Prof. Peter H. N. de With Profile

Prof. Peter H. N. de With

Professor at Eindhoven Univ. of Technology

SPIE Involvement:

Author

Publications (139)

Proceedings Article | 2 April 2024 Presentation + Paper

Unsupervised cell segmentation by invariant information clustering

Wessel van Nierop, Jan-N. Schneider, Peter H. de With, Fons van der Sommen

Proceedings Volume 12926, 129260V (2024) https://doi.org/10.1117/12.3001442

KEYWORDS: Live cell imaging, Machine learning, Deep learning, Information theory, Image segmentation, Data modeling, Performance modeling, Tunable filters, Ablation, Microscopy, Semantics, Transform theory, Image filtering

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Proceedings Article | 2 April 2024 Poster + Paper

Evaluating task-specific augmentations in self-supervised pre-training for 3D medical image analysis

C. H. Claessens, J. J. M. Hamm, C. G. Viviers, J. Nederend, D. Grünhagen, P. Tanis, P. H. de With, F. van der Sommen

Proceedings Volume 12926, 129261L (2024) https://doi.org/10.1117/12.3000850

KEYWORDS: Medical imaging, 3D image processing, 3D modeling, Lung, Education and training, Image segmentation, Voxels, Tumors, Image classification

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Proceedings Article | 2 April 2024 Poster + Paper

Robustness evaluation of CAD systems for lung nodule segmentation using clinically relevant image perturbations

Fidan Mammadli, Terese A. Hellström, Christiaan G. Viviers, Igor Jacobs, Lotte J. Ewals, Nick Tasios, Dimitrios Mavroeidis, Hendrika P. Verhees, Peter H. de With, Joost Nederend, Fons van der Sommen

Proceedings Volume 12926, 1292628 (2024) https://doi.org/10.1117/12.3006211

KEYWORDS: Motion models, Lung, Computed tomography, Data modeling, Image segmentation, CT reconstruction, Artificial intelligence, Simulations, Performance modeling, Cancer detection

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Proceedings Article | 7 June 2023 Paper

Floor-plan generation from noisy point clouds

Xin Liu, Egor Bondarev, Peter H. de With

Proceedings Volume 12701, 1270111 (2023) https://doi.org/10.1117/12.2679358

KEYWORDS: Buildings, Point clouds, Semantics, 3D modeling, Tunable filters, Principal component analysis, Stereoscopic cameras, Image segmentation, Sensors

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SPIE Journal Paper | 28 April 2023 Open Access

Training procedure for scanning electron microscope 3D surface reconstruction using unsupervised domain adaptation with simulated data

Tim Houben, Thomas Huisman, Maxim Pisarenco, Fons van der Sommen, Peter de With

JM3, Vol. 22, Issue 03, 031208, (April 2023) https://doi.org/10.1117/12.10.1117/1.JMM.22.3.031208

KEYWORDS: Scanning electron microscopy, Education and training, Semiconducting wafers, Electron microscopes, 3D scanning, Data modeling, Critical dimension metrology, Scatterometry, 3D metrology, 3D modeling

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Proceedings Article | 27 April 2023 Poster + Presentation + Paper

Depth estimation from SEM images using deep learning and angular data diversity

Tim Houben, Maxim Pisarenco, Thomas Huisman, Hans Onvlee, Fons van der Sommen, Peter de With

Proceedings Volume 12496, 124961E (2023) https://doi.org/10.1117/12.2658094

KEYWORDS: Scanning electron microscopy, Line scan image sensors, Education and training, Simulations, Analytic models, Monte Carlo methods, Electron beams, Neural networks, Image analysis, Silicon

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Proceedings Article | 7 April 2023 Presentation + Paper

Probabilistic 3D segmentation for aleatoric uncertainty quantification in full 3D medical data

Christiaan G. Viviers, M. M. Amaan Valiuddin, Peter H. de With, Fons van der Sommen

Proceedings Volume 12465, 124651I (2023) https://doi.org/10.1117/12.2654255

KEYWORDS: Measurement uncertainty, Deep convolutional neural networks, Spatial data uncertainty, 3D modeling, Education and training, Image segmentation, Computed tomography, Lung, 3D image processing, Voxels, Computer aided detection

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Proceedings Article | 7 April 2023 Poster + Paper

Clinical segmentation for improved pancreatic ductal adenocarcinoma detection and segmentation

Terese A. Hellström, Christiaan G. Viviers, Mark Ramaekers, Nick Tasios, Joost Nederend, Misha D. Luyer, Peter H. de With, Fons van der Sommen

Proceedings Volume 12465, 124652M (2023) https://doi.org/10.1117/12.2654164

KEYWORDS: Tumors, Cancer detection, Image segmentation, Pancreas, 3D modeling, Computed tomography, Performance modeling, Pancreatic cancer, Artificial intelligence, Education and training

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Proceedings Article | 7 April 2023 Poster + Paper

Barrett's lesion detection using a minimal integer-based neural network for embedded systems integration

