default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDFons van der Sommen
Person information
- affiliation: Eindhoven University of Technology, Department of Electrical Engineering
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[j19]Carolus H. J. Kusters
, Tim J. M. Jaspers, T. G. W. Boers, Martijn R. Jong, Jelmer B. Jukema, Kiki N. Fockens, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With:
Will Transformers change gastrointestinal endoscopic image analysis? A comparative analysis between CNNs and Transformers, in terms of performance, robustness and generalization. Medical Image Anal. 99: 103348 (2025)- [e3]Sharib Ali, Fons van der Sommen, Bartlomiej Wladyslaw Papiez, Noha Ghatwary, Yueming Jin, Iris Kolenbrander:
Cancer Prevention, Detection, and Intervention - Third MICCAI Workshop, CaPTion 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings. Lecture Notes in Computer Science 15199, Springer 2025, ISBN 978-3-031-73375-8 [contents] - 2024
- [j18]Tim J. M. Jaspers, Tim Boers, Carolus H. J. Kusters, Martijn R. Jong, Jelmer B. Jukema, Albert J. de Groof, Jacques J. Bergman, Peter H. N. de With, Fons van der Sommen:
Robustness evaluation of deep neural networks for endoscopic image analysis: Insights and strategies. Medical Image Anal. 94: 103157 (2024) - [j17]Tim Boers, Kiki N. Fockens, Joost A. van der Putten, Tim J. M. Jaspers, Carolus H. J. Kusters, Jelmer B. Jukema, Martijn R. Jong, Maarten R. Struyvenberg, Jeroen de Groof, Jacques J. Bergman, Peter H. N. de With, Fons van der Sommen:
Foundation models in gastrointestinal endoscopic AI: Impact of architecture, pre-training approach and data efficiency. Medical Image Anal. 98: 103298 (2024) - [j16]Tim J. Schoonbeek, Goutham Balachandran, Hans Onvlee, Tim Houben, Shao-Hsuan Hung, Jacek Kustra, Peter H. N. de With, Fons van der Sommen:
Supervised Representation Learning Towards Generalizable Assembly State Recognition. IEEE Robotics Autom. Lett. 9(11): 9915-9922 (2024) - [j15]Christiaan G. A. Viviers, Lena Filatova, Maurice Termeer, Peter H. N. de With, Fons van der Sommen:
Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging Geometries. IEEE Trans. Image Process. 33: 2462-2476 (2024) - [c72]Nikoo Dehghani, Ayla Thijssen, Quirine E. W. van der Zander, Ramon-Michel Schreuder, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
Evaluating Confidence Calibration in Endoscopic Diagnosis Models. CVPR Workshops 2024: 5020-5025 - [c71]M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud van Sloun, Peter H. N. de With, Fons van der Sommen:
Retaining Informative Latent Variables in Probabilistic Segmentation. ICASSP 2024: 5635-5639 - [c70]Willem J. Menu, Nikoo Dehghani, Peter H. N. de With, Fons van der Sommen:
Effect of Post-Training Pruning and Quantization on Endoscopic Computer-Aided Diagnosis Models. ISBI 2024: 1-5 - [c69]Joris V. de Nijs, Tim J. M. Jaspers, Franciscus H. A. Bakker, Willem M. Brinkman, Peter H. N. de With, Fons van der Sommen:
Automated Surgical Urethral Length Estimation for Robot-Assisted Radical Prostatectomy. ISBI 2024: 1-5 - [c68]Cris H. B. Claessens, Eloy W. R. Schultz, Anna Koch, Ingrid Nies, Terese A. E. Hellström, Joost Nederend, Ilse Niers-Stobbe, Annemarie Bruining, Jurgen M. J. Piek, Peter H. N. de With, Fons van der Sommen:
Multi-center Ovarian Tumor Classification Using Hierarchical Transformer-Based Multiple-Instance Learning. CaPTion@MICCAI 2024: 3-13 - [c67]Tim J. M. Jaspers, Ronald L. P. D. de Jong, Yasmina Al Khalil, Tijn Zeelenberg, Carolus H. J. Kusters, Yiping Li, Romy C. van Jaarsveld, Franciscus H. A. Bakker, Jelle P. Ruurda, Willem M. Brinkman, Peter H. N. de With, Fons van der Sommen:
