Rafał Obuchowicz

868 total citations
52 papers, 459 citations indexed

About

Rafał Obuchowicz is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Orthopedics and Sports Medicine. According to data from OpenAlex, Rafał Obuchowicz has authored 52 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Surgery and 12 papers in Orthopedics and Sports Medicine. Recurrent topics in Rafał Obuchowicz's work include Radiomics and Machine Learning in Medical Imaging (12 papers), Tendon Structure and Treatment (7 papers) and Dental Radiography and Imaging (5 papers). Rafał Obuchowicz is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (12 papers), Tendon Structure and Treatment (7 papers) and Dental Radiography and Imaging (5 papers). Rafał Obuchowicz collaborates with scholars based in Poland, United States and Australia. Rafał Obuchowicz's co-authors include Adam Piórkowski, Michał Strzelecki, Marcin Kociołek, Mariusz Oszust, Karolina Nurzyǹska, Andrzej Urbanik, Michał Bonczar, Marzena Bielecka, Beata Jarmołowska and Andrzej Bielecki and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and PLoS ONE.

In The Last Decade

Rafał Obuchowicz

48 papers receiving 454 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rafał Obuchowicz Poland 14 152 80 78 78 71 52 459
André Mastmeyer Germany 10 110 0.7× 207 2.6× 106 1.4× 98 1.3× 54 0.8× 22 367
Jim Graham United Kingdom 20 260 1.7× 87 1.1× 127 1.6× 52 0.7× 113 1.6× 39 1.2k
M. de la Fuente Germany 13 74 0.5× 172 2.1× 84 1.1× 312 4.0× 58 0.8× 67 557
Darko Štern Austria 17 221 1.5× 407 5.1× 157 2.0× 216 2.8× 35 0.5× 34 960
Simone Balocco Spain 13 167 1.1× 154 1.9× 157 2.0× 162 2.1× 11 0.2× 44 630
Shumao Pang China 11 86 0.6× 237 3.0× 98 1.3× 102 1.3× 8 0.1× 21 373
Nandhini Santhanam Germany 3 205 1.3× 94 1.2× 79 1.0× 22 0.3× 7 0.1× 4 519
Guillaume Dardenne France 9 63 0.4× 71 0.9× 44 0.6× 105 1.3× 9 0.1× 48 294
Fumio Sasazawa Japan 11 68 0.4× 100 1.3× 62 0.8× 143 1.8× 20 0.3× 17 403

Countries citing papers authored by Rafał Obuchowicz

Since Specialization
Citations

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

Fields of papers citing papers by Rafał Obuchowicz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rafał Obuchowicz

This figure shows the co-authorship network connecting the top 25 collaborators of Rafał Obuchowicz. A scholar is included among the top collaborators of Rafał Obuchowicz 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 Rafał Obuchowicz. Rafał Obuchowicz 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.
Kaminski, Pawel M., Rafał Obuchowicz, Michał Strzelecki, et al.. (2025). Assessment of Bone Aging—A Comparison of Different Methods for Evaluating Bone Tissue. Applied Sciences. 15(13). 7526–7526.
2.
Nurzyǹska, Karolina, et al.. (2025). Automated determination of hip arthrosis on the Kellgren–Lawrence scale in pelvic digital radiographs scans using machine learning. Computer Methods and Programs in Biomedicine. 266. 108742–108742. 2 indexed citations
3.
Nurzyǹska, Karolina, et al.. (2025). Deep Learning for Ultrasonographic Assessment of Temporomandibular Joint Morphology. Tomography. 11(3). 27–27. 3 indexed citations
4.
Obuchowicz, Rafał, et al.. (2025). Artificial Intelligence-Empowered Radiology—Current Status and Critical Review. Diagnostics. 15(3). 282–282. 19 indexed citations
5.
6.
7.
Kaminski, Pawel M., Karolina Nurzyǹska, Rafał Obuchowicz, et al.. (2024). Sex Differentiation of Trabecular Bone Structure Based on Textural Analysis of Pelvic Radiographs. Journal of Clinical Medicine. 13(7). 1904–1904. 3 indexed citations
8.
Bonczar, Michał, et al.. (2023). Evaluation of lateral epicondylopathy, posterior interosseous nerve compression, and plica syndrome as co-existing causes of chronic tennis elbow. International Orthopaedics. 47(7). 1787–1795. 7 indexed citations
9.
Obuchowicz, Rafał, et al.. (2023). Combining variational mode decomposition with regularisation techniques to denoise MRI data. Magnetic Resonance Imaging. 106. 55–76. 5 indexed citations
10.
Obuchowicz, Rafał, et al.. (2023). Texture Analysis for the Bone Age Assessment from MRI Images of Adolescent Wrists in Boys. Journal of Clinical Medicine. 12(8). 2762–2762. 9 indexed citations
11.
Obuchowicz, Rafał, et al.. (2023). Textural Features of MR Images Correlate with an Increased Risk of Clinically Significant Cancer in Patients with High PSA Levels. Journal of Clinical Medicine. 12(8). 2836–2836. 1 indexed citations
12.
Tabor, Zbisław, et al.. (2023). Deep Learning Algorithm for Differentiating Patients with a Healthy Liver from Patients with Liver Lesions Based on MR Images. Cancers. 15(12). 3142–3142. 2 indexed citations
13.
Młyniec, Andrzej, et al.. (2021). The dispersion of viscoelastic properties of fascicle bundles within the tendon results from the presence of interfascicular matrix and flow of body fluids. Materials Science and Engineering C. 130. 112435–112435. 16 indexed citations
14.
Obuchowicz, Rafał, Mariusz Oszust, Marzena Bielecka, Andrzej Bielecki, & Adam Piórkowski. (2020). Magnetic Resonance Image Quality Assessment by Using Non-Maximum Suppression and Entropy Analysis. Entropy. 22(2). 220–220. 18 indexed citations
15.
Obuchowicz, Rafał, Mariusz Oszust, & Adam Piórkowski. (2020). Interobserver variability in quality assessment of magnetic resonance images. BMC Medical Imaging. 20(1). 109–109. 16 indexed citations
16.
Obuchowicz, Rafał, Piotr Kohut, Krzysztof Holak, et al.. (2019). Interfascicular matrix-mediated transverse deformation and sliding of discontinuous tendon subcomponents control the viscoelasticity and failure of tendons. Journal of the mechanical behavior of biomedical materials. 97. 238–246. 15 indexed citations
17.
Bielecka, Marzena, Rafał Obuchowicz, & Mariusz Korkosz. (2018). The shape language in application to the diagnosis of cervical vertebrae pathology. PLoS ONE. 13(10). e0204546–e0204546. 3 indexed citations
18.
Obuchowicz, Rafał, et al.. (2018). Caries detection enhancement using texture feature maps of intraoral radiographs. Oral Radiology. 36(3). 275–287. 37 indexed citations
19.
Obuchowicz, Rafał & Michał Bonczar. (2016). Ultrasonographic Differentiation of Lateral Elbow Pain. SHILAP Revista de lepidopterología. 2(2). E38–E46. 13 indexed citations
20.
Fiedorowicz, Ewa, et al.. (2010). The influence of μ-opioid receptor agonist and antagonist peptides on peripheral blood mononuclear cells (PBMCs). Peptides. 32(4). 707–712. 29 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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