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 dystrophyFrom1 Oct 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
21 - 30 of 238
- Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy(2022)
Authors: Siri Willems, Liesbeth Vandewinckele, Wouter Crijns, Frederik Maes, Caroline Weltens
Pages: 84 - 90 - Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty (vol 9, 840282, 2022)(2022)
Authors: Adriaan Lambrechts, Frederik Maes, Sabine Van Huffel
- Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty(2022)
Authors: Adriaan Lambrechts, Frederik Maes, Sabine Van Huffel
- The Dice loss in the context of missing or empty labels: introducing phi and epsilon(2022)
Authors: Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes
Pages: 527 - 537Number of pages: 11 - Cross-modal distillation to improve MRI-based brain tumor segmentation with missing MRI sequences.(2021)
Authors: Masoomeh Rahimpour, Jeroen Bertels, Ahmed Radwan, Stefan Sunaert, Dirk Vandermeulen, Frederik Maes, Karolien Goffin, Michel Koole
Pages: 1 - 12 - Model-based Strategies for Joint Analysis of Multi-Parametric Cardiac MRI Sequences(2021)
Authors: Sofie Tilborghs, Frederik Maes
- Convolutional LSTM(2021)
Authors: Tom Eelbode, Pieter Sinonquel, Raf Bisschops, Frederik Maes
Pages: 121 - 126 - Interobserver variability in organ at risk delineation in head and neck cancer(2021)
Authors: Siri Willems, Frederik Maes, Sandra Nuyts
- Pitfalls in training and validation of deep learning systems(2021)
Authors: Tom Eelbode, Pieter Sinonquel, Frederik Maes, Raf Bisschops
- Ga-68-PSMA-11 PET, F-18-PSMA-1007 PET, and MRI for Gross Tumor Volume Delineation in Primary Prostate Cancer: Intermodality and Intertracer Variability(2021)
Authors: Cédric Draulans, Raymond Oyen, Sofie Isebaert, Frederik Maes, Steven Joniau, Robin De Roover, Gilles Defraene, Karolien Goffin, Karin Haustermans
Pages: 202 - 211
Patents
1 - 1 of 1