Exploring the Effect of Dataset Diversity in Self-supervised Learning for Surgical Computer Vision. DEMI@MICCAI 2024: 43-53 - [c66]Carolus H. J. Kusters, T. G. W. Boers, Tim J. M. Jaspers, Martijn R. Jong, Rixta A. H. van Eijck van Heslinga, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With:
Optimizing Multi-expert Consensus for Classification and Precise Localization of Barrett's Neoplasia. CaPTion@MICCAI 2024: 83-92 - [c65]Lemar Abdi, M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Peter H. N. de With, Fons van der Sommen:
Typicality Excels Likelihood for Unsupervised Out-of-Distribution Detection in Medical Imaging. UNSURE@MICCAI 2024: 149-159 - [c64]Marissa Ramirez de Chanlatte, Phillip Colella, Trevor Darrell, Alexandra Carlson, Peter H. N. de With, Huayu Deng, Shanyan Guan, James Hays, Tim Houben, Thomas Huisman, Nikita Jaipuria, Hans Johansen, Shuja Khalid, Akshay Krishnan, Chuming Li, Maxim Pisarenco, Amit Raj, Frank Rudzicz, Tim J. Schoonbeek, Sandhya Sridhar, Nathan Tseng, Fons van der Sommen, Chen Wang, Yunbo Wang, Tong Wu, Xiaokang Yang, Jiawei Yao, Derek Young, Xianling Zhang:
Proceedings of the Workshop on 3D Geometry Generation for Scientific Computing. WACV (Workshops) 2024: 762-766 - [c63]Tim J. Schoonbeek, Tim Houben, Hans Onvlee, Peter H. N. de With, Fons van der Sommen:
IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like Setting. WACV 2024: 4353-4362 - [i16]Christiaan G. A. Viviers, Lena Filatova, Maurice Termeer, Peter H. N. de With, Fons van der Sommen:
Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging Geometries. CoRR abs/2405.11677 (2024) - [i15]Tim J. M. Jaspers, Ronald L. P. D. de Jong, Yasmina Al Khalil, Tijn Zeelenberg, Carolus H. J. Kusters, Yiping Li, Romy C. van Jaarsveld, Franciscus H. A. Bakker, Jelle P. Ruurda, Willem M. Brinkman, Peter H. N. de With, Fons van der Sommen:
Exploring the Effect of Dataset Diversity in Self-Supervised Learning for Surgical Computer Vision. CoRR abs/2407.17904 (2024) - [i14]Tim J. Schoonbeek, Goutham Balachandran, Hans Onvlee, Tim Houben, Shao-Hsuan Hung, Jacek Kustra, Peter H. N. de With, Fons van der Sommen:
Supervised Representation Learning towards Generalizable Assembly State Recognition. CoRR abs/2408.11700 (2024) - [i13]Dan Lehman, Tim J. Schoonbeek, Shao-Hsuan Hung, Jacek Kustra, Peter H. N. de With, Fons van der Sommen:
Find the Assembly Mistakes: Error Segmentation for Industrial Applications. CoRR abs/2408.12945 (2024) - [i12]Christiaan G. A. Viviers, M. M. Amaan Valiuddin, Francisco Caetano, Lemar Abdi, Lena Filatova, Peter H. N. de With, Fons van der Sommen:
Can Your Generative Model Detect Out-of-Distribution Covariate Shift? CoRR abs/2409.03043 (2024) - 2023
- [j14]Luis Albert Zavala-Mondragón, Peter H. N. de With, Fons van der Sommen:
A Signal Processing Interpretation of Noise-Reduction Convolutional Neural Networks: Exploring the mathematical formulation of encoding-decoding CNNs. IEEE Signal Process. Mag. 40(7): 38-63 (2023) - [c62]Christiaan G. A. Viviers, Mark Ramaekers, M. M. Amaan Valiuddin, Terese Hellström, Nick Tasios, John van der Ven, Igor Jacobs, Lotte Ewals, Joost Nederend, Peter H. N. de With, Misha Luyer, Fons van der Sommen:
Segmentation-based Assessment of Tumor-Vessel Involvement for Surgical Resectability Prediction of Pancreatic Ductal Adenocarcinoma. ICCV (Workshops) 2023: 2413-2423 - [c61]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 - [c60]Nikoo Dehghani, Thom Scheeve, T. G. W. Boers, Quirine E. W. van der Zander, Ayla Thijssen, Ramon-Michel Schreuder, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