Tim G. Boers, Carolus H. Kusters, Kiki Fockens, Jelmer Jukema, Martijn Jong, Jeroen de Groof, Jacques Bergman, Fons van der Sommen, Peter H. de With

Proceedings Volume 12465, 1246527 (2023) https://doi.org/10.1117/12.2653890

KEYWORDS: Quantization, Image segmentation, Neural networks, Embedded systems

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Proceedings Article | 7 April 2023 Presentation + Paper

Effect of domain-specific self-supervised pretraining on predictive uncertainty for colorectal polyp characterization

N. Dehghani, T. Scheeve, T. G. Boers, Q. E. van der Zander, A. Thijssen, R. Schreuder, A. A. Masclee, E. Schoon, F. van der Sommen, P. H. de With

Proceedings Volume 12465, 124651G (2023) https://doi.org/10.1117/12.2653848

KEYWORDS: Calibration, Polyps, Performance modeling, Computer aided detection, Reliability, Medical imaging, Endoscopy, Network architectures, Image classification

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Proceedings Article | 7 April 2023 Poster + Paper

Real-time Barrett's neoplasia characterization in NBI videos using an int8-based quantized neural network

Carolus H. Kusters, Tim G. Boers, Jelmer Jukema, Martijn Jong, Kiki Fockens, Albert de Groof, Jacques Bergman, Fons van der Sommen, Peter H. de With

Proceedings Volume 12465, 124651P (2023) https://doi.org/10.1117/12.2647557

KEYWORDS: Computer aided detection, Endoscopy

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Proceedings Article | 7 April 2023 Presentation + Paper

How does image quality affect computer-aided diagnosis of colorectal polyps?

Thom Scheeve, Nikoo Dehghani, Quirine E. van der Zander, Ayla Thijssen, Ramon-Michel Schreuder, Ad A. Masclee, Erik Schoon, Fons van der Sommen, Peter H. de With

Proceedings Volume 12465, 124650S (2023) https://doi.org/10.1117/12.2654167

KEYWORDS: Image quality, Endoscopy, Polyps, Cancer, Colorectal cancer, Clinical practice, Deep learning, Distortion

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Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths with rising incidence. Since the survival rate of CRC is correlated with the cancer stage at diagnosis, timely detection and adequate treatment strategies are of utmost importance. Technical innovations such as machine learning (ML) and its application in endoscopy show promising results, but the trust of medical doctors in ML is lacking and the ‘black box’ nature complicates the understanding of such systems in clinical practice. In contrast to CT and MRI, image quality is a limiting factor in especially endoscopic imaging, as it is very operator dependent. However, the influence of image quality on convolutional (deep) neural networks (CNNs) is insufficiently studied in relation to clinical practice and the usage of medical image data for computer-aided detection and diagnosis (CADx) systems. This paper explores the influence of degraded image quality on the performance of CNNs applied to colorectal polyp (CRP) characterization. Five commonly used CNN architectures, from simple to more complex, are employed with a custom classification head for common CRP characterization. To degrade the quality of images, distortions such as noise, blur, and contrast changes are imposed on the data and their influence on the performance degradation is studied for the mentioned CNN architectures. A large prospectively collected in vivo data set, gathered from four Dutch, both academic and community, hospitals is employed. Results for CRP characterization show that promising CNN-based methods are rather susceptible to noise and blur distortions but reasonably resilient to changes in contrast. This implies that image quality needs monitoring and control prior to directly using image data in CNN models, in order to gain trustworthy use of deep learning (DL) models in a clinical setting. We propose that incorporating an image quality indicator in CADx systems will lead to better acceptance of such systems, and is necessary for the safe implementation of DL applications in clinical practice.

Proceedings Article | 4 April 2022 Poster + Paper

Colorectal polyp classification using confidence-calibrated convolutional neural networks

Koen Kusters, Thom Scheeve, Nikoo Dehghani, Quirine E. van der Zander, Ramon-Michel Schreuder, Ad A. Masclee, Erik Schoon, Fons van der Sommen, Peter H. de With

Proceedings Volume 12033, 120331P (2022) https://doi.org/10.1117/12.2606801

KEYWORDS: Calibration, Reliability, Error control coding, Computer aided diagnosis and therapy, Convolutional neural networks, Systems modeling, Electrochemical etching, In vivo imaging, Endoscopy, Cancer

