Monique D. Dorrius

2.2k total citations
73 papers, 1.4k citations indexed

About

Monique D. Dorrius is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Pathology and Forensic Medicine. According to data from OpenAlex, Monique D. Dorrius has authored 73 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Radiology, Nuclear Medicine and Imaging, 40 papers in Pulmonary and Respiratory Medicine and 8 papers in Pathology and Forensic Medicine. Recurrent topics in Monique D. Dorrius's work include Radiomics and Machine Learning in Medical Imaging (33 papers), Lung Cancer Diagnosis and Treatment (33 papers) and MRI in cancer diagnosis (23 papers). Monique D. Dorrius is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (33 papers), Lung Cancer Diagnosis and Treatment (33 papers) and MRI in cancer diagnosis (23 papers). Monique D. Dorrius collaborates with scholars based in Netherlands, China and Austria. Monique D. Dorrius's co-authors include Matthijs Oudkerk, Paul E. Sijens, Geertruida H. de Bock, Rozemarijn Vliegenthart, Ruud M. Pijnappel, Hildebrand Dijkstra, Marjolein A. Heuvelmans, Peter M. A. van Ooijen, Marcel J. W. Greuter and Peter Kappert and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Radiology.

In The Last Decade

Monique D. Dorrius

66 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Monique D. Dorrius Netherlands	24	1.1k	594	210	168	154	73	1.4k
Chantal Van Ongeval Belgium	18	637 0.6×	524 0.9×	320 1.5×	266 1.6×	187 1.2×	97	1.3k
Kanae K. Miyake Japan	18	806 0.8×	216 0.4×	503 2.4×	195 1.2×	87 0.6×	60	1.3k
Carrie B. Hruska United States	26	1.5k 1.4×	1.1k 1.8×	378 1.8×	454 2.7×	300 1.9×	91	2.1k
Massimo Falchini Italy	17	469 0.4×	703 1.2×	103 0.5×	319 1.9×	55 0.4×	39	1.0k
Cherie M. Kuzmiak United States	19	495 0.5×	337 0.6×	311 1.5×	278 1.7×	295 1.9×	83	1.1k
Jia Hua China	22	917 0.9×	175 0.3×	78 0.4×	104 0.6×	146 0.9×	61	1.4k
K. Eguchi Japan	16	756 0.7×	1.1k 1.9×	152 0.7×	315 1.9×	115 0.7×	81	1.5k
Sujata V. Ghate United States	17	521 0.5×	253 0.4×	402 1.9×	137 0.8×	90 0.6×	38	858
Darin White United States	13	223 0.2×	372 0.6×	72 0.3×	212 1.3×	127 0.8×	25	773
Barbara Galen United States	5	554 0.5×	661 1.1×	71 0.3×	242 1.4×	135 0.9×	5	1.0k

Countries citing papers authored by Monique D. Dorrius

Since Specialization

Citations

This map shows the geographic impact of Monique D. Dorrius's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Monique D. Dorrius with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monique D. Dorrius more than expected).

Fields of papers citing papers by Monique D. Dorrius

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Monique D. Dorrius. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Monique D. Dorrius. The network helps show where Monique D. Dorrius may publish in the future.

Co-authorship network of co-authors of Monique D. Dorrius

This figure shows the co-authorship network connecting the top 25 collaborators of Monique D. Dorrius. A scholar is included among the top collaborators of Monique D. Dorrius based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Monique D. Dorrius. Monique D. Dorrius is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jing, Xueping, Monique D. Dorrius, Sunyi Zheng, et al.. (2023). Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks. European Radiology. 34(3). 2084–2092. 7 indexed citations

Velden, Bas H. M. van der, Eric Tetteroo, Emile G. Coerkamp, et al.. (2023). Long-term Survival in Breast Cancer Patients Is Associated with Contralateral Parenchymal Enhancement at MRI: Outcomes of the SELECT Study. Radiology. 307(4). e221922–e221922. 4 indexed citations

Jing, Xueping, et al.. (2023). Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter‐Observer Variability. Journal of Magnetic Resonance Imaging. 60(1). 80–91. 4 indexed citations

Du, Yihui, Grigory Sidorenkov, Harry J.M. Groen, et al.. (2022). Airflow Limitation Increases Lung Cancer Risk in Smokers: The Lifelines Cohort Study. Cancer Epidemiology Biomarkers & Prevention. 31(7). 1442–1449. 3 indexed citations

