Andrzej Skalski

976 total citations
61 papers, 523 citations indexed

About

Andrzej Skalski is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Andrzej Skalski has authored 61 papers receiving a total of 523 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Vision and Pattern Recognition, 25 papers in Biomedical Engineering and 16 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Andrzej Skalski's work include Medical Image Segmentation Techniques (22 papers), Anatomy and Medical Technology (11 papers) and AI in cancer detection (11 papers). Andrzej Skalski is often cited by papers focused on Medical Image Segmentation Techniques (22 papers), Anatomy and Medical Technology (11 papers) and AI in cancer detection (11 papers). Andrzej Skalski collaborates with scholars based in Poland, United States and United Kingdom. Andrzej Skalski's co-authors include Marek Wodziński, Daria Hemmerling, Janusz Gajda, Elmar Nöth, Juan Rafael Orozco‐Arroyave, Tomasz P. Zieliński, Paweł Turcza, Tomasz Drewniak, Piotr Kędzierawski and Jacek Jakubowski and has published in prestigious journals such as Sensors, Physics in Medicine and Biology and Medical Physics.

In The Last Decade

Andrzej Skalski

56 papers receiving 500 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrzej Skalski Poland 13 176 161 141 121 103 61 523
Tobias Gehrig Germany 17 68 0.4× 70 0.4× 135 1.0× 120 1.0× 184 1.8× 47 844
Tahir Mahmood South Korea 13 232 1.3× 25 0.2× 192 1.4× 77 0.6× 11 0.1× 30 620
Haijun Lei China 16 201 1.1× 75 0.5× 434 3.1× 43 0.4× 57 0.6× 58 865
Francesco Girardi Italy 12 124 0.7× 118 0.7× 109 0.8× 38 0.3× 34 0.3× 13 469
Yin Dai China 9 162 0.9× 16 0.1× 214 1.5× 62 0.5× 13 0.1× 14 455
Tanvir Mahmud Bangladesh 13 373 2.1× 33 0.2× 177 1.3× 69 0.6× 33 0.3× 32 774
Xiao-Yun Zhou China 12 104 0.6× 13 0.1× 106 0.8× 164 1.4× 29 0.3× 34 473
Muhammad Adeel Azam Italy 8 104 0.6× 45 0.3× 147 1.0× 59 0.5× 6 0.1× 20 455
Yu‐Lin Wei China 13 33 0.2× 24 0.1× 91 0.6× 51 0.4× 98 1.0× 44 613
Mario Ceresa Spain 14 78 0.4× 24 0.1× 71 0.5× 127 1.0× 24 0.2× 49 683

Countries citing papers authored by Andrzej Skalski

Since Specialization
Citations

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

Fields of papers citing papers by Andrzej Skalski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrzej Skalski

