Artigos com autorizações de acesso público - Henkjan HuismanSaiba mais
Não disponível em nenhum local: 1
Statistical power in image segmentation: Relating sample size to reference standard quality
E Gibson, HJ Huisman, DC Barratt
International Conference on Medical Image Computing and Computer-Assisted …, 2015
Autorizações: Canadian Institutes of Health Research
Disponíveis em algum local: 51
The medical segmentation decathlon
M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ...
Nature communications 13 (1), 4128, 2022
Autorizações: US National Institutes of Health, Helmholtz Association, Danish Council for …
Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge
G Litjens, R Toth, W Van De Ven, C Hoeks, S Kerkstra, B Van Ginneken, ...
Medical image analysis 18 (2), 359-373, 2014
Autorizações: US National Institutes of Health, Dutch Cancer Society
Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T
EK Vos, GJS Litjens, T Kobus, T Hambrock, CA Kaa, JO Barentsz, ...
European urology 64 (3), 448-455, 2013
Autorizações: Dutch Cancer Society
PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images
SG Armato III, H Huisman, K Drukker, L Hadjiiski, JS Kirby, N Petrick, ...
Journal of Medical Imaging 5 (4), 044501-044501, 2018
Autorizações: US Department of Energy, US National Institutes of Health
Imaging vascular function for early stage clinical trials using dynamic contrast-enhanced magnetic resonance imaging
MO Leach, B Morgan, PS Tofts, DL Buckley, W Huang, MA Horsfield, ...
European radiology 22, 1451-1464, 2012
Autorizações: Cancer Research UK
Prostate cancer: computer-aided diagnosis with multiparametric 3-T MR imaging—effect on observer performance
T Hambrock, PC Vos, CA Hulsbergen–van de Kaa, JO Barentsz, ...
Radiology 266 (2), 521-530, 2013
Autorizações: Dutch Cancer Society
End-to-end prostate cancer detection in bpMRI via 3D CNNs: effects of attention mechanisms, clinical priori and decoupled false positive reduction
A Saha, M Hosseinzadeh, H Huisman
Medical image analysis 73, 102155, 2021
Autorizações: European Commission
Supervised uncertainty quantification for segmentation with multiple annotations
S Hu, D Worrall, S Knegt, B Veeling, H Huisman, M Welling
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
Autorizações: Netherlands Organisation for Scientific Research
Deep learning–assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge
M Hosseinzadeh, A Saha, P Brand, I Slootweg, M de Rooij, H Huisman
European Radiology, 1-11, 2022
Autorizações: European Commission
Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI
GJS Litjens, JO Barentsz, N Karssemeijer, HJ Huisman
European radiology 25, 3187-3199, 2015
Autorizações: Dutch Cancer Society
Artificial intelligence based algorithms for prostate cancer classification and detection on magnetic resonance imaging: a narrative review
JJ Twilt, KG van Leeuwen, HJ Huisman, JJ Fütterer, M de Rooij
Diagnostics 11 (6), 959, 2021
Autorizações: European Commission
Artificial intelligence and radiologists at prostate cancer detection in mri—the pi-cai challenge
A Saha, J Bosma, J Twilt, B van Ginneken, D Yakar, M Elschot, J Veltman, ...
Medical Imaging with Deep Learning, short paper track, 2023
Autorizações: European Commission
Inter-site variability in prostate segmentation accuracy using deep learning
E Gibson, Y Hu, N Ghavami, HU Ahmed, C Moore, M Emberton, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
Autorizações: Cancer Research UK
AAPM task group report 273: recommendations on best practices for AI and machine learning for computer‐aided diagnosis in medical imaging
L Hadjiiski, K Cha, HP Chan, K Drukker, L Morra, JJ Näppi, B Sahiner, ...
Medical physics 50 (2), e1-e24, 2023
Autorizações: US National Institutes of Health
Computer-extracted features can distinguish noncancerous confounding disease from prostatic adenocarcinoma at multiparametric MR imaging
GJS Litjens, R Elliott, NNC Shih, MD Feldman, T Kobus, ...
Radiology 278 (1), 135-145, 2016
Autorizações: US National Institutes of Health, Dutch Cancer Society
Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study
A Saha, JS Bosma, JJ Twilt, B van Ginneken, A Bjartell, AR Padhani, ...
The Lancet Oncology 25 (7), 879-887, 2024
Autorizações: Prostate Cancer UK, European Commission
Correlation between dynamic contrast-enhanced MRI and quantitative histopathologic microvascular parameters in organ-confined prostate cancer
CG van Niekerk, JAWM van der Laak, T Hambrock, HJ Huisman, ...
European radiology 24, 2597-2605, 2014
Autorizações: Dutch Cancer Society
Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges
MRS Sunoqrot, A Saha, M Hosseinzadeh, M Elschot, H Huisman
European radiology experimental 6 (1), 35, 2022
Autorizações: European Commission, Research Council of Norway
Fully automatic deep learning framework for pancreatic ductal adenocarcinoma detection on computed tomography
N Alves, M Schuurmans, G Litjens, JS Bosma, J Hermans, H Huisman
Cancers 14 (2), 376, 2022
Autorizações: European Commission
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