Research Output per year
Personal profile
Quote
In the fight against cancer, we need to make sure the medical specialists have the right 'weapons'.
Research profile
Fons van der Sommen is an assistant professor at the research group Video Coding & Architectures of the department of Electrical Engineering. He is a passionate scientist and educator, holding a MSc. in Electrical Engineering (2012, cum laude) and a PhD in Computer Vision (2017, cum laude). Driven by a personal tragedy, a passion for science and a desire to contribute to this world, he applies his understanding of machine learning and computer vision in healthcare, where he aims to develop novel assistive technologies for medical doctors, helping them with early diagnosis and effective treatment of disease.
In particular, in the field of Medical Image Analysis, Van der Sommen's research focuses on Computer-Aided Detection and Diagnosis (CADe/CADx) for oncology, striving to increase the detection rates and early diagnosis of developing cancer -- thereby vastly increasing the chances of survival for patients. Towards this goal, he works closely with medical specialists in an interdisciplinary team, aiming to translate medical domain knowledge into technical algorithms and vice versa.
Academic background
Fons van der Sommen studied Electrical Engineering at Eindhoven University of Technology (TU/e, the Netherlands) where he obtained his MSc in 2012 with the distinction cum laude. The year before his father had died of cancer, with motivated him to investigate the feasibility of an algorithm for the computer-aided detection of esophageal cancer. This resulted in three publications on international conferences. Following his Master's studies Van der Sommen continued to work on computer vision methods for esophageal cancer detection in collaboration with the Catharina Hospital (Eindhoven) while pursuing a PhD degree. In 2017 he obtained his doctorate with his thesis 'Computer-aided detection of early Barrett's cancer', again with the distinction cum laude. In 2018, after having been a postdoctoral researcher at TU/e for a year, he was appointed assistant professor at the research group Video Coding & Architectures of the TU/e department of Electrical Engineering. That same year he was awarded the TU/e PhD thesis prize.
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- 6 Similar Profiles
Barrett Esophagus
Medicine & Life Sciences
Endoscopy
Engineering & Materials Science
Neoplasms
Medicine & Life Sciences
Lasers
Medicine & Life Sciences
Tissue
Engineering & Materials Science
Imaging techniques
Engineering & Materials Science
Color
Engineering & Materials Science
Biopsy
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2012 2020
Deep learning algorithm detection of Barrett's neoplasia with high accuracy during live endoscopic procedures: a pilot study (with video)
de Groof, A. J., Struyvenberg, M. R., Fockens, K. N., van der Putten, J., van der Sommen, F., Boers, T. G., Zinger, S., Bisschops, R., de With, P. H., Pouw, R. E., Curvers, W. L., Schoon, E. J. & Bergman, J. J. G. H. M., 9 Jan 2020, In : Gastrointestinal Endoscopy.Research output: Contribution to journal › Article › Academic › peer-review
Learning
Neoplasms
Barrett Esophagus
Sensitivity and Specificity
Endoscopy
1
Citation
(Scopus)
2
Downloads
(Pure)
A novel clinical gland feature for detection of early Barrett’s neoplasia using volumetric laser endomicroscopy
Scheeve, T., Struyvenberg, M. R., Curvers, W. L., de Groof, J., Schoon, E. J., Bergman, J. J. G. H. M., van der Sommen, F. & de With, P. H. N., 13 Mar 2019, Medical Imaging 2019: Computer-Aided Diagnosis: Computer-Aided Diagnosis. Mori, K. & Hahn, H. K. (eds.). Bellingham: SPIE, 6 p. 10950-70. (Proceedings of SPIE; vol. 10950).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
esophagus
glands
Barrett Esophagus
Lasers
histograms
2
Citations
(Scopus)
16
Downloads
(Pure)
Author correction: Why rankings of biomedical image analysis competitions should be interpreted with care (Nature Communications, (2018), 9, 1, (5217), 10.1038/s41467-018-07619-7)
Maier-Hein, L., Eisenmann, M., Reinke, A., Onogur, S., Stankovic, M., Scholz, P., Arbel, T., Bogunovic, H., Bradley, A. P., Carass, A., Feldmann, C., Frangi, A. F., Full, P. M., van Ginneken, B., Hanbury, A., Honauer, K., Kozubek, M., Landman, B. A., März, K., Maier, O. & 18 others, , 1 Dec 2019, In : Nature Communications. 10, 1, 2 p., 588.Research output: Contribution to journal › Comment/Letter to the editor › Academic › peer-review
Open Access
File
HTML
ranking
image analysis
