dr.ir. Bas van der Velden is a senior postdoctoral researcher interested in predicting outcome of cancer patients using advanced image analysis, with a focus on eXplainable Artificial Intelligence (XAI).
He has a PhD in Medical Imaging from the Image Sciences Institute (University Medical Center Utrecht) and a MSc degree in Medical Engineering from the Eindhoven University of Technology. He has research experience abroad at Memorial Sloan Kettering Cancer Center and UC Berkeley.
Image Sciences Institute
University Medical Center Utrecht
Heidelberglaan 100
Q.02.4.45
3584 CX Utrecht
The Netherlands
University Medical Center Utrecht
Heidelberglaan 100
Q.02.4.45
3584 CX Utrecht
The Netherlands
email: b.h.m.vandervelden-2@umcutrecht.nl
office: Q.02.4.45
phone: +31 88 75 69654
secretary: +31 88 75 57772
office: Q.02.4.45
phone: +31 88 75 69654
secretary: +31 88 75 57772
Publications
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Dynamic Contrast-enhanced and Diffusion-weighted Magnetic Resonance Imaging for Response Evaluation After Single-Dose Ablative Neoadjuvant Partial Breast Irradiation
Mar 2022 in Advances in Radiation Oncology 7 (2), p. 1-11 -
Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial
Jan 2022 in Radiology 302 (1), p. 29-36 -
Population-based estimates of overtreatment with adjuvant systemic therapy in early breast cancer patients with data from the Netherlands and the USA
2022 in Breast Cancer Research and Treatment -
Toward Computer-Assisted Triaging of Magnetic Resonance Imaging-Guided Biopsy in Preoperative Breast Cancer Patients
Jul 2021 in Investigative Radiology 56 (7), p. 442-449 -
Prognostic value of breast MRI characteristics before and during neoadjuvant endocrine therapy in patients with ER+/HER2- breast cancer
Jul 2021 in The British journal of radiology 94 (1123), p. 1-10 -
Radiogenomic Analysis of Breast Cancer by Linking MRI Phenotypes with Tumor Gene Expression
Aug 2020 in Radiology 296 (2), p. 277-287 -
Synchronous Breast Cancer: Phenotypic Similarities on MRI
Jun 2020 in Journal of Magnetic Resonance Imaging 51 (6), p. 1858-1867 -
Contralateral parenchymal enhancement on breast MRI before and during neoadjuvant endocrine therapy in relation to the preoperative endocrine prognostic index
Dec 2020 in European Radiology 30 (12), p. 6740-6748 -
Harmonization of Quantitative Parenchymal Enhancement in T1 -Weighted Breast MRI
Nov 2020 in Journal of Magnetic Resonance Imaging 52 ( 5), p. 1374-1382 -
Volumetric breast density estimation on MRI using explainable deep learning regression
Oct 2020 in Scientific Reports 10 (1), -
Are contralateral parenchymal enhancement on dynamic contrast-enhanced MRI and genomic ER-pathway activity in ER-positive/HER2-negative breast cancer related?
Dec 2019 in European Journal of Radiology 121 -
Perfusion in the contralateral breast on preoperative MRI may complement ER-pathway activity from the index tumor to stratify outcome of endocrine therapy for early-stage invasive breast cancer
Apr 2018 in European Journal of Cancer 92 (Supplement 3), p. S49-S50 -
Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI reproduces as a biomarker of survival in ER-positive/HER2-negative breast cancer patients
Nov 2018 in European Radiology 28 (11), p. 4705-4716 -
Eligibility of patients for minimally invasive breast cancer therapy based on MRI analysis of tumor proximity to skin and pectoral muscle
2018 in The Breast Journal 24 (4), p. 501-508 -
Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study
2017 in Physics in Medicine and Biology 62 (16), p. 6467-6485 -
Complementary value of contralateral parenchymal enhancement on DCE-MRI to prognostic models and molecular assays in high-risk ER+HER2- breast cancer
2017 in Clinical Cancer Research 23 (21), p. 6505-6515 -
Prediction Model For Extensive Ductal Carcinoma In Situ Around Early-Stage Invasive Breast Cancer
Jul 2016 in Investigative Radiology 51 (7), p. 462-468 -
Determining the bias and variance of a deterministic finger-tracking algorithm
Jun 2016 in Behavior Research Methods 48 (2), p. 772-782 -
Prediction model for extensive ductal carcinoma in situ around early-stage invasive breast cancer
Apr 2016 in European Journal of Cancer 57 p. S86-S87 -
Parenchymal enhancement of the contralateral breast in DCE-MRI and outcome of patients with early breast cancer: complementary value of the 70-gene signature
Apr 2016 in European Journal of Cancer 57 p. S17-S17 -
Prediction of the 70-gene signature in early breast cancer patients using computer-derived DCE-MRI features of the tumor and intramammary blood vessels
Apr 2016 in European Journal of Cancer 57 p. S17-S17 -
Association between computer-derived features of the ipsilateral breast on DCE-MRI and the 70-gene signature in patients with invasive breast cancer
Feb 2016 in Cancer Research 76 (S4), p. P4-02-07