Effect of domain-specific self-supervised pretraining on predictive uncertainty for colorectal polyp characterization. Medical Imaging: Computer-Aided Diagnosis 2023 - [c59]Terese Hellström, Christiaan G. A. Viviers, Mark Ramaekers, Nick Tasios, Joost Nederend, Misha Luyer, Peter H. N. de With, Fons van der Sommen:
Clinical segmentation for improved pancreatic ductal adenocarcinoma detection and segmentation. Medical Imaging: Computer-Aided Diagnosis 2023 - [c58]Carolus H. J. Kusters, T. G. W. Boers, Jelmer B. Jukema, Martijn R. Jong, Kiki N. Fockens, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With:
Real-time Barrett's neoplasia characterization in NBI videos using an int8-based quantized neural network. Medical Imaging: Computer-Aided Diagnosis 2023 - [c57]Thom Scheeve, Nikoo Dehghani, Quirine E. W. van der Zander, Ayla Thijssen, Ramon-Michel Schreuder, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
How does image quality affect computer-aided diagnosis of colorectal polyps? Medical Imaging: Computer-Aided Diagnosis 2023 - [c56]Christiaan G. A. Viviers, M. M. Amaan Valiuddin, Peter H. N. de With, Fons van der Sommen:
Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data. Medical Imaging: Computer-Aided Diagnosis 2023 - [c55]Carolus H. J. Kusters, T. G. W. Boers, Tim J. M. Jaspers, Jelmer B. Jukema, Martijn R. Jong, Kiki N. Fockens, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With:
CNNs vs. Transformers: Performance and Robustness in Endoscopic Image Analysis. AMAI@MICCAI 2023: 21-31 - [c54]Tim J. M. Jaspers, Tim Boers, Carolus H. J. Kusters, Martijn R. Jong, Jelmer B. Jukema, Albert J. de Groof, Jacques J. Bergman, Peter H. N. de With, Fons van der Sommen:
Investigating the Impact of Image Quality on Endoscopic AI Model Performance. AMAI@MICCAI 2023: 32-41 - [c53]Sanne E. Okel, Christiaan G. A. Viviers, Mark Ramaekers, Terese Hellström, Nick Tasios, Dimitrios Mavroeidis, Jon R. Pluyter, Igor Jacobs, Misha Luyer, Peter H. N. de With, Fons van der Sommen:
Advancing Abdominal Organ and PDAC Segmentation Accuracy with Task-Specific Interactive Models. AMAI@MICCAI 2023: 52-61 - [c52]Tim J. Schoonbeek, Hans Onvlee, Pierluigi Frisco, Peter H. N. de With, Fons van der Sommen:
Beyond Action Recognition: Extracting Meaningful Information from Procedure Recordings. VR Workshops 2023: 881-882 - [e2]Sharib Ali, Fons van der Sommen, Maureen van Eijnatten, Bartlomiej W. Papiez, Yueming Jin, Iris Kolenbrander:
Cancer Prevention Through Early Detection - Second International Workshop, CaPTion 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. Lecture Notes in Computer Science 14295, Springer 2023, ISBN 978-3-031-45349-6 [contents] - [i11]Christiaan G. A. Viviers, M. M. Amaan Valiuddin, Peter H. N. de With, Fons van der Sommen:
Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data. CoRR abs/2305.00950 (2023) - [i10]Luis Albert Zavala-Mondragón, Peter H. N. de With, Fons van der Sommen:
A signal processing interpretation of noise-reduction convolutional neural networks. CoRR abs/2307.13425 (2023) - [i9]M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen:
Investigating and Improving Latent Density Segmentation Models for Aleatoric Uncertainty Quantification in Medical Imaging. CoRR abs/2307.16694 (2023) - [i8]Christiaan G. A. Viviers, Mark Ramaekers, M. M. Amaan Valiuddin, Terese Hellström, Nick Tasios, John van der Ven, Igor Jacobs, Lotte Ewals, Joost Nederend, Peter H. N. de With, Misha Luyer, Fons van der Sommen:
Segmentation-based Assessment of Tumor-Vessel Involvement for Surgical Resectability Prediction of Pancreatic Ductal Adenocarcinoma. CoRR abs/2310.00639 (2023) - [i7]Tim J. Schoonbeek, Tim Houben, Hans Onvlee, Peter H. N. de With, Fons van der Sommen:
IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like Setting. CoRR abs/2310.17323 (2023) - 2022