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Computer-Aided Diagnosis (CADx) systems for in-vivo characterization of Colorectal Polyps (CRPs) which are precursor lesions of Colorectal Cancer (CRC), can assist clinicians with diagnosis and better informed decisionmaking during colonoscopy procedures. Current deep learning-based state-of-the-art solutions achieve a high classification performance, but lack measures to increase the reliability of such systems. In this paper, the reliability of a Convolutional Neural Network (CNN) for characterization of CRPs is specifically addressed by confidence calibration. Well-calibrated models produce classification-confidence scores that reflect the actual correctness likelihood of the model, thereby supporting reliable predictions by trustworthy and informative confidence scores. Two recently proposed trainable calibration methods are explored for CRP classification to calibrate the confidence of the proposed CNN. We show that the confidence-calibration error can be decreased by 33.86% (−0.01648 ± 0.01085), 48.33% (−0.04415 ± 0.01731), 50.57% (−0.11423 ± 0.00680), 61.68% (−0.01553 ± 0.00204) and 48.27% (−0.22074 ± 0.08652) for the Expected Calibration Error (ECE), Average Calibration Error (ACE), Maximum Calibration Error (MCE), Over-Confidence Error (OE) and Cumulative Calibration Error (CUMU), respectively. Moreover, the absolute difference between the average entropy and the expected entropy was considerably reduced by 32.00% (−0.04374 ± 0.01238) on average. Furthermore, even a slightly improved classification performance is observed, compared to the uncalibrated equivalent. The obtained results show that the proposed model for CRP classification with confidence calibration produces better calibrated predictions without sacrificing classification performance. This work shows promising points of engagement towards obtaining reliable and well-calibrated CADx systems for in-vivo polyp characterization, to assist clinicians during colonoscopy procedures.

Proceedings Article | 4 April 2022 Presentation + Paper

Efficient endoscopic frame informativeness assessment by reusing the encoder of the primary CAD task

Fidan Mammadli, Fons van der Sommen, Tim Boers, Joost van der Putten, Kiki Fockens, Jelmer Jukema, Martijn de Jong, Jacques J.G.H.M. Bergman, Peter H. de With

Proceedings Volume 12033, 120331C (2022) https://doi.org/10.1117/12.2611133

KEYWORDS: Convolutional neural networks, Computer aided diagnosis and therapy, Computer vision technology, Artificial intelligence, Artificial neural networks, Endoscopy, CAD systems, Image quality, Algorithm development, Network architectures, Video, Detection and tracking algorithms

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Towards real-time 6D pose estimation of objects in single-view cone-beam x-ray

Christiaan G. A. Viviers, Joël de Bruijn, Lena Filatova, Peter H. de With, Fons van der Sommen

Proceedings Volume 12034, 120341V (2022) https://doi.org/10.1117/12.2611143

KEYWORDS: X-rays, X-ray imaging, 3D modeling, Systems modeling, Medical imaging, Computer simulations, Image classification, Machine learning, Machine vision, Image guided radiation therapy, 3D applications

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Proceedings Article | 5 March 2022 Paper

Depth estimation from a single CD-SEM image using domain adaptation with multimodal data

Tim Houben, Thomas Huisman, Maxim Pisarenco, Fons van der Sommen, Peter de With

Proceedings Volume 12084, 120841I (2022) https://doi.org/10.1117/12.2622635

KEYWORDS: Data modeling, 3D modeling, Semiconducting wafers, Monte Carlo methods, Neural networks, Metrology, Semiconductors, Scanning electron microscopy, 3D metrology, Sensors

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Proceedings Article | 15 February 2021 Presentation + Paper

Video-based infant monitoring using a CNN-LSTM scheme

Lan Min, Yue Sun, Peter H. de With

Proceedings Volume 11597, 1159717 (2021) https://doi.org/10.1117/12.2581026

KEYWORDS: Video, Feature extraction, Convolutional neural networks, Brain

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Augmented-reality visualization for improved patient positioning workflow during MR-HIFU therapy

Francesca Manni, Cyril Ferrer, Celine E. Vincent, Marco Lai, Lambertus W. Bartels, Clemens Bos, Fons van der Sommen, Peter H. N. de With

Proceedings Volume 11598, 115982C (2021) https://doi.org/10.1117/12.2580838

KEYWORDS: Visualization, Magnetic resonance imaging, Augmented reality, Image fusion, Cameras, Ultrasonography, Tissues, Scanners, Medical imaging, Bone

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Proceedings Article | 15 February 2021 Presentation + Paper

Evaluation of a non-contact Photo-Plethysmographic Imaging (iPPG) system for peripheral arterial disease assessment

Marco Lai, Claudio Spiridione Dicorato, Marco de Wild, Frank Verbakel, Sergei Shulepov, Joanneke Groen, Marc Notten, Gerald Lucassen, Marc R. H. van Sambeek, Benno H. Hendriks, Peter H. de With

Proceedings Volume 11600, 116000F (2021) https://doi.org/10.1117/12.2580640

KEYWORDS: Imaging systems, Skin, Arteries, Ultrasonography, Standards development, Gold, Doppler effect, Blood, Surgery, Speckle

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Fast tissue detection in volumetric laser endomicroscopy using convolutional neural networks: an object-detection approach

Endi Selmanaj, Fons van der Sommen, Sanne Okel, Joost van der Putten, Maarten Struyvenberg, Jacques J. G. H. M. Bergman, Peter H. de With

Proceedings Volume 11596, 1159635 (2021) https://doi.org/10.1117/12.2579573

KEYWORDS: Tissues, Laser tissue interaction, Endomicroscopy, Convolutional neural networks, Esophagus, Cancer, New and emerging technologies, Network architectures, Laser applications, Computer-aided diagnosis

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Proceedings Article | 15 February 2021 Presentation + Paper

