Division of Image Processing / LKEB

Department of Radiology, Leiden University Medical Center

Home

2024 2023 2022 2021 2020

Publications 2025

[1] H. S. Assadi et al., “Cardiac MRI Markers of Ageing: A Multicentre, Cross-sectional Cohort Study,” European Heart Journal Open, p. oeaf032, Mar. 2025, doi: 10.1093/ehjopen/oeaf032.

[2] R. Bajaj et al., “Examination of the performance of machine learning-based automated coronary plaque characterization by NIRS-IVUS and OCT with histology,” European Heart Journal - Digital Health, p. ztaf009, Mar. 2025, doi: 10.1093/ehjdh/ztaf009.

[3] E. Erdogan et al., “Morphological characteristics of non-culprit lesions in patients with chronic and acute coronary syndromes: A NIRS-IVUS study,” in Diagnostic and Therapeutic Applications of Light in Cardiology 2025, SPIE, Mar. 2025, p. PC1329502. doi: 10.1117/12.3049890.

[4] R. Gao, P. Mody, C. Rao, F. Dankers, and M. Staring, “On factors that influence deep learning-based dose prediction of head and neck tumors,” Physics in Medicine and Biology, Apr. 2025, doi: 10.1088/1361-6560/adcfeb.

[5] C. Grafton-Clarke et al., “Four-dimensional flow provides incremental diagnostic value over echocardiography in aortic stenosis,” Open Heart, vol. 12, no. 1, May 2025, doi: 10.1136/openhrt-2024-003081.

[6] S. Iwańczyk et al., “Endothelial shear stress pattern in coronary artery aneurysm: A case report,” Kardiologia Polska, Feb. 2025, doi: 10.33963/v.phj.104603.

[7] J. Nicolaisen et al., “Induced Human-like Coronary Stenosis in Hypercholesterolemic PCSK9 Minipigs,” Journal of Cardiovascular Translational Research, Mar. 2025, doi: 10.1007/s12265-025-10607-0.

[8] P. C. Revaiah et al., “Segmental post-PCI physiological gradients using ultrasonic or optical flow ratio: Insights from ASET JAPAN Study,” European Heart Journal - Imaging Methods and Practice, p. qyaf017, Jan. 2025, doi: 10.1093/ehjimp/qyaf017.

[9] S. Rezaei et al., “Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy,” Astronomy and Computing, vol. 51, p. 100921, Apr. 2025, doi: 10.1016/j.ascom.2024.100921.

[10] E. J. A. Verheijen et al., “Artificial intelligence for segmentation and classification in lumbar spinal stenosis: An overview of current methods,” European Spine Journal, Jan. 2025, doi: 10.1007/s00586-025-08672-9.