Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma.

Autor: Ter Maat LS; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., De Mooij RAJ; Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., Van Duin IAJ; Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Verhoeff JJC; Department of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Elias SG; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Leiner T; Department of Radiology, Mayo Clinical, Rochester, MN, USA., van Amsterdam WAC; Department of Data Science and Biostatistics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Troenokarso MF; Utrecht University, Utrecht, The Netherlands., Arntz ERAN; Utrecht University, Utrecht, The Netherlands., Van den Berkmortel FWPJ; Department of Medical Oncology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands., Boers-Sonderen MJ; Department of Medical Oncology, Radboudumc, Radboud University, Nijmegen, The Netherlands., Boomsma MF; Department of Radiology, Isala Zwolle, Zwolle, The Netherlands., Van den Eertwegh FJM; Department of Medical Oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Boelelaan 1117, Amsterdam, The Netherlands., de Groot JW; Isala Oncology Center, Isala Zwolle, Zwolle, The Netherlands., Hospers GAP; Department of Medical Oncology, UMC Groningen, University of Groningen, Groningen, The Netherlands., Piersma D; Department of Medical Oncology, Medisch Spectrum Twente, Enschede, The Netherlands., Vreugdenhil A; Department of Medical Oncology, Maxima Medical Center, Veldhoven, The Netherlands., Westgeest HM; Department of Internal Medicine, Amphia Hospital, Breda, The Netherlands., Kapiteijn E; Department of Medical Oncology, Leiden University Medical Center, Leiden University, Leiden, The Netherlands., De Wit AA; Department of Public Health, Healthcare Innovation and Evaluation and Medical Humanities, Julius Center Research Program Methodology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Blokx WAM; Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Van Diest PJ; Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., De Jong PA; Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands., Pluim JPW; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.; Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., Suijkerbuijk KPM; Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. k.suijkerbuijk@umcutrecht.nl., Veta M; Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Publikováno v: Scientific reports [Sci Rep] 2024 Dec 30; Vol. 14 (1), pp. 31668. Date of Electronic Publication: 2024 Dec 30.

Deep-learning-based joint rigid and deformable contour propagation for magnetic resonance imaging-guided prostate radiotherapy.

Autor: Kolenbrander ID; Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.; Eindhoven Artificial Intelligence Systems Institute, Eindhoven University of Technology, Eindhoven, The Netherlands., Maspero M; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., Hendriksen AA; Computational Imaging, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands., Pollitt R; Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., van der Voort van Zyp JRN; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., van den Berg CAT; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.; Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands., Pluim JPW; Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.; Eindhoven Artificial Intelligence Systems Institute, Eindhoven University of Technology, Eindhoven, The Netherlands., van Eijnatten MAJM; Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.; Eindhoven Artificial Intelligence Systems Institute, Eindhoven University of Technology, Eindhoven, The Netherlands.

Publikováno v: Medical physics [Med Phys] 2024 Apr; Vol. 51 (4), pp. 2367-2377. Date of Electronic Publication: 2024 Feb 26.

Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T.

Autor: Harrevelt SD; Department of Biomedical Engineering, Technische Universiteit Eindhoven, Eindhoven, The Netherlands., Meliado EFM; Department of Radiotherapy, UMC Utrecht, Utrecht, The Netherlands., van Lier ALHMW; Department of Radiotherapy, UMC Utrecht, Utrecht, The Netherlands., Reesink D; Department of Oncological Urology, UMC Utrecht, Utrecht, The Netherlands., Meijer RP; Department of Oncological Urology, UMC Utrecht, Utrecht, The Netherlands., Pluim JPW; Department of Biomedical Engineering, Technische Universiteit Eindhoven, Eindhoven, The Netherlands., Raaijmakers AJE; Department of Biomedical Engineering, Technische Universiteit Eindhoven, Eindhoven, The Netherlands.; Department of Radiotherapy, UMC Utrecht, Utrecht, The Netherlands.

Publikováno v: NMR in biomedicine [NMR Biomed] 2023 Dec; Vol. 36 (12), pp. e5019. Date of Electronic Publication: 2023 Aug 25.

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma.

Autor: Ter Maat LS; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands. Electronic address: l.s.termaat@umcutrecht.nl., van Duin IAJ; Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Elias SG; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Leiner T; Department of Radiology, Mayo Clinical, Rochester, MN, USA., Verhoeff JJC; Department of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Arntz ERAN; Utrecht University, Utrecht, the Netherlands., Troenokarso MF; Utrecht University, Utrecht, the Netherlands., Blokx WAM; Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Isgum I; Departments of Biomedical Engineering and Physics & Radiology and Nuclear Medicine, University Medical Center Amsterdam, University of Amsterdam, Amsterdam, the Netherlands; Quantitative Healthcare Analysis group, Informatics Institute, Faculty of Science, University of Amsterdam, Amsterdam, the Netherlands., de Wit GA; Department of Public Health, Healthcare Innovation & Evaluation and Medical Humanities, Julius Center Research Program Methodology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., van den Berkmortel FWPJ; Department of Medical Oncology, Zuyderland Medical Center, Sittard-Geleen, the Netherlands., Boers-Sonderen MJ; Department of Medical Oncology, Radboudumc, Radboud University, Nijmegen, the Netherlands., Boomsma MF; Department of Radiology, Isala Zwolle, Zwolle, the Netherlands., van den Eertwegh FJM; Department of medical oncology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Boelelaan 1117, Amsterdam, the Netherlands., de Groot JWB; Isala Oncology Center, Isala Zwolle, Zwolle, the Netherlands., Piersma D; Department of Medical Oncology, Medisch Spectrum Twente, Enschede, the Netherlands., Vreugdenhil A; Department of Medical Oncology, Máxima Medical Center, Veldhoven, the Netherlands., Westgeest HM; Department of Medical Oncology, Amphia Hospital, Breda, the Netherlands., Kapiteijn E; Department of Medical Oncology, Leiden University Medical Center, Leiden University, Leiden, the Netherlands., van Diest PJ; Department of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Pluim JPW; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands., de Jong PA; Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Suijkerbuijk KPM; Department of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands., Veta M; Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.

Publikováno v: European journal of cancer (Oxford, England : 1990) [Eur J Cancer] 2023 May; Vol. 185, pp. 167-177. Date of Electronic Publication: 2023 Feb 24.

Bandwidth Improvement in Ultrasound Image Reconstruction Using Deep Learning Techniques.

Autor: Awasthi N; Photoacoustics and Ultrasound Laboratory Eindhoven (PULS/e), Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.; Medical Image Analysis Group (IMAG/e), Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., van Anrooij L; Medical Image Analysis Group (IMAG/e), Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., Jansen G; Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, 1105 AZ Amsterdam, The Netherlands., Schwab HM; Photoacoustics and Ultrasound Laboratory Eindhoven (PULS/e), Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands., Pluim JPW; Medical Image Analysis Group (IMAG/e), Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.; Image Sciences Institute, University Medical Center, 3584 CX Utrecht, The Netherlands., Lopata RGP; Photoacoustics and Ultrasound Laboratory Eindhoven (PULS/e), Department of Biomedical Engineering, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.

Publikováno v: Healthcare (Basel, Switzerland) [Healthcare (Basel)] 2022 Dec 30; Vol. 11 (1). Date of Electronic Publication: 2022 Dec 30.