Development of a CT-compatible anthropomorphic skull phantom for surgical planning, training, and simulation

Marco Lai, Simon Skyrman, Flip Kor, Robert Homan, Drazenko Babic, Erik Edström, Oscar Persson, Gustav Burström, Adrian Elmi-Terander, Benno H. Hendriks, Peter H. de With

Proceedings Volume 11601, 116010A (2021) https://doi.org/10.1117/12.2577629

KEYWORDS: Skull, Surgery, Brain, Image segmentation, Biopsy, Virtual reality, Navigation systems, Magnetic resonance imaging, Computed tomography, Calcium

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Tissue-border detection in volumetric laser endomicroscopy using bi-directional gated recurrent neural networks

Sanne Okel, Fons van der Sommen, Endi Selmanaj, Joost van der Putten, Maarten Struyvenberg, Jacques J.G.H.M. Bergman, Peter H. de With

Proceedings Volume 11597, 115972H (2021) https://doi.org/10.1117/12.2579751

KEYWORDS: Image segmentation, Tissues, Neural networks, Endomicroscopy, Laser tissue interaction, Solid modeling, Computer aided diagnosis and therapy, Esophagus, Convolutional neural networks, Computer aided design

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Iterative reconstruction anti-correlated ROF model for noise reduction in dual-energy CBCT imaging

Luis A. Zavala-Mondragon, Klaus Juergen Engel, Bernd Menser, Danny Ruijters, Peter H. de With, Fons van der Sommen

Proceedings Volume 11596, 115962G (2021) https://doi.org/10.1117/12.2579500

KEYWORDS: Denoising, Radio over Fiber, Dual energy imaging, Reconstruction algorithms, Neuroimaging, Brain, X-rays, Visible radiation, Signal attenuation, Photon counting

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Proceedings Article | 15 February 2021 Presentation + Paper

Hyperspectral imaging for tissue classification in glioblastoma tumor patients: a deep spectral-spatial approach

Francesca Manni, Chuchen Cai, Fons van der Sommen, Svitlana Zinger, Caifeng Shan, Erik Edström, Adrian Elmi-Terander, Himar Fabelo, Samuel Ortega, Gustavo Callicó, Peter H. de With

Proceedings Volume 11598, 1159810 (2021) https://doi.org/10.1117/12.2580158

KEYWORDS: Tumors, Hyperspectral imaging, Tissue optics, Tissues, Surgery, Statistical analysis, Optical imaging, In vivo imaging, Image classification, Brain

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Proceedings Article | 15 February 2021 Poster + Presentation + Paper

Triplet network for classification of benign and pre-malignant polyps

Roger Fonollà, Maciej Smyl, Fons van der Sommen, Ramon Schreuder, Erik Schoon, Peter H. de With

Proceedings Volume 11597, 1159731 (2021) https://doi.org/10.1117/12.2577546

KEYWORDS: Error control coding, Endoscopy, Visualization, Visual process modeling, Tumor growth modeling, Tissues, Safety, Network architectures, Laser imaging, Colorectal cancer

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SPIE Journal Paper | 22 June 2020

Toward robust multitype and orientation detection of vessels in maritime surveillance

Amir Ghahremani, Egor Bondarev, Peter H. de With

JEI, Vol. 29, Issue 03, 033015, (June 2020) https://doi.org/10.1117/12.10.1117/1.JEI.29.3.033015

KEYWORDS: Maritime surveillance, Sensors, Data modeling, Cameras, Image classification, Convolutional neural networks, Earth observing sensors, Satellites, Systems modeling, Surveillance systems

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Proceedings Article | 16 March 2020 Paper

Feasibility study of catheter segmentation in 3D Frustum ultrasounds by DCNN

Lan Min, Hongxu Yang, Caifeng Shan, Alexander Kolen, Peter H. de With

Proceedings Volume 11315, 1131521 (2020) https://doi.org/10.1117/12.2549084

KEYWORDS: Image segmentation, 3D image processing, Ultrasonography, 3D acquisition, Image filtering, Therapeutics, Binary data, Computer programming, Cardiac catheterization, Surgery

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Proceedings Article | 16 March 2020 Paper

Automated discomfort detection for premature infants in NICU using time-frequency feature-images and CNNs

Yue Sun, Deedee Kommers, Tao Tan, Wenjin Wang, Xi Long, Caifeng Shan, Carola van Pul, Ronald Aarts, Peter Andriessen, Peter H. de With

Proceedings Volume 11314, 113144B (2020) https://doi.org/10.1117/12.2549250

KEYWORDS: Video, Time-frequency analysis, Motion estimation, Optical flow, Signal processing, Convolutional neural networks, Image classification, Motion analysis, Image processing

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Proceedings Article | 16 March 2020 Paper

Automated classification of brain tissue: comparison between hyperspectral imaging and diffuse reflectance spectroscopy

Marco Lai, Simon Skyrman, Caifeng Shan, Elvira Paulussen, Francesca Manni, Akash Swamy, Drazenko Babic, Erik Edstrom, Oscar Persson, Gustav Burstrom, Adrian Elmi-Terander, Benno H. Hendriks, Peter H. de With