- [j13]Tim Houben, Thomas Huisman, Maxim Pisarenco, Fons van der Sommen, Peter H. N. de With:
Depth estimation from a single SEM image using pixel-wise fine-tuning with multimodal data. Mach. Vis. Appl. 33(4): 56 (2022) - [j12]Luis Albert Zavala-Mondragón, Peter M. J. Rongen, Javier Oliván Bescós, Peter H. N. de With, Fons van der Sommen:
Noise Reduction in CT Using Learned Wavelet-Frame Shrinkage Networks. IEEE Trans. Medical Imaging 41(8): 2048-2066 (2022) - [c51]Koen C. Kusters, Thom Scheeve, Nikoo Dehghani, Quirine E. W. van der Zander, Ramon-Michel Schreuder, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
Colorectal polyp classification using confidence-calibrated convolutional neural networks. Medical Imaging: Computer-Aided Diagnosis 2022 - [c50]Fidan Mammadli, Fons van der Sommen, Tim Boers, Joost van der Putten, Kiki N. Fockens, Jelmer B. Jukema, Martijn R. Jong, Jacques J. G. H. M. Bergman, Peter H. N. de With:
Efficient endoscopic frame informativeness assessment by reusing the encoder of the primary CAD task. Medical Imaging: Computer-Aided Diagnosis 2022 - [c49]Carolus H. J. Kusters, Tim Boers, Jelmer B. Jukema, Martijn R. Jong, Kiki N. Fockens, Albert J. de Groof, Jacques J. Bergman, Fons van der Sommen, Peter H. N. de With:
A CAD System for Real-Time Characterization of Neoplasia in Barrett's Esophagus NBI Videos. CaPTion@MICCAI 2022: 89-98 - [c48]M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen:
Efficient Out-of-Distribution Detection of Melanoma with Wavelet-Based Normalizing Flows. CaPTion@MICCAI 2022: 99-107 - [c47]Nikoo Dehghani, Thom Scheeve, Quirine E. W. van der Zander, Ayla Thijssen, Ramon-Michel Schreuder, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
Robust Colorectal Polyp Characterization Using a Hybrid Bayesian Neural Network. CaPTion@MICCAI 2022: 108-117 - [c46]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: 131-138 - [c45]Christiaan G. A. Viviers, Mark Ramaekers, Peter H. N. de With, Dimitrios Mavroeidis, Joost Nederend, Misha Luyer, Fons van der Sommen:
Improved Pancreatic Tumor Detection by Utilizing Clinically-Relevant Secondary Features. CaPTion@MICCAI 2022: 139-148 - [c44]Christiaan G. A. Viviers, Joel de Bruijn, Lena Filatova, Peter H. N. de With, Fons van der Sommen:
Towards real-time 6D pose estimation of objects in single-view cone-beam x-ray. Medical Imaging: Image-Guided Procedures 2022 - [c43]Kurt Stolle, Sebastian Vogel, Fons van der Sommen, Willem P. Sanberg:
Block-Level Surrogate Models for Inference Time Estimation in Hardware-Aware Neural Architecture Search. ECML/PKDD (5) 2022: 463-479 - [e1]Sharib Ali, Fons van der Sommen, Bartlomiej Wladyslaw Papiez, Maureen A. J. M. van Eijnatten, Yueming Jin, Iris Kolenbrander:
Cancer Prevention Through Early Detection - First International Workshop, CaPTion 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13581, Springer 2022, ISBN 978-3-031-17978-5 [contents] - [i6]Christiaan G. A. Viviers, Mark Ramaekers, Peter H. N. de With, Dimitrios Mavroeidis, Joost Nederend, Misha Luyer, Fons van der Sommen:
Improved Pancreatic Tumor Detection by Utilizing Clinically-Relevant Secondary Features. CoRR abs/2208.03581 (2022) - [i5]M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen:
Efficient Out-of-Distribution Detection of Melanoma with Wavelet-based Normalizing Flows. CoRR abs/2208.04639 (2022) - [i4]Christiaan G. A. Viviers, Joel de Bruijn, Lena Filatova, Peter H. N. de With, Fons van der Sommen:
Towards real-time 6D pose estimation of objects in single-view cone-beam X-ray. CoRR abs/2211.03211 (2022) - 2021
- [j11]Roger Fonolla, Quirine E. W. van der Zander, Ramon-Michel Schreuder, Sharmila Subramaniam, Pradeep Bhandari, Ad A. M. Masclee, Erik J. Schoon, Fons van der Sommen, Peter H. N. de With:
