Correlation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study.

Autor: Bastati N; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Perkonigg M; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Sobotka D; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Poetter-Lang S; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Fragner R; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Beer A; Department of Pathology, Medical University of Vienna, Vienna, Austria., Messner A; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Watzenboeck M; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Pochepnia S; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Kittinger J; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Herold A; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Kristic A; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Hodge JC; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria., Traussnig S; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria., Trauner M; Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria., Ba-Ssalamah A; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria. ahmed.ba-ssalamah@meduniwien.ac.at.; Department of Biomedical Imaging and Image-Guided Therapy, General Hospital of Vienna (AKH), Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria. ahmed.ba-ssalamah@meduniwien.ac.at., Langs G; Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.; Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.

Publikováno v: European radiology [Eur Radiol] 2023 Nov; Vol. 33 (11), pp. 7729-7743. Date of Electronic Publication: 2023 Jun 26.

CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation.

Autor: Kavur AE; Graduate School of Natural and Applied Sciences, Dokuz Eylul University, Izmir, Turkey., Gezer NS; Department of Radiology, Faculty Of Medicine, Dokuz Eylul University, Izmir, Turkey., Barış M; Department of Radiology, Faculty Of Medicine, Dokuz Eylul University, Izmir, Turkey., Aslan S; Ca' Foscari University of Venice, ECLT and DAIS, Venice, Italy; Ege University, International Computer Institute, Izmir, Turkey., Conze PH; IMT Atlantique, LaTIM UMR 1101, Brest, France., Groza V; Median Technologies, Valbonne, France., Pham DD; Intelligent Systems, Faculty of Engineering, University of Duisburg-Essen, Germany., Chatterjee S; Data and Knowledge Engineering Group, Otto von Guericke University, Magdeburg, Germany; Biomedical Magnetic Resonance, Otto von Guericke University Magdeburg, Germany., Ernst P; Data and Knowledge Engineering Group, Otto von Guericke University, Magdeburg, Germany., Özkan S; Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey., Baydar B; Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey., Lachinov D; Department of Ophthalmology and Optometry, Medical Uni. of Vienna, Austria., Han S; Johns Hopkins University, Baltimore, USA., Pauli J; Intelligent Systems, Faculty of Engineering, University of Duisburg-Essen, Germany., Isensee F; Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany., Perkonigg M; CIR Lab Dept of Biomedical Imaging and Image-guided Therapy Medical Uni. of Vienna, Austria., Sathish R; Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, India., Rajan R; School of Medical Science and Technology, Indian Institute of Technology, Kharagpur, India., Sheet D; Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, India., Dovletov G; Intelligent Systems, Faculty of Engineering, University of Duisburg-Essen, Germany., Speck O; Biomedical Magnetic Resonance, Otto von Guericke University Magdeburg, Germany., Nürnberger A; Data and Knowledge Engineering Group, Otto von Guericke University, Magdeburg, Germany., Maier-Hein KH; Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany., Bozdağı Akar G; Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey., Ünal G; Faculty of Computer and Informatics Engineering, İstanbul Technical University, İstanbul, Turkey., Dicle O; Department of Radiology, Faculty Of Medicine, Dokuz Eylul University, Izmir, Turkey., Selver MA; Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey. Electronic address: alper.selver@deu.edu.tr.

Publikováno v: Medical image analysis [Med Image Anal] 2021 Apr; Vol. 69, pp. 101950. Date of Electronic Publication: 2020 Dec 25.

[Machine learning in radiology : Terminology from individual timepoint to trajectory].

Autor: Langs G; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich. georg.langs@meduniwien.ac.at., Attenberger U; Universitätsklinik für Radiologie, Universitätsklinikum Bonn, Bonn, Deutschland., Licandro R; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich.; Computer Vision Lab, Institute of Visual Computing and Human-Centered Technology, Technische Universität Wien, Favoritenstrasse 9-11, Wien, Österreich., Hofmanninger J; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich., Perkonigg M; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich., Zusag M; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich., Röhrich S; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich., Sobotka D; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich., Prosch H; Universitätsklinik für Radiologie und Nuklearmedizin, Computational Imaging Research Lab, Medizinische Universität Wien, Währinger Gürtel 18-20, 1090, Wien, Österreich.

Publikováno v: Der Radiologe [Radiologe] 2020 Jan; Vol. 60 (1), pp. 6-14.

New improved model for joint segmentation and registration of multi-modality images: application to medical images.

Autor: Badshah, Noor¹ (AUTHOR) noorbadshah@uetpeshawar.edu.pk, Begum, Nasra¹ (AUTHOR), Rada, Lavdie² (AUTHOR), Ashfaq, Muniba³ (AUTHOR), Atta, Hadia⁴ (AUTHOR)

Publikováno v: Journal of Intelligent & Fuzzy Systems. 2024, Vol. 46 Issue 4, p8755-8770. 16p.

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