Jing, Xueping, L. J. Cornelissen, Sunyi Zheng, et al.. (2022). Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time. European Radiology. 32(12). 8706–8715. 31 indexed citations

Sijens, Paul E., Hildebrand Dijkstra, Geertruida H. de Bock, et al.. (2021). Diffusion weighted imaging of the breast: Performance of standardized breast tumor tissue selection methods in clinical decision making. PLoS ONE. 16(1). e0245930–e0245930. 2 indexed citations

Cui, Xiaonan, Sunyi Zheng, Marjolein A. Heuvelmans, et al.. (2021). Performance of a deep learning-based lung nodule detection system as an alternative reader in a Chinese lung cancer screening program. European Journal of Radiology. 146. 110068–110068. 28 indexed citations

Cui, Xiaonan, Sunyi Zheng, Marjolein A. Heuvelmans, et al.. (2021). P42.02 Evaluating the Feasibility of a Deep Learning-Based Computer-Aided Detection System for Lung Nodule Detection in a Lung Cancer Screening Program. Journal of Thoracic Oncology. 16(3). S477–S478. 1 indexed citations

Cui, Xiaonan, Marjolein A. Heuvelmans, Daiwei Han, et al.. (2020). A Subsolid Nodules Imaging Reporting System (SSN-IRS) for Classifying 3 Subtypes of Pulmonary Adenocarcinoma. Clinical Lung Cancer. 21(4). 314–325.e4. 7 indexed citations

10.

Cui, Xiaonan, Marjolein A. Heuvelmans, Daiwei Han, et al.. (2020). Optimization of CT windowing for diagnosing invasiveness of adenocarcinoma presenting as sub-solid nodules. European Journal of Radiology. 128. 108981–108981. 2 indexed citations

11.

Cui, Xiaonan, Marjolein A. Heuvelmans, Daiwei Han, et al.. (2019). Comparison of Veterans Affairs, Mayo, Brock classification models and radiologist diagnosis for classifying the malignancy of pulmonary nodules in Chinese clinical population. Translational Lung Cancer Research. 8(5). 605–613. 18 indexed citations

12.

Rook, Mieneke, Grigory Sidorenkov, Peter M. A. van Ooijen, et al.. (2019). Early imaging biomarkers of lung cancer, COPD and coronary artery disease in the general population: rationale and design of the ImaLife (Imaging in Lifelines) Study. European Journal of Epidemiology. 35(1). 75–86. 43 indexed citations

13.

Zelst, Jan van, Suzan Vreemann, Albert Gubern‐Mérida, et al.. (2018). Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening. Investigative Radiology. 53(10). 579–586. 64 indexed citations

14.

Walter, Joan, Marjolein A. Heuvelmans, Uraujh Yousaf-Khan, et al.. (2018). New Subsolid Pulmonary Nodules in Lung Cancer Screening: The NELSON Trial. Journal of Thoracic Oncology. 13(9). 1410–1414. 46 indexed citations

15.

Dijkstra, Hildebrand, et al.. (2016). Quantitative DWI implemented after DCE-MRI yields increased specificity for BI-RADS 3 and 4 breast lesions. Journal of Magnetic Resonance Imaging. 44(6). 1642–1649. 46 indexed citations

16.

Zhao, Ying, Marjolein A. Heuvelmans, Monique D. Dorrius, et al.. (2013). Features of Resolving and Nonresolving Indeterminate Pulmonary Nodules at Follow-up CT: The NELSON Study. Radiology. 270(3). 872–879. 37 indexed citations

17.

Dorrius, Monique D., et al.. (2011). The negative predictive value of breast Magnetic Resonance Imaging in noncalcified BIRADS 3 lesions. European Journal of Radiology. 81(2). 209–213. 22 indexed citations

18.

Dorrius, Monique D., Ruud M. Pijnappel, Liesbeth Jansen, et al.. (2011). The added value of quantitative multi-voxel MR spectroscopy in breast magnetic resonance imaging. European Radiology. 22(4). 915–922. 20 indexed citations

19.

Sijens, Paul E., Monique D. Dorrius, Peter Kappert, et al.. (2010). Quantitative multivoxel proton chemical shift imaging of the breast. Magnetic Resonance Imaging. 28(3). 314–319. 17 indexed citations

20.

Wang, Ying, Geertruida H. de Bock, Rob J. van Klaveren, et al.. (2009). Volumetric measurement of pulmonary nodules at low-dose chest CT: effect of reconstruction setting on measurement variability. European Radiology. 20(5). 1180–1187. 57 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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