Proceedings Volume 11315, 113151X (2020) https://doi.org/10.1117/12.2548754

KEYWORDS: Brain, Tissues, Hyperspectral imaging, Tissue optics, Neuroimaging, Tumors, Sensors, Diffuse reflectance spectroscopy, Surgery, Imaging systems

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Proceedings Article | 16 March 2020 Paper

First steps into endoscopic video analysis for Barrett’s cancer detection: challenges and opportunities

Joost van der Putten, Jeroen de Groof, Fons van der Sommen, Maarten Struyvenberg, Svitlana Zinger, Wouter Curvers, Erik Schoon, Jacques Bergman, Peter H. de With

Proceedings Volume 11314, 1131431 (2020) https://doi.org/10.1117/12.2544229

KEYWORDS: Video, Video surveillance, Endoscopy, Cancer, Esophagus, Computer aided design, Image classification

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Proceedings Article | 16 March 2020 Paper

The field effect in Barrett's Esophagus: a macroscopic view using white light endoscopy and deep learning

Levi Verhage, Joost van der Putten, Fons van der Sommen, Jeroen de Groof, Maarten Struyvenberg, Peter H. de With

Proceedings Volume 11314, 1131437 (2020) https://doi.org/10.1117/12.2549391

KEYWORDS: Data modeling, Esophagus, Algorithm development, Tissues, Performance modeling, Endoscopy, Evolutionary algorithms, Computer aided diagnosis and therapy, Image segmentation, Image classification

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Proceedings Article | 10 March 2020 Presentation + Paper

Detection of frame informativeness in endoscopic videos using image quality and recurrent neural networks

T. G. W. Boers, J. van der Putten, J. de Groof, M. Struyvenberg, K. Fockens, W. Curvers, E. Schoon, F. van der Sommen, J. Bergman, P.H. de With

Proceedings Volume 11313, 1131315 (2020) https://doi.org/10.1117/12.2545734

KEYWORDS: Endoscopy, Image quality, Video, Neural networks, Artificial intelligence, Esophagus, Visualization, Image classification, Evolutionary algorithms, Binary data

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Proceedings Article | 10 March 2020 Presentation + Paper

Influence of decoder size for binary segmentation tasks in medical imaging

Joost van der Putten, Fons van der Sommen, Peter H. de With

Proceedings Volume 11313, 1131318 (2020) https://doi.org/10.1117/12.2542199

KEYWORDS: Image segmentation, Binary data, Medical imaging, Skin, Computer programming, Data modeling, RGB color model, Network architectures, Statistical modeling, Convolution

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Proceedings Article | 31 January 2020 Paper

Improving open-set person re-identification by statistics-driven gallery refinement

Tunc Alkanat, Egor Bondarev, Peter H. de With

Proceedings Volume 11433, 114330V (2020) https://doi.org/10.1117/12.2559441

KEYWORDS: Feature extraction, Cameras, Statistical analysis, Image retrieval, Principal component analysis, Electrical engineering, Surveillance systems

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SPIE Journal Paper | 12 July 2019

Development and analysis of a real-time system for automated detection of improvised explosive device indicators from ground vehicles

Dennis W. J. M. van de Wouw, Frank B. ter Haar, Gijs Dubbelman, Peter H. N. de With

JEI, Vol. 28, Issue 04, 043009, (July 2019) https://doi.org/10.1117/12.10.1117/1.JEI.28.4.043009

KEYWORDS: Improvised explosive devices, 3D modeling, Cameras, Real-time computing, Explosives detection, Imaging systems, RGB color model, Global Positioning System, Image processing, 3D image processing

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SPIE Journal Paper | 24 April 2019 Open Access

Impact of JPEG 2000 compression on deep convolutional neural networks for metastatic cancer detection in histopathological images

Farhad Ghazvinian Zanjani, Svitlana Zinger, Bastian Piepers, Saeed Mahmoudpour, Peter Schelkens, Peter H. de With

JMI, Vol. 6, Issue 02, 027501, (April 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.2.027501

KEYWORDS: Image compression, Data modeling, Solid modeling, Convolutional neural networks, Tumors, Performance modeling, CAD systems, Computer aided design, Cancer, Computer aided diagnosis and therapy

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Proceedings Article | 18 March 2019 Presentation + Paper

Cancer detection in mass spectrometry imaging data by dilated convolutional neural networks

J. van Kersbergen, F. Ghazvinian Zanjani, S. Zinger, F. van der Sommen, B. Balluff, D. R. Vos, S. Ellis, R. M. Heeran, M. Lucas, H. Marquering, I. Jansen, C. Savci-Heijink, D. de Bruin, P. H. de With

Proceedings Volume 10956, 109560I (2019) https://doi.org/10.1117/12.2512360

KEYWORDS: Bladder, Cancer, Tissues, Lung, Mass spectrometry, Convolution, Convolutional neural networks, Tumors, Image classification, Principal component analysis

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Proceedings Article | 15 March 2019 Paper

