Tim Houben
Eindhoven University of Technology
6 Papers
14 Citations
Tim Houben is an academic researcher from Eindhoven University of Technology. The author has contributed to research in topics: Computer science & Metrology. The author has an hindex of 2, co-authored 3 publications.
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Papers
One-class Gaussian process regressor for quality assessment of transperineal ultrasound images
Saskia Camps,Tim Houben,Davide Fontanarosa,Christopher Edwards,Maria Antico,Matteo Dunnhofer,E.G.H.J. Martens,Jose A Baeza,Ben G. L. Vanneste,Evert J. Van Limbergen,Frank Verhaegen,Gustavo Carneiro +11 more
- 11 Apr 2018
TL;DR: A one-class regressor, based on DenseNet and Gaussian processes, was implemented to assess automatically the quality of transperineal ultrasound images of the male pelvic region, which achieved a scoring accuracy, specificity and sensitivity that was comparable with those of experts.
Quality Assessment of Transperineal Ultrasound Images of the Male Pelvic Region Using Deep Learning
Saskia Camps,Tim Houben,Christopher Edwards,Maria Antico,Matteo Dunnhofer,E.G.H.J. Martens,Jose A Baeza,Hen Vanneste,Evert J. Van Limbergen,Frank Verhaegen,Gustavo Carneiro,Davide Fontanarosa +11 more
- 01 Oct 2018
TL;DR: A prototype deep learning algorithm is introduced that can automatically assign a quality score to 2D US images of the male pelvic region based on their usability during an ultrasound guided radiotherapy workflow and it has been shown that the performance of this algorithm is comparable with a medical accredited sonographer and two radiation oncologists.
Training procedure for scanning electron microscope 3D surface reconstruction using unsupervised domain adaptation with simulated data
TL;DR: In this article , a data-driven approach that predicts the dimensions, height and width (CD) values, of fin-like structures was proposed. But, the method only requires experimental images from a scanning electron microscope of the patterns concerned.
3
Depth estimation from SEM images using deep learning and angular data diversity
Tim Houben,Maxim Pisarenco,T.J. Huisman,H. Onvlee,F. van der Sommen,P. D. De with +5 more
- 27 Apr 2023
TL;DR: In this paper , the authors presented a comprehensive study of depth estimation performance when single or multi-angle data is available, and showed that a data-driven tilted-beam approach is a leap forward in accurate height prediction for the semiconductor industry.
2
Automatic Quality Assessment of Transperineal Ultrasound Images of the Male Pelvic Region, Using Deep Learning.
Saskia Camps,Saskia Camps,Tim Houben,Gustavo Carneiro,Christopher Edwards,Maria Antico,Matteo Dunnhofer,E.G.H.J. Martens,Jose A Baeza,Ben G. L. Vanneste,E.J. van Limbergen,Frank Verhaegen,Davide Fontanarosa +12 more
TL;DR: A one-class regressor, based on DenseNet and Gaussian processes, was implemented to automatically assess the quality of transperineal ultrasound images of the male pelvic region, which could potentially remove the need for ultrasound image interpretation and make real-time volumetric organ tracking in the radiotherapy environment using ultrasound more appealing.