Jeroen de Groof

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 12

Top Topics

Discriminative Classifiers

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Medical Imaging: Image Processing

Artif. Intell. Medicine

Publications

T. G. W. Boers, Carolus H. J. Kusters, Kiki N. Fockens, Jelmer B. Jukema, Martijn R. Jong, Jeroen de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With
Barrett's lesion detection using a minimal integer-based neural network for embedded systems integration. Medical Imaging: Computer-Aided Diagnosis (2023)
T. G. W. Boers, Carolus H. J. Kusters, Kiki N. Fockens, Jelmer B. Jukema, Martijn R. Jong, Jeroen de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With
Comparing Training Strategies Using Multi-Assessor Segmentation Labels for Barrett's Neoplasia Detection. CaPTion@MICCAI (2022)
Joost van der Putten, Maarten R. Struyvenberg, Jeroen de Groof, Thom Scheeve, Wouter L. Curvers, Erik J. Schoon, Jacques J. G. H. M. Bergman, Peter H. N. de With, Fons van der Sommen
Deep principal dimension encoding for the classification of early neoplasia in Barrett's Esophagus with volumetric laser endomicroscopy. Comput. Medical Imaging Graph. 80 (2020)
Joost van der Putten, Jeroen de Groof, Maarten R. Struyvenberg, Tim Boers, Kiki Fockens, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With
Multi-stage domain-specific pretraining for improved detection and localization of Barrett's neoplasia: A comprehensive clinically validated study. Artif. Intell. Medicine 107 (2020)
Joost van der Putten, Fons van der Sommen, Jeroen de Groof, Maarten R. Struyvenberg, Svitlana Zinger, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman, Peter H. N. de With
Modeling clinical assessor intervariability using deep hypersphere encoder-decoder networks. Neural Comput. Appl. 32 (14) (2020)
Levi Verhage, Joost van der Putten, Fons van der Sommen, Jeroen de Groof, Maarten R. Struyvenberg, Peter H. N. de With
The field effect in Barrett's Esophagus: a macroscopic view using white light endoscopy and deep learning. Medical Imaging: Computer-Aided Diagnosis (2020)
T. G. W. Boers, Joost van der Putten, Jeroen de Groof, Maarten R. Struyvenberg, Kiki Fockens, Wouter L. Curvers, Erik J. Schoon, Fons van der Sommen, Jacques J. Bergman, Peter H. N. de With
Detection of frame informativeness in endoscopic videos using image quality and recurrent neural networks. Medical Imaging: Image Processing (2020)
Joost van der Putten, Jeroen de Groof, Fons van der Sommen, Maarten R. Struyvenberg, Svitlana Zinger, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman, Peter H. N. de With
First steps into endoscopic video analysis for Barrett's cancer detection: challenges and opportunities. Medical Imaging: Computer-Aided Diagnosis (2020)
Joost van der Putten, Jeroen de Groof, Fons van der Sommen, Maarten R. Struyvenberg, Svitlana Zinger, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman, Peter H. N. de With
Pseudo-labeled Bootstrapping and Multi-stage Transfer Learning for the Classification and Localization of Dysplasia in Barrett's Esophagus. MLMI@MICCAI (2019)
Joost van der Putten, Fons van der Sommen, Maarten R. Struyvenberg, Jeroen de Groof, Wouter L. Curvers, Erik J. Schoon, Jacques J. G. H. M. Bergman, Peter H. N. de With
Tissue segmentation in volumetric laser endomicroscopy data using FusionNet and a domain-specific loss function. Medical Imaging: Image Processing (2019)
Joost van der Putten, Rogier R. Wildeboer, Jeroen de Groof, Ruud van Sloun, Maarten R. Struyvenberg, Fons van der Sommen, Svitlana Zinger, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman, Peter H. N. de With
Deep Learning Biopsy Marking of Early Neoplasia in Barrett's Esophagus by Combining WLE and BLI Modalities. ISBI (2019)
Joost van der Putten, Jeroen de Groof, Fons van der Sommen, Maarten R. Struyvenberg, Svitlana Zinger, Wouter L. Curvers, Erik J. Schoon, Jacques J. Bergman, Peter H. N. de With
Informative Frame Classification of Endoscopic Videos Using Convolutional Neural Networks and Hidden Markov Models. ICIP (2019)