Tissue segmentation in volumetric laser endomicroscopy data using FusionNet and a domain-specific loss function

Joost van der Putten, Fons van der Sommen, Maarten Struyvenberg, Jeroen de Groof, Wouter Curvers, Erik Schoon, Jacques J.G.H.M. Bergman, Peter H. de With

Proceedings Volume 10949, 109492J (2019) https://doi.org/10.1117/12.2512192

KEYWORDS: Image segmentation, Optical coherence tomography, Computer aided diagnosis and therapy, Esophagus, Endomicroscopy, Endoscopy

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Proceedings Article | 15 March 2019 Paper

Enhanced face alignment using an unsupervised roll estimation initialization

Cheng Li, Arash Pourtaherian, W. Tjon a Ten, Peter H. N. de With

Proceedings Volume 11041, 110412C (2019) https://doi.org/10.1117/12.2523111

KEYWORDS: Facial recognition systems, Sensors, Head, Image segmentation, Error analysis, Eye models, Feature extraction, Light sources and illumination, Detection and tracking algorithms, Mouth

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Proceedings Article | 15 March 2019 Paper

Robust discomfort detection for infants using an unsupervised roll estimation

Cheng Li, Arash Pourtaherian, W. Tjon A Ten, Peter H. de With

Proceedings Volume 10949, 1094930 (2019) https://doi.org/10.1117/12.2512619

KEYWORDS: Infrared radiation, Infrared imaging, Facial recognition systems, Video, Video surveillance, Feature extraction, Image segmentation

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Proceedings Article | 15 March 2019 Paper

Towards multi-class detection: a self-learning approach to reduce inter-class noise from training dataset

Amir Ghahremani, Egor Bondarev, Peter H. N. de With

Proceedings Volume 11041, 110411M (2019) https://doi.org/10.1117/12.2523182

KEYWORDS: Data modeling, Performance modeling, Statistical modeling, Sensors, Visual process modeling, Surveillance, Maritime surveillance, Video surveillance, Visualization, Surveillance systems

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Proceedings Article | 15 March 2019 Paper

Towards accurate camera geopositioning by image matching

Raffaele Imbriaco, Clint Sebastian, Egor Bondarev, Peter H. N. de With

Proceedings Volume 11041, 110411C (2019) https://doi.org/10.1117/12.2522999

KEYWORDS: Panoramic photography, Databases, Image retrieval, Cameras, Feature extraction, Image processing, Convolutional neural networks

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Proceedings Article | 13 March 2019 Paper

Computer-aided classification of colorectal polyps using blue-light and linked-color imaging

Thom Scheeve, Ramon-Michel Schreuder, Fons van der Sommen, Joep E. IJspeert, Evelien Dekker, Erik Schoon, Peter H. De With

Proceedings Volume 10950, 1095012 (2019) https://doi.org/10.1117/12.2508223

KEYWORDS: Colorectal cancer, Endoscopy, Imaging systems, Diagnostics, Computer aided diagnosis and therapy, Image classification, Machine learning

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Proceedings Article | 13 March 2019 Paper

A novel clinical gland feature for detection of early Barrett’s neoplasia using volumetric laser endomicroscopy

Thom Scheeve, Maarten Struyvenberg, Wouter Curvers, Albert de Groof, Erik Schoon, Jacques J. G. H. Bergman, Fons van der Sommen, Peter H. de With

Proceedings Volume 10950, 109501Y (2019) https://doi.org/10.1117/12.2508244

KEYWORDS: Image segmentation, Tissues, Image analysis, In vivo imaging, Endomicroscopy, Esophagus, Endoscopy, Machine learning

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Proceedings Article | 13 March 2019 Paper

Dose distribution as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma

P. P. J. Langenhuizen, H. van Gorp, S. Zinger, H. B. Verheul, S. Leenstra, P. H. de With

Proceedings Volume 10950, 109504C (2019) https://doi.org/10.1117/12.2512472

KEYWORDS: Tumors, Magnetic resonance imaging, Principal component analysis, Brain, MATLAB, Analytical research, Feature extraction, 3D acquisition

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Proceedings Article | 8 March 2019 Paper

Image fusion on the endoscopic view for endo-nasal skull-base surgery

Marco Lai, Caifeng Shan, Drazenko Babic, Robert Homan, Adrian Elmi Terander, Erik Edstrom, Oscar Persson, Gustav Burstrom, Peter H. de With

Proceedings Volume 10951, 109511D (2019) https://doi.org/10.1117/12.2512734

KEYWORDS: Endoscopy, Endoscopes, Image fusion, Calibration, Surgery, Navigation systems, Optical tracking

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Proceedings Article | 8 March 2019 Paper

Automated tumor assessment of squamous cell carcinoma on tongue cancer patients with hyperspectral imaging

Francesca Manni, Fons van der Sommen, Sveta Zinger, Esther Kho, Susan Brouwer de Koning, Theo Ruers, Caifeng Shan, Jean Schleipen, Peter H. de With

