaging, proton magnetic resonance imaging (MRI) has been the latest to be introduced into clinical practice. Its value to replace X-ray and computed tomography (CT) when radiation exposure or iodinat
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https://doaj.org/article/a6698d8f4fa94ba394ab642873210d4d
Akademický článek
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Autor:
Volker Dicken, J. Weßling, Rolf M. Mesters, Andreas Kießling, Melvin D'Anastasi, Anno Graser, R. Koch, M. Karpitschka, A. Wulff, A. J. Höink, N. Kohlhase, Boris Buerke, D Pinto dos Santos, L. Bornemann, Walter Heindel, L. Wassenaar, Christoph Schülke, M Fabel
Publikováno v:
European Radiology. 24:2709-2718
Multicentre evaluation of the precision of semi-automatic 2D/3D measurements in comparison to manual, linear measurements of lymph nodes regarding their inter-observer variability in multi-slice CT (MSCT) of patients with lymphoma. MSCT data of 63 pa
Autor:
Hans U. Kauczor, C. Hintze, Monika Eichinger, Julien Dinkel, Omid Khalilzadeh, M Fabel, Jürgen Biederer, Michael Thomas, Heinz Peter Schlemmer, M. Thorn, M. Puderbach, Claus Peter Heussel
Publikováno v:
Lung Cancer. 82:76-82
Therapy monitoring in oncologic patient requires precise measurement methods. In order to improve the precision of measurements, we used a semi-automated generic segmentation algorithm to measure the size of large lung cancer tumors. The reproducibil
Autor:
Hendrik Bolte, J.P. Schäfer, M. Tepper, A Wulff, Sandra Freitag-Wolf, Olav Jansen, H.M. Knabe, M. Fabel
Publikováno v:
European Journal of Radiology. 82:e567-e573
To examine technical parameters of measurement accuracy and differences in tumor response classification using RECIST 1.1 and volumetric assessment in three common metastasis types (lung nodules, liver lesions, lymph node metastasis) simultaneously.5
Autor:
E. J. R. Van Beek, Meinrad Beer, M. Fabel, W. Hirsch, Jürgen Biederer, Jim M. Wild, Michael Puderbach
Publikováno v:
Insights into Imaging
Biederer, J, Beer, M, Hirsch, W, Wild, J, Fabel, M, Puderbach, M & van Beek, E 2012, ' MRI of the lung (2/3). Why … when … how? ', Insights into Imaging, vol. 3, no. 4, pp. 355-371 . https://doi.org/10.1007/s13244-011-0146-8
Biederer, J, Beer, M, Hirsch, W, Wild, J, Fabel, M, Puderbach, M & van Beek, E 2012, ' MRI of the lung (2/3). Why … when … how? ', Insights into Imaging, vol. 3, no. 4, pp. 355-371 . https://doi.org/10.1007/s13244-011-0146-8
Background Among the modalities for lung imaging, proton magnetic resonance imaging (MRI) has been the latest to be introduced into clinical practice. Its value to replace X-ray and computed tomography (CT) when radiation exposure or iodinated contra
Autor:
Thorsten A. Bley, Wolfgang L. Gross, Elena Csernok, Marcus Both, Frank Oliver Henes, Kristine Herrmann, F Moosig, Y Chen, M Fabel
Publikováno v:
Annals of the Rheumatic Diseases. 70:1926-1929
To investigate the correlation of serum levels of high mobility group box 1 (HMGB1) with the extent of granulomatous inflammation in granulomatosis with polyangiitis (GPA).From 169 patients with GPA, 17 patients with granulomatous inflammation, witho
Publikováno v:
Der Pneumologe. 8:234-242
Mehr als jede andere Modalitat im Spektrum der radiologischen Lungendiagnostik verbindet die Magnetresonanztomographie (MRT) morphologische und funktionelle Aspekte in einer Untersuchung. Fur den praktischen Einsatz stehen angepasste Untersuchungspro
Publikováno v:
Der Radiologe. 49:705-711
Parallele Bildgebung und „echo sharing“ haben die Akquisitionszeiten der MRT fur grose Volumina deutlich reduziert. Dynamische zwei- und dreidimensionale Abbildungen des gesamten Thorax mit hoher zeitlicher Auflosung (bis 10 Einzelbilder/s bzw. 2
Autor:
L. Bornemann, M. Hittinger, M. Pusken, Jan Hendrik Moltz, H. O. Peitgen, Jan-Martin Kuhnigk, Andreas Kiessling, E. Peitgen, Hendrik Bolte, H. C. Bauknecht, S. Meier, M Fabel, Volker Dicken
Publikováno v:
IEEE Journal of Selected Topics in Signal Processing. 3:122-134
This article presents advanced algorithms for segmenting lung nodules, liver metastases, and enlarged lymph nodes in CT scans. Segmentation and volumetry are essential tasks of a software assistant for oncological therapy monitoring. Our methods are