Researcher
Frederik Maes
- Disciplines:Artificial intelligence, Multimedia processing, Biological system engineering, Signal processing, Other computer engineering, information technology and mathematical engineering, Medical imaging and therapy
Affiliations
- Processing Speech and Images (PSI) (Division)
Responsible
From1 Aug 2020 → Today - Processing Speech and Images (PSI) (Division)
Member
From1 Aug 2020 → Today - Department of Electrical Engineering (ESAT) (Department)
Member
From1 Oct 2004 → 31 Dec 2007 - Radiology (Division)
Member
From1 Oct 2000 → 30 Sep 2004 - ESAT - PSI, Processing Speech and Images (Division)
Member
From1 Oct 1999 → 31 Jul 2020
Projects
1 - 10 of 53
- Engelstalig: precision medicine en care in patients neuromuscular dystrophyFrom7 Nov 2023 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Compressed sensing for accelerated microstructure imagingFrom1 Oct 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Machine Learning tool to increase the efficiency of segmentation correction in transcatheter heart intervention planningFrom1 Sep 2022 → TodayFunding: Baekeland
- Evaluating novel radiological and clinical outcome measures in hereditary neuromuscular diseases.From1 Jun 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Development of AI tools to assist the treatment of colorectal cancerFrom1 Feb 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- AI in medical imaging: from proof-of-concept to daily radiology servicesFrom11 Jan 2022 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Development of AI based imaging tools for the analysis of lung disease in preclinical rodent modelsFrom22 Nov 2021 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Learning-based computational strategies for multimodal image analysis of neurovascular diseasesFrom18 Nov 2021 → TodayFunding: FWO fellowships
- Towards more accurate diagnostics in healthcare: AI applied to super-resolution ultrasound imagingFrom1 Nov 2021 → TodayFunding: Department Coordination
- Machine Learning Methods for Multiple Sclerosis Classification and Prediction using MRI Brain ConnectivityFrom25 Jan 2021 → 6 Oct 2022Funding: Own budget, for example: patrimony, inscription fees, gifts
Publications
31 - 40 of 235
- Shape constrained CNN for cardiac MR segmentation with simultaneous prediction of shape and pose parameters(2021)
Authors: Sofie Tilborghs, Tom Dresselaers, Piet Claus, Jan Bogaert, Frederik Maes
Pages: 127 - 136 - Resorption of retromolar bone grafts after alveolar ridge augmentation-volumetric changes after 12 months assessed by CBCT analysis(2021)
Authors: Reinhilde Jacobs, Frederik Maes
- Learning from mistakes: An error-driven mechanism to improve segmentation performance based on expert feedback(2021)
Authors: Siri Willems, Edmond Sterpin, Wouter Crijns, Sandra Nuyts, Frederik Maes
Pages: 68 - 77 - Artificial intelligence and its impact on quality improvement in upper and lower gastrointestinal endoscopy(2021)
Authors: Pieter Sinonquel, Tom Eelbode, Peter Bossuyt, Frederik Maes, Raf Bisschops
Pages: 242 - 253 - On the relationship between calibrated predictors and unbiased volume estimation(2021)
Authors: Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew Blaschko
Pages: 678 - 688 - icobrain ms 5.1: Combining unsupervised and supervised approaches for improving the detection of multiple sclerosis lesions(2021)
Authors: Mladen Rakic, Sabine Van Huffel, Frederik Maes
- Improving T1w MRI-based brain tumor segmentation using cross-modal distillation(2021)
Authors: Masoomeh Rahimpour, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Karolien Goffin, Michel Koole
- Deep learning for elective neck delineation: More consistent and time efficient(2020)
Authors: Julie Van Der Veen, Siri Willems, Frederik Maes, Sandra Nuyts
Pages: 180 - 188 - The Treasury of Images: exploring the opportunities for diagnosing and treating prostate cancer(2020)
Authors: Cédric Draulans, Karin Haustermans, Frederik Maes, Sofie Isebaert
- Ga-68-PSMA-11-PET, F-18-PSMA-1007-PET and MRI for Gross Tumor Volume Delineation in Primary Prostate Cancer: Intermodality and Inter-tracer Variability(2020)
Authors: Cédric Draulans, FJ Pos, RJ Smeenk, L Kerkmeijer, W Vogel, J Nagarajah, M Janssen, C Mai, S Heijmink, M van der Leest, et al.
Pages: E878 - E878
Patents
1 - 1 of 1