Image analysis
communication
2
Citations
(Scopus)
Automated tumor assessment of squamous cell carcinoma on tongue cancer patients with hyperspectral imaging
Manni, F., van der Sommen, F., Zinger, S., Kho, E., Brouwer de Koning, S., Ruers, T., Shan, C., Schleipen, J. & de With, P., 8 Mar 2019, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. Fei, B. & Linte, C. A. (eds.). Bellingham: SPIE, 7 p. 109512K. (Proceedings of SPIE; vol. 10951).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Tongue Neoplasms
Squamous Cell Carcinoma
Neoplasms
Computer-Assisted Surgery
Nasal Cavity
Cancer detection in mass spectrometry imaging data by dilated convolutional neural networks
van Kersbergen, J., Ghazvinian Zanjani, F., Zinger, S., van der Sommen, F., Balluff, B., Vos, D. R. N., Ellis, S. R., Heeren, R. M. A., Lucas, M., Marquering, H. A., Jansen, I., Savci-Heijink, C. D., de Bruin, D. M. & de With, P. H. N., 18 Mar 2019, Medical Imaging 2019: Digital Pathology. Tomaszewski, J. E. & Ward, A. D. (eds.). SPIE, 8 p. 1095601. (Proceedings of SPIE; vol. 10956).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Mass spectrometry
Tumors
Neural networks
Imaging techniques
Molecular imaging
Prizes
Best Poster Presentation
Fons van der Sommen (Recipient), 10 May 2017
Prize: Other › Career, activity or publication related prizes (lifetime, best paper, poster etc.) › Scientific
Best Poster Presentation
Fons van der Sommen (Recipient), 18 Jun 2013
Prize: Other › Career, activity or publication related prizes (lifetime, best paper, poster etc.) › Scientific
TU/e Best PhD Thesis Award
Fons van der Sommen (Recipient), 21 Sep 2018
Prize: TU/e › Other › Scientific
Activities 2013 2019
- 4 Contributed talk
A novel clinical gland feature for detection of early Barrett’s neoplasia using volumetric laser endomicroscopy
Thom Scheeve (Speaker), Maarten R. Struyvenberg (Member), Wouter L. Curvers (Member), Jeroen de Groof (Member), Erik J. Schoon (Member), Jacques J.G.H.M. Bergman (Member), F. van der Sommen (Member), P.H.N. de With (Member)20 Feb 2019
Activity: Talk or presentation types › Contributed talk › Scientific
Computer-aided classification of colorectal polyps using blue-light and linked-color imaging
Thom Scheeve (Speaker), Ramon-Michel Schreuder (Member), Fons van der Sommen (Member), Joep E.G. IJspeert (Member), Evelien Dekker (Member), Erik J. Schoon (Member), P.H.N. de With (Member)18 Feb 2019
Activity: Talk or presentation types › Contributed talk › Scientific
Computer-aided classification of colorectal polyps
Thom Scheeve (Speaker), Ramon-Michel Schreuder (Member), F. van der Sommen (Member), Erik J. Schoon (Member), P.H.N. de With (Member)5 Apr 2018
Activity: Talk or presentation types › Contributed talk › Scientific
Voorjaarsvergadering Nederlandse Vereniging voor Gastroenterologie, Koningshof, Veldhoven, the Netherlands
Fons van der Sommen (Speaker)22 Mar 2013
Activity: Talk or presentation types › Contributed talk › Scientific
Courses
Press / Media
New method uses computer to scan esophagus images for signs of esophageal cancer
Peter H.N. de With & Fons van der Sommen
5/07/16
1 item of Media coverage
Press/Media: Expert Comment
New detection method paves the way for 100 percent detection of esophageal cancer
Peter H.N. de With & Fons van der Sommen
5/07/16
1 item of Media coverage
Press/Media: Expert Comment
New detection method paves the way for 100% detection of esophageal cancer
Peter H.N. de With & Fons van der Sommen
5/07/16
1 item of Media coverage
Press/Media: Expert Comment
New detection method paves the way for 100 percent detection of esophageal cancer Eindhoven University of Technology 11m
Peter H.N. de With & Fons van der Sommen
5/07/16
1 item of Media coverage
Press/Media: Expert Comment
Nieuwe opsporingsmethode moet overlevingskans slokdarmkanker vergroten
4/07/16
1 Media contribution
Press/Media: Research
Student theses
Automatic detection of early cancer in the esophagus using high-definition endoscopy
Author: van der Sommen, F., 31 Aug 2012Supervisor: Zinger, S. (Supervisor 1), de With, P. (Supervisor 2) & Schoon, E. J. (External person) (External coach)
Student thesis: Master
Computer-aided classification of colorectal polyps
Author: Scheeve, T., 29 Mar 2018Supervisor: van der Sommen, F. (Supervisor 1) & Schoon, E. J. (External person) (External coach)
Student thesis: Master
Image features for automated colorectal polyp classification based on clinical prediction models
Author: van Grinsven, M., 13 Dec 2018Supervisor: de With, P. (Supervisor 1) & van der Sommen, F. (Supervisor 2)
Student thesis: Master