Wouter B Veldhuis
Overview
Explore the profile of Wouter B Veldhuis including associated specialties, affiliations and a list of published articles.
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Articles
92
Citations
1322
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Recent Articles
1.
Schuiveling M, Ter Maat L, Van Duin I, Verheijden R, Troenokarso M, Moeskops P, et al.
J Natl Cancer Inst
. 2025 Feb;
PMID: 39980388
Introduction: The association of body composition with checkpoint inhibitor outcomes in melanoma is a matter of ongoing debate. In this study, we aim to investigate body mass index (BMI) alongside...
2.
Smit K, Derksen J, Kurk S, Moeskops P, Koopman M, Veldhuis W, et al.
Clin Nutr ESPEN
. 2024 Jul;
63:572-584.
PMID: 38997109
Background: Low muscle mass and skeletal muscle mass (SMM) loss are associated with adverse patient outcomes, but the time-consuming nature of manual SMM quantification prohibits implementation of this metric in...
3.
Veenhuizen S, van Grinsven S, Laseur I, Bakker M, Monninkhof E, de Lange S, et al.
Eur Radiol
. 2024 Apr;
34(10):6334-6347.
PMID: 38639912
Objectives: Supplemental MRI screening improves early breast cancer detection and reduces interval cancers in women with extremely dense breasts in a cost-effective way. Recently, the European Society of Breast Imaging...
4.
Wang H, H M van der Velden B, Verburg E, Bakker M, Pijnappel R, Veldhuis W, et al.
Eur J Radiol
. 2024 Apr;
175:111442.
PMID: 38583349
Objectives: Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI (DCE-MRI) as rated by radiologists is subject to inter- and intrareader variability. We aim to automate BPE category from DCE-MRI. Methods:...
5.
Langius-Wiffen E, Slotman D, Groeneveld J, Ac van Osch J, Nijholt I, de Boer E, et al.
Eur J Radiol
. 2024 Feb;
173:111361.
PMID: 38401407
Purpose: To evaluate the diagnostic performance and generalizability of the winning DL algorithm of the RSNA 2020 PE detection challenge to a local population using CTPA data from two hospitals....
6.
Samim A, Spijkers S, Moeskops P, Littooij A, de Jong P, Veldhuis W, et al.
Pediatr Radiol
. 2023 Aug;
53(12):2492-2501.
PMID: 37640800
Background: Body composition during childhood may predispose to negative health outcomes later in life. Automatic segmentation may assist in quantifying pediatric body composition in children. Objective: To evaluate automatic segmentation...
7.
Wang H, H M van der Velden B, Verburg E, Bakker M, Pijnappel R, Veldhuis W, et al.
Radiology
. 2023 Aug;
308(2):e222841.
PMID: 37552061
Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense...
8.
Langius-Wiffen E, Nijholt I, van Dijk R, de Boer E, Nijboer-Oosterveld J, Veldhuis W, et al.
Eur Radiol
. 2023 Aug;
34(1):384-390.
PMID: 37542651
Objectives: Virtual monochromatic images (VMI) are increasingly used in clinical practice as they improve contrast-to-noise ratio. However, due to their different appearances, the performance of artificial intelligence (AI) trained on...
9.
Langius-Wiffen E, de Jong P, Mohamed Hoesein F, Dekker L, van den Hoven A, Nijholt I, et al.
Eur Radiol
. 2023 Aug;
34(1):367-373.
PMID: 37532902
Objectives: The purpose of this study was to evaluate the incremental value of artificial intelligence (AI) compared to the diagnostic accuracy of radiologists alone in detecting incidental acute pulmonary embolism...
10.
Sweet A, Kobes T, Houwert R, Leenen L, de Jong P, Veldhuis W, et al.
J Trauma Acute Care Surg
. 2023 Jul;
96(4):623-627.
PMID: 37480167
Background: Chest tubes are commonly placed in trauma care to treat life-threatening intrathoracic injuries by evacuating blood or air from the pleural cavity. Currently, it is common practice to routinely...