Automatic image and text-based description for colorectal polyps using BASIC classification. Artif. Intell. Medicine 121: 102178 (2021) - [j10]Luis Albert Zavala-Mondragón, Peter H. N. de With, Fons van der Sommen:
Image Noise Reduction Based on a Fixed Wavelet Frame and CNNs Applied to CT. IEEE Trans. Image Process. 30: 9386-9401 (2021) - [c42]Catherine Taelman, Saloua Chlaily, Eduard Khachatrian, Fons van der Sommen, Andrea Marinoni:
On the Exploitation of Heterophily in Graph-Based Multimodal Remote Sensing Data Analysis. CIKM Workshops 2021 - [c41]Koen C. Kusters, Luis Albert Zavala-Mondragón, Javier Oliván Bescós, Peter M. J. Rongen, Peter H. N. de With, Fons van der Sommen:
Conditional Generative Adversarial Networks for low-dose CT image denoising aiming at preservation of critical image content. EMBC 2021: 2682-2687 - [c40]Stefan Cornelissen, Joost A. van der Putten, T. G. W. Boers, Jelmer B. Jukema, Kiki N. Fockens, Jacques J. G. H. M. Bergman, Fons van der Sommen, Peter H. N. de With:
Evaluating Self-Supervised Learning Methods for Downstream Classification of Neoplasia in Barrett's Esophagus. ICIP 2021: 66-70 - [c39]Roger Fonolla, Maciej Smyl, Fons van der Sommen, Ramon-Michel Schreuder, Erik J. Schoon, Peter H. N. de With:
Triplet network for classification of benign and pre-malignant polyps. Medical Imaging: Computer-Aided Diagnosis 2021 - [c38]Sanne E. Okel, Fons van der Sommen, Endi Selmanaj, Joost van der Putten, Maarten R. Struyvenberg, Jacques J. G. H. M. Bergman, Peter H. N. de With:
Tissue-border detection in volumetric laser endomicroscopy using bi-directional gated recurrent neural networks. Medical Imaging: Computer-Aided Diagnosis 2021 - [c37]M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen:
Improving Aleatoric Uncertainty Quantification in Multi-annotated Medical Image Segmentation with Normalizing Flows. UNSURE/PIPPI@MICCAI 2021: 75-88 - [c36]Francesca Manni, Chuchen Cai, Fons van der Sommen, Svitlana Zinger, Caifeng Shan, Erik Edström, Adrian Elmi Terander, Himar Fabelo, Samuel Ortega, Gustavo Marrero Callicó, Peter H. N. de With:
Hyperspectral imaging for tissue classification in glioblastoma tumor patients: a deep spectral-spatial approach. Medical Imaging: Image-Guided Procedures 2021 - [c35]Francesca Manni, Cyril J. Ferrer, Celine E. C. Vincent, Marco Lai, Lambertus W. Bartels, Clemens Bos, Fons van der Sommen, Peter H. N. de With:
Augmented-reality visualization for improved patient positioning workflow during MR-HIFU therapy. Medical Imaging: Image-Guided Procedures 2021 - [c34]Endi Selmanaj, Fons van der Sommen, Sanne E. Okel, Joost van der Putten, Maarten R. Struyvenberg, Jacques J. G. H. M. Bergman, Peter H. N. de With:
Fast tissue detection in volumetric laser endomicroscopy using convolutional neural networks: an object-detection approach. Medical Imaging: Image Processing 2021 - [c33]Luis Albert Zavala-Mondragón, Klaus J. Engel, Bernd Menser, Danny Ruijters, Peter H. N. de With, Fons van der Sommen:
Iterative reconstruction anti-correlated ROF model for noise reduction in dual-energy CBCT imaging. Medical Imaging: Image Processing 2021 - [i3]M. M. Amaan Valiuddin, Christiaan G. A. Viviers, Ruud J. G. van Sloun, Peter H. N. de With, Fons van der Sommen:
Improving Aleatoric Uncertainty Quantification in Multi-Annotated Medical ImageSegmentation with Normalizing Flows. CoRR abs/2108.02155 (2021) - 2020
- [j9]Joost van der Putten, Fons van der Sommen, Peter H. N. de With:
