David Völgyes
David Völgyes
senior scientific software engineer at S&T Corp
Verified email at - Homepage
Cited by
Cited by
Image quality with iterative reconstruction techniques in CT of the lungs—A phantom study
HK Andersen, D Völgyes, ACT Martinsen
European journal of radiology open 5, 35-40, 2018
Characterisation of silica nanoparticulate layers with scanning-angle reflectometry
E Hild, T Seszták, D Völgyes, Z Hórvölgyi
From Colloids to Nanotechnology, 61-67, 2004
TeraTomo project: a fully 3D GPU based reconstruction code for exploiting the imaging capability of the NanoPET/CT system
M Magdics, L Szirmay-Kalos, Á Szlavecz, G Hesz, B Benyó, Á Cserkaszky, ...
World Molecular Imaging Congress, 2010
Performance evaluation of scatter modeling of the GPU-based “Tera-Tomo” 3D PET reconstruction
M Magdics, L Szirmay-Kalos, B Tóth, D Légrády, A Cserkaszky, L Balkay, ...
2011 IEEE Nuclear Science Symposium Conference Record, 4086-4088, 2011
How different iterative and filtered back projection kernels affect computed tomography numbers and low contrast detectability
D Völgyes, M Pedersen, A Stray-Pedersen, D Waaler, ACT Martinsen
Journal of computer assisted tomography 41 (1), 75-81, 2017
A weighted histogram-based tone mapping algorithm for CT images
D Völgyes, ACT Martinsen, A Stray-Pedersen, D Waaler, M Pedersen
Algorithms 11 (8), 111, 2018
NEMA NU4-2008 performance evaluation of Albira: A two-ring small-animal PET system using continuous LYSO crystals
MZ Pajak, D Volgyes, SL Pimlott, CC Salvador, AS Asensi, C McKeown, ...
Open Medicine Journal 3 (1), 2016
Detector modeling techniques for pre-clinical 3D PET reconstruction on the GPU
M Magdics, B Tóth, L Szécsi, B Csébfalvi, L Szirmay-Kalos, A Szlavecz, ...
11th International Meeting on Fully Three-Dimensional Image Reconstruction …, 2011
Local energy scale map for NanoPET™/CT system
P Major, G Hesz, Á Szlávecz, D Volgyes, B Benyó, G Németh
2009 IEEE Nuclear Science Symposium Conference Record (NSS/MIC), 3177-3180, 2009
Mitral annulus segmentation and anatomical orientation detection in TEE images using periodic 3D CNN
BS Andreassen, D Völgyes, E Samset, AHS Solberg
IEEE access 10, 51472-51486, 2022
Presentation of test measurements with a commercial small animal PET/MR imaging system
K Nagy, G Nemeth, P Major, Z Nyitrai, D Máthé, B Gulyás, C Halldin, ...
Journal of Nuclear Medicine 52 (supplement 1), 259-259, 2011
COMPET: High resolution high sensitivity MRI compatible pre-clinical PET scanner
KE Hines, E Bolle, M Rissi, D Volgyes, O Dorholt, O Rřhne, S Stapnes, ...
Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2013
Timing calibration method for NanoPET™/CT system
G Hesz, D Volgyes, B Benyo, T Bukki, P Major
IEEE Nuclear Science Symposuim & Medical Imaging Conference, 2010
CryoSat-2 waveform classification for melt event monitoring
M Vermeer, D Völgyes, M McMillan, D Fantin
Proceedings of the Northern Lights Deep Learning Workshop 3, 2022
Image quality in forensic CT imaging
D Völgyes
NTNU, 2018
Lidar-based Norwegian tree species detection using deep learning
M Vermeer, JA Hay, D Völgyes, Z Koma, J Breidenbach, DSM Fantin
arXiv preprint arXiv:2311.06066, 2023
Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
A Vats, D Völgyes, M Vermeer, M Pedersen, K Raja, DSM Fantin, JA Hay
arXiv preprint arXiv:2311.01188, 2023
Semi-and weak-supervised learning for Norwegian tree species detection
M Vermeer, D Völgyes, TK Sřrensen, H Miller, D Fantin
Proceedings of the Northern Lights Deep Learning Workshop 4, 2023
Our MapAI approach: focusing on data pipeline and loss functions
TK Sřrensen, M Vermeer, JA Hay, D Fantin, D Völgyes
Nordic Machine Intelligence 2 (3), 2022
Image De-Quantization Using Plate Bending Model
D Völgyes, ACT Martinsen, A Stray-Pedersen, D Waaler, M Pedersen
Algorithms 11 (8), 110, 2018
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