Proceedings Volume 10951, 109512K (2019) https://doi.org/10.1117/12.2512238

KEYWORDS: Tumors, Cancer, Tissues, Hyperspectral imaging, Image segmentation, Image classification, Tongue, Visualization, Reflectivity, Pathology

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SPIE Journal Paper | 14 January 2019 Open Access

Catheter segmentation in three-dimensional ultrasound images by feature fusion and model fitting

Hongxu Yang, Caifeng Shan, Arash Pourtaherian, Alexander F. Kolen, Peter H. N. de With

JMI, Vol. 6, Issue 01, 015001, (January 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.1.015001

KEYWORDS: Image segmentation, 3D image processing, 3D modeling, Image fusion, Ultrasonography, Heart, Surgery, Visualization, Tissues, Image classification

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SPIE Journal Paper | 10 May 2018 Open Access

Semiautomatic training and evaluation of a learning-based vehicle make and model recognition system

Matthijs Zwemer, Guido M. Y. Brouwers, Rob G. Wijnhoven, Peter H. de With

JEI, Vol. 27, Issue 05, 051225, (May 2018) https://doi.org/10.1117/12.10.1117/1.JEI.27.5.051225

KEYWORDS: Data modeling, Sensors, Performance modeling, Visualization, Image classification, Statistical modeling, Video, Cameras, Visual process modeling, Imaging systems

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Proceedings Article | 13 March 2018 Presentation + Paper

Coherent needle detection in ultrasound volumes using 3D conditional random fields

Farhad Ghazvinian Zanjani, Arash Pourtaherian, Xikai Tang, Svitlana Zinger, Nenad Mihajlovic, Gary Ng, Hendrikus H. Korsten, Peter H. de With

Proceedings Volume 10576, 105760W (2018) https://doi.org/10.1117/12.2293079

KEYWORDS: Volume segmentation, Image-guided intervention, Ultrasonography, Image segmentation, Visualization, Feature selection, 3D image processing

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Proceedings Article | 13 March 2018 Presentation + Paper

Feature study on catheter detection in three-dimensional ultrasound

Hongxu Yang, Arash Pourtaherian, Caifeng Shan, Alexander Kolen, Peter H. de With

Proceedings Volume 10576, 105760V (2018) https://doi.org/10.1117/12.2293099

KEYWORDS: 3D image processing, Ultrasonography, Heart, In vitro testing, Machine learning, Cardiac catheterization, Image filtering

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Proceedings Article | 6 March 2018 Presentation + Paper

Cancer detection in histopathology whole-slide images using conditional random fields on deep embedded spaces

Farhad Ghazvinian Zanjani, Svitlana Zinger, Peter H. de With

Proceedings Volume 10581, 105810I (2018) https://doi.org/10.1117/12.2293107

KEYWORDS: Feature extraction, Feature selection, Convolutional neural networks, CAD systems, Image segmentation, Digital image processing, Medical image processing, Machine learning, Artificial neural networks, Color image segmentation

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Proceedings Article | 27 February 2018 Paper

Quantitative CT based radiomics as predictor of resectability of pancreatic adenocarcinoma

Joost van der Putten, Svitlana Zinger, Fons van der Sommen, Peter H. de With, Mathias Prokop, John Hermans

Proceedings Volume 10575, 105753O (2018) https://doi.org/10.1117/12.2291746

KEYWORDS: Tumors, Computed tomography, Binary data, Feature selection, Surgery, Feature extraction, Tissues, Pancreas

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Proceedings Article | 27 February 2018 Presentation + Paper

MRI textures as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma

P. P. J. H. Langenhuizen, M. J. W. Legters, S. Zinger, H. B. Verheul, S. Leenstra, P. H. N. de With

Proceedings Volume 10575, 105750H (2018) https://doi.org/10.1117/12.2293464

KEYWORDS: Tumors, Magnetic resonance imaging, Brain, Feature extraction, Tissues, Microsurgery, Image analysis

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Proceedings Article | 17 March 2017 Paper

Dense-HOG-based drift-reduced 3D face tracking for infant pain monitoring

Ronald W.J.J. Saeijs, Walther Tjon A Ten, Peter H. de With

Proceedings Volume 10341, 103411U (2017) https://doi.org/10.1117/12.2268522

KEYWORDS: 3D modeling, Head, Detection and tracking algorithms, Cameras, Eye, Video, Filtering (signal processing), 3D image processing, Motion models, Feature extraction

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Proceedings Article | 3 March 2017 Presentation + Paper

Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

Sander Klomp, Fons van der Sommen, Anne-Fré Swager, Svitlana Zinger, Erik Schoon, Wouter Curvers, Jacques Bergman, Peter H. de With

Proceedings Volume 10134, 101340D (2017) https://doi.org/10.1117/12.2253860

KEYWORDS: Esophagus, Cancer, Performance modeling, Visual process modeling, Feature extraction, Image classification, Feature selection, Principal component analysis, Machine learning, Tissues

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Proceedings Article | 3 March 2017 Paper

Automatic transperineal ultrasound probe positioning based on CT scan for image guided radiotherapy