Efficient Decoder Reduction for a Variety of Encoder-Decoder Problems. IEEE Access 8: 169444-169455 (2020) - [j8]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: 101914 (2020) - [j7]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: 101701 (2020) - [j6]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): 10705-10717 (2020) - [j5]Francesca Manni, Adrian Elmi Terander, Gustav Burström, Oscar Persson, Erik Edström, Ronald Holthuizen, Caifeng Shan, Svitlana Zinger, Fons van der Sommen, Peter H. N. de With:
Towards Optical Imaging for Spine Tracking without Markers in Navigated Spine Surgery. Sensors 20(13): 3641 (2020) - [j4]Tim Boers, Joost van der Putten, Maarten R. Struyvenberg, Kiki Fockens, Jelmer Jukema, Erik J. Schoon, Fons van der Sommen, Jacques J. Bergman, Peter H. N. de With:
Improving Temporal Stability and Accuracy for Endoscopic Video Tissue Classification Using Recurrent Neural Networks. Sensors 20(15): 4133 (2020) - [j3]Francesca Manni, Fons van der Sommen, Himar Fabelo, Svitlana Zinger, Caifeng Shan, Erik Edström, Adrian Elmi Terander, Samuel Ortega, Gustavo Marrero Callicó, Peter H. N. de With:
Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach. Sensors 20(23): 6955 (2020) - [c32]Francesca Manni, Roger Fonollá, Fons van der Sommen, Svitlana Zinger, Caifeng Shan, Esther Kho, Susan G. Brouwer de Koning, Theo Ruers, Peter H. N. de With:
Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery. EMBC 2020: 1169-1173 - [c31]Luis Albert Zavala-Mondragón, Fons van der Sommen, Danny Ruijters, Klaus J. Engel, Heidrun Steinhauser, Peter H. N. de With:
Robust Algorithm for Denoising of Photon-Limited Dual-Energy Cone Beam CT Projections. ISBI 2020: 867-871 - [c30]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 - [c29]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 - [c28]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: 1131315 - [c27]Joost van der Putten, Fons van der Sommen, Peter H. N. de With:
Influence of decoder size for binary segmentation tasks in medical imaging. Medical Imaging: Image Processing 2020: 1131318 - [c26]Luis Albert Zavala-Mondragón, Danny Ruijters, Peter van de Haar, Peter H. N. de With, Fons van der Sommen:
Dual-Energy CBCT Pre-Spectral-Decomposition Filtering with Wavelet Shrinkage Networks. MLSP 2020: 1-6
2010 – 2019
- 2019
- [c25]Francesca Manni, Xin Liu, Ronald Holthuizen, Svitlana Zinger, Fons van der Sommen, Caifeng Shan, Marco Mamprin, Gustav Burström, Adrian Elmi Terander, Erik Edström, Peter H. N. de With:
Towards non-invasive patient tracking: optical image analysis for spine tracking during spinal surgery procedures. EMBC 2019: 3909-3914 - [c24]Michelle C. A. van Grinsven, Thom Scheeve, Ramon-Michel Schreuder, Fons van der Sommen, Erik J. Schoon, Peter H. N. de With:
Image Features for Automated Colorectal Polyp Classification Based on Clinical Prediction Models. ICIP 2019: 210-214 - [c23]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: 380-384 - [c22]Roger Fonollá, Fons van der Sommen, Ramon-Michel Schreuder, Erik J. Schoon, Peter H. N. de With:
Multi-Modal Classification of Polyp Malignancy using CNN Features with Balanced Class Augmentation. ISBI 2019: 74-78 - [c21]Farhad Ghazvinian Zanjani, Andreas Panteli, Svitlana Zinger, Fons van der Sommen, Tao Tan, Benjamin Balluff, D. R. Naomi Vos, Shane R. Ellis, Ron M. A. Heeren, Marit Lucas, Henk A. Marquering, Ivo G. H. Jansen, C. D. Savci-Heijink, Daniel M. de Bruin, Peter H. N. de With:
Cancer Detection in Mass Spectrometry Imaging Data by Recurrent Neural Networks. ISBI 2019: 674-678 - [c20]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: 1127-1131 - [c19]Thom Scheeve, Maarten R. Struyvenberg, Wouter L. Curvers, Albert J. de Groof, Erik J. Schoon, Jacques J. G. H. M. Bergman, Fons van der Sommen, Peter H. N. de With:
