Vincent Andrearczyk

5.7k total citations
34 papers, 605 citations indexed

About

Vincent Andrearczyk is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Vincent Andrearczyk has authored 34 papers receiving a total of 605 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Vincent Andrearczyk's work include Radiomics and Machine Learning in Medical Imaging (19 papers), AI in cancer detection (14 papers) and Medical Imaging Techniques and Applications (6 papers). Vincent Andrearczyk is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (19 papers), AI in cancer detection (14 papers) and Medical Imaging Techniques and Applications (6 papers). Vincent Andrearczyk collaborates with scholars based in Switzerland, France and United States. Vincent Andrearczyk's co-authors include Henning Müller, Paul F. Whelan, Adrien Depeursinge, Manfredo Atzori, Amjad Khan, Sebastian Otálora, Stéphane Marchand‐Maillet, Maria Stella Graziani, Mara Graziani and Abdalla Ibrahim and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Vincent Andrearczyk

31 papers receiving 593 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vincent Andrearczyk Switzerland 13 338 276 147 110 74 34 605
Jinzheng Cai United States 11 408 1.2× 383 1.4× 357 2.4× 101 0.9× 73 1.0× 17 773
Christoph Haarburger Germany 11 446 1.3× 310 1.1× 105 0.7× 93 0.8× 77 1.0× 16 676
Zohaib Salahuddin Netherlands 7 274 0.8× 173 0.6× 59 0.4× 85 0.8× 88 1.2× 13 446
Marek Wodziński Poland 12 163 0.5× 193 0.7× 81 0.6× 66 0.6× 46 0.6× 48 469
Liming Zhong China 12 303 0.9× 101 0.4× 96 0.7× 141 1.3× 58 0.8× 40 490
Adam P. Harrison United States 14 338 1.0× 197 0.7× 269 1.8× 96 0.9× 48 0.6× 28 568
Kazuma Kobayashi Japan 14 241 0.7× 193 0.7× 52 0.4× 42 0.4× 65 0.9× 32 638
Gustav Müller‐Franzes Germany 11 316 0.9× 239 0.9× 89 0.6× 73 0.7× 70 0.9× 22 567
Mehrdad J. Gangeh Canada 17 414 1.2× 299 1.1× 173 1.2× 159 1.4× 80 1.1× 34 719
Dzhoshkun I. Shakir United Kingdom 9 221 0.7× 131 0.5× 160 1.1× 105 1.0× 50 0.7× 22 532

Countries citing papers authored by Vincent Andrearczyk

Since Specialization
Citations

This map shows the geographic impact of Vincent Andrearczyk'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 Vincent Andrearczyk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vincent Andrearczyk more than expected).

Fields of papers citing papers by Vincent Andrearczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Vincent Andrearczyk. 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 Vincent Andrearczyk. The network helps show where Vincent Andrearczyk may publish in the future.

Co-authorship network of co-authors of Vincent Andrearczyk

This figure shows the co-authorship network connecting the top 25 collaborators of Vincent Andrearczyk. A scholar is included among the top collaborators of Vincent Andrearczyk 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 Vincent Andrearczyk. Vincent Andrearczyk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Andrearczyk, Vincent, et al.. (2025). Automatic rib fracture detection on postmortem CT data using deep learning. International Journal of Legal Medicine. 140(2). 857–866.
2.
3.
Abler, Daniel, Vincent Andrearczyk, Julien Fageot, et al.. (2024). Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction. Scientific Reports. 14(1). 9644–9644. 2 indexed citations
4.
Andrearczyk, Vincent, et al.. (2023). Head and Neck Tumor Segmentation and Outcome Prediction. Lecture notes in computer science. 15 indexed citations
5.
Andrearczyk, Vincent, Valentin Oreiller, Sarah Boughdad, et al.. (2023). Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge. Medical Image Analysis. 90. 102972–102972. 12 indexed citations
6.
Andrearczyk, Vincent, et al.. (2023). Disentangling Neuron Representations with Concept Vectors. ArODES (HES-SO (https://www.hes-so.ch/)). 3770–3775. 2 indexed citations
7.
Graziani, Mara, Davide Calvaresi, Mor Vered, et al.. (2022). A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences. Artificial Intelligence Review. 56(4). 3473–3504. 65 indexed citations
8.
Andrearczyk, Vincent, Valentin Oreiller, Daniel Abler, et al.. (2022). Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study. Clinical and Translational Radiation Oncology. 33. 153–158. 5 indexed citations
9.
Savjani, Ricky R., et al.. (2022). Automated Tumor Segmentation in Radiotherapy. Seminars in Radiation Oncology. 32(4). 319–329. 22 indexed citations
10.
Andrearczyk, Vincent, Valentin Oreiller, Mario Jreige, et al.. (2022). Segmentation and Classification of Head and Neck Nodal Metastases and Primary Tumors in PET/CT. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2022. 4731–4735. 9 indexed citations
11.
Graziani, Mara, et al.. (2021). On the Scale Invariance in State of the Art CNNs Trained on ImageNet. SHILAP Revista de lepidopterología. 3(2). 374–391. 13 indexed citations
12.
Ibrahim, Abdalla, Henry C. Woodruff, Vincent Andrearczyk, et al.. (2021). Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods. Journal of Personalized Medicine. 11(9). 842–842. 116 indexed citations
13.
Andrearczyk, Vincent, Valentin Oreiller, Martin Vallières, et al.. (2020). Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans. ArODES (HES-SO (https://www.hes-so.ch/)). 33–43. 24 indexed citations
14.
Graziani, Maria Stella, Vincent Andrearczyk, Stéphane Marchand‐Maillet, & Henning Müller. (2020). Concept attribution: Explaining CNN decisions to physicians. Computers in Biology and Medicine. 123. 103865–103865. 55 indexed citations
15.
Hoebel, Katharina, Vincent Andrearczyk, Andrew Beers, et al.. (2020). An exploration of uncertainty information for segmentation quality assessment. ArODES (HES-SO (https://www.hes-so.ch/)). 55–55. 20 indexed citations
16.
Otálora, Sebastian, Manfredo Atzori, Vincent Andrearczyk, Amjad Khan, & Henning Müller. (2019). Staining Invariant Features for Improving Generalization of Deep Convolutional Neural Networks in Computational Pathology. Frontiers in Bioengineering and Biotechnology. 7. 198–198. 54 indexed citations
17.
Andrearczyk, Vincent. (2019). Solid Spherical Energy (SSE) CNNs for Efficient 3D Medical Image Analysis. Arrow - TU Dublin (Technological University Dublin). 1 indexed citations
18.
Andrearczyk, Vincent, Julien Fageot, Valentin Oreiller, Xavier Montet, & Adrien Depeursinge. (2018). Exploring local rotation invariance in 3D CNNs with steerable filters. ArODES (HES-SO (https://www.hes-so.ch/)). 15–26. 4 indexed citations
19.
Andrearczyk, Vincent & Paul F. Whelan. (2017). Deep learning for biomedical texture image analysis. Arrow@dit (Dublin Institute of Technology). 10 indexed citations
20.
Andrearczyk, Vincent & Paul F. Whelan. (2017). Convolutional neural network on three orthogonal planes for dynamic texture classification. Pattern Recognition. 76. 36–49. 56 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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