S. Camps, F. Verhaegen, G. Paiva Fonesca, P. H. de With, D. Fontanarosa

Proceedings Volume 10135, 101352X (2017) https://doi.org/10.1117/12.2254254

KEYWORDS: Ultrasonography, Radiotherapy, Prostate, Computed tomography, Image acquisition, Visualization, Bladder, Rectum, Algorithm development, Prostate cancer, Robotics, 3D modeling

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Proceedings Article | 24 March 2016 Paper

Early esophageal cancer detection using RF classifiers

Markus H. Janse, Fons van der Sommen, Svitlana Zinger, Erik Schoon, Peter H. de With

Proceedings Volume 9785, 97851D (2016) https://doi.org/10.1117/12.2208583

KEYWORDS: Cancer, Endoscopy, Computer aided diagnosis and therapy, Image segmentation, Computing systems, Tissues, Data modeling, Binary data, Imaging systems

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Proceedings Article | 24 March 2016 Paper

Sweet-spot training for early esophageal cancer detection

Fons van der Sommen, Svitlana Zinger, Erik Schoon, Peter H. N. de With

Proceedings Volume 9785, 97851B (2016) https://doi.org/10.1117/12.2208114

KEYWORDS: Cancer, Optical inspection, Visualization, Tissues, Algorithm development, Computer aided diagnosis and therapy, Endoscopy, Inspection, Image analysis, Image segmentation, CAD systems, Esophagus, Computing systems

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Proceedings Article | 18 March 2016 Paper

Accurate biopsy-needle depth estimation in limited-angle tomography using multi-view geometry

Fons van der Sommen, Sveta Zinger, Peter H. de With

Proceedings Volume 9786, 97860D (2016) https://doi.org/10.1117/12.2214450

KEYWORDS: Image-guided intervention, Reconstruction algorithms, Tomography, X-rays, 3D image processing, CT reconstruction, Computed tomography, Error analysis, Sensors, Image segmentation, Switches

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Proceedings Article | 8 December 2015 Paper

Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound

Arash Pourtaherian, Svitlana Zinger, Nenad Mihajlovic, Peter de With, Jinfeng Huang, Gary Ng, Hendrikus Korsten

Proceedings Volume 9875, 987513 (2015) https://doi.org/10.1117/12.2228604

KEYWORDS: Matrices, Ultrasonography, 3D image processing, Wavelets, Feature extraction, Biopsy, 3D modeling, Imaging systems, Data modeling

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SPIE Journal Paper | 18 November 2015

Exploiting automatically generated databases of traffic signs and road markings for contextual co-occurrence analysis

Lykele Hazelhoff, Ivo Creusen, Thomas Woudsma, Peter H. N. de With

JEI, Vol. 24, Issue 06, 061203, (November 2015) https://doi.org/10.1117/12.10.1117/1.JEI.24.6.061203

KEYWORDS: Imaging systems, Roads, Databases, Image segmentation, Panoramic photography, Safety, Image processing, Computing systems, Visualization, Detection and tracking algorithms

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SPIE Journal Paper | 22 October 2015

Real-time planar segmentation of depth images: from three-dimensional edges to segmented planes

Hani Javan Hemmat, Egor Bondarev, Peter H. de With

JEI, Vol. 24, Issue 05, 051008, (October 2015) https://doi.org/10.1117/12.10.1117/1.JEI.24.5.051008

KEYWORDS: Image segmentation, 3D image processing, Edge detection, Detection and tracking algorithms, Sensors, Image processing algorithms and systems, Reconstruction algorithms, Clouds, Data modeling, Algorithm development

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Proceedings Article | 18 March 2015 Paper

Benchmarking of state-of-the-art needle detection algorithms in 3D ultrasound data volumes

Arash Pourtaherian, Svitlana Zinger, Peter de With, Hendrikus Korsten, Nenad Mihajlovic

Proceedings Volume 9415, 94152B (2015) https://doi.org/10.1117/12.2081800

KEYWORDS: Wavelets, Ultrasonography, 3D modeling, Detection and tracking algorithms, 3D image processing, Transducers, Breast, Visibility, 3D acquisition, Visualization

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Proceedings Article | 16 March 2015 Paper

Fast planar segmentation of depth images

Hani Javan Hemmat, Arash Pourtaherian, Egor Bondarev, Peter H. de With

Proceedings Volume 9399, 93990I (2015) https://doi.org/10.1117/12.2083340

KEYWORDS: Image segmentation, 3D image processing, Image processing algorithms and systems, Edge detection, Algorithm development, Detection and tracking algorithms, Reconstruction algorithms, Neodymium, 3D modeling, Image processing

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Proceedings Article | 16 March 2015 Paper

Multi-volume mapping and tracking for real-time RGB-D sensing

Lingni Ma, Egor Bondarev, Peter H. de With

Proceedings Volume 9399, 939918 (2015) https://doi.org/10.1117/12.2083350

KEYWORDS: Cameras, Detection and tracking algorithms, Visualization, Algorithm development, 3D modeling, Optical tracking, Near field, Associative arrays, Data fusion, Sensors

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