A novel clinical gland feature for detection of early Barrett's neoplasia using volumetric laser endomicroscopy. Medical Imaging: Computer-Aided Diagnosis 2019: 109501Y - [c18]Thom Scheeve, Ramon-Michel Schreuder, Fons van der Sommen, Joep E. G. IJspeert, Evelien Dekker, Erik J. Schoon, Peter H. N. de With:
Computer-aided classification of colorectal polyps using blue-light and linked-color imaging. Medical Imaging: Computer-Aided Diagnosis 2019: 1095012 - [c17]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: 169-177 - [c16]J. van Kersbergen, Farhad Ghazvinian Zanjani, Sveta Zinger, Fons van der Sommen, Benjamin Balluff, D. R. Naomi Vos, Shane R. Ellis, Ron M. A. Heeren, Marit Lucas, Henk A. Marquering, Ivo G. H. Jansen, C. D. Savci-Heijink, Daniel M. de Bruin, Peter H. N. de With:
Cancer detection in mass spectrometry imaging data by dilated convolutional neural networks. Medical Imaging: Digital Pathology 2019: 109560I - [c15]Francesca Manni, Fons van der Sommen, Sveta Zinger, Esther Kho, Susan G. Brouwer de Koning, Theo Ruers, Caifeng Shan, Jean Schleipen, Peter H. N. de With:
Automated tumor assessment of squamous cell carcinoma on tongue cancer patients with hyperspectral imaging. Medical Imaging: Image-Guided Procedures 2019: 109512K - [c14]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: 109492J - 2018
- [j2]Fons van der Sommen, Sander Klomp, Anne-Fré Swager, Svitlana Zinger, Wouter L. Curvers, Jacques J. Bergman, Erik J. Schoon, Peter H. N. de With:
Predictive features for early cancer detection in Barrett's esophagus using Volumetric Laser Endomicroscopy. Comput. Medical Imaging Graph. 67: 9-20 (2018) - [c13]Joost van der Putten, Fons van der Sommen, Svitlana Zinger, Daniel M. de Bruin, Guido Kamphuis, Peter H. N. de With:
Bladder Cancer Segmentation on Multispectral Images. ICDSC 2018: 13:1-13:4 - [c12]Sjors van Riel, Fons van der Sommen, Sveta Zinger, Erik J. Schoon, Peter H. N. de With:
Automatic Detection of Early Esophageal Cancer with CNNS Using Transfer Learning. ICIP 2018: 1383-1387 - [c11]Joost van der Putten, Svitlana Zinger, Fons van der Sommen, Peter H. N. de With, Mathias Prokop, John Hermans:
Quantitative CT based radiomics as predictor of resectability of pancreatic adenocarcinoma. Medical Imaging: Computer-Aided Diagnosis 2018: 105753O - [c10]Annika Reinke, Matthias Eisenmann, Sinan Onogur, Marko Stankovic, Patrick Scholz, Peter M. Full, Hrvoje Bogunovic, Bennett A. Landman, Oskar Maier, Bjoern H. Menze, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Fons van der Sommen, Guoyan Zheng, Henning Müller, Michal Kozubek, Tal Arbel, Andrew P. Bradley, Pierre Jannin, Annette Kopp-Schneider, Lena Maier-Hein:
How to Exploit Weaknesses in Biomedical Challenge Design and Organization. MICCAI (4) 2018: 388-395 - [i2]Lena Maier-Hein, Matthias Eisenmann, Annika Reinke, Sinan Onogur, Marko Stankovic, Patrick Scholz, Tal Arbel, Hrvoje Bogunovic, Andrew P. Bradley, Aaron Carass, Carolin Feldmann, Alejandro F. Frangi, Peter M. Full, Bram van Ginneken, Allan Hanbury, Katrin Honauer, Michal Kozubek, Bennett A. Landman, Keno März, Oskar Maier, Klaus H. Maier-Hein, Bjoern H. Menze, Henning Müller, Peter F. Neher, Wiro J. Niessen, Nasir M. Rajpoot, Gregory C. Sharp, Korsuk Sirinukunwattana, Stefanie Speidel, Christian Stock, Danail Stoyanov, Abdel Aziz Taha, Fons van der Sommen, Ching-Wei Wang, Marc-André Weber, Guoyan Zheng, Pierre Jannin, Annette Kopp-Schneider:
Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions. CoRR abs/1806.02051 (2018) - 2017
- [c9]Alexandros Rikos, Fons van der Sommen, Anne-Fré Swager, Svitlana Zinger, Erik J. Schoon, Wouter L. Curvers, Jacques J. Bergman, Peter H. N. de With:
Improved Barrett's Cancer Detection in Volumetric Laser Endomicroscopy Scans Using Multiple-Frame Voting. CBMS 2017: 708-713 - [c8]Sander Klomp, Fons van der Sommen, Anne-Fré Swager, Svitlana Zinger, Erik J. Schoon, Wouter L. Curvers, Jacques J. Bergman, Peter H. N. de With:
Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging. Medical Imaging: Computer-Aided Diagnosis 2017: 101340D - [i1]Kees A. Schouhamer Immink, Stan Baggen, Ferdaous Chaabane, Yanling Chen, Peter H. N. de With, Héla Gassara, Hamed Gharbi, Adel Ghazel, Khaled Grati, Naira M. Grigoryan, Ashot N. Harutyunyan, Masayuki Imanishi, Mitsugu Iwamoto, Ken-ichi Iwata, Hiroshi Kamabe, Brian M. Kurkoski, Shigeaki Kuzuoka, Patrick Langenhuizen, Jan Lewandowsky, Akiko Manada, Shigeki Miyake, Hiroyoshi Morita, Jun Muramatsu, Safa Najjar, Arnak V. Poghosyan, Fatma Rouissi, Yuta Sakai, Ulrich Tamm, Joost van der Putten, Fons van der Sommen, A. J. Han Vinck, Tadashi Wadayama, Dirk Wübben, Hirosuke Yamamoto:
Proceedings of Workshop AEW10: Concepts in Information Theory and Communications. CoRR abs/1707.08567 (2017) - 2016
- [c7]Norbertus Christianus van Dongen, Fons van der Sommen, Svitlana Zinger, Erik J. Schoon, Peter H. N. de With:
Automatic assessment of informative frames in endoscopic video. ISBI 2016: 119-122 - [c6]Markus H. A. Janse, Fons van der Sommen, Svitlana Zinger, Erik J. Schoon, Peter H. N. de With:
Early esophageal cancer detection using RF classifiers. Medical Imaging: Computer-Aided Diagnosis 2016: 97851D - [c5]Fons van der Sommen, Svitlana Zinger, Erik J. Schoon, Peter H. N. de With:
Sweet-spot training for early esophageal cancer detection. Medical Imaging: Computer-Aided Diagnosis 2016: 97851B - [c4]Fons van der Sommen, Sveta Zinger, Peter H. N. de With:
Accurate biopsy-needle depth estimation in limited-angle tomography using multi-view geometry. Medical Imaging: Image-Guided Procedures 2016: 97860D - 2015
- [c3]Martin A. R. Pieck, Fons van der Sommen, Svitlana Zinger, Peter H. N. de With:
Real-time semantic context labeling for image understanding. ICIP 2015: 3180-3184 - 2014
- [j1]Fons van der Sommen, Svitlana Zinger, Erik J. Schoon, Peter H. N. de With:
Supportive automatic annotation of early esophageal cancer using local gabor and color features. Neurocomputing 144: 92-106 (2014) - 2013
- [c2]Fons van der Sommen, Svitlana Zinger, Erik J. Schoon, Peter H. N. de With:
Computer-aided detection of early cancer in the esophagus using HD endoscopy images. Medical Imaging: Computer-Aided Diagnosis 2013: 86700V - [c1]Arnaud A. A. Setio, Fons van der Sommen, Svitlana Zinger, Erik J. Schoon, Peter H. N. de With:
Evaluation and Comparison of Textural Feature Representation for the Detection of Early Stage Cancer in Endoscopy. VISAPP (1) 2013: 238-243
Coauthor Index
Jacques J. Bergman
aka: Jacques J. G. H. M. Bergman
aka: Jacques J. G. H. M. Bergman
T. G. W. Boers
aka: Tim Boers
aka: Tim Boers
Kiki Fockens
aka: Kiki N. Fockens
aka: Kiki N. Fockens
Jelmer Jukema
aka: Jelmer B. Jukema
aka: Jelmer B. Jukema
Joost van der Putten
aka: Joost A. van der Putten
aka: Joost A. van der Putten
[j19] [j18] [j17] [j16] [j15] [c72] [c71] [c70] [c69] [c68] [c67] [c66] [c65] [c64] [c63] [i16] [i15] [i14] [i13] [i12] [j14] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [i11] [i10] [i9] [i8] [i7] [j13] [j12] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [i6] [i5] [i4] [j11] [j10] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [i3] [j9] [j8] [j7] [j6] [j5] [j4] [j3] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [j2] [c13] [c12] [c11] [c9] [c8] [i1] [c7] [c6] [c5] [c4] [c3] [j1] [c2] [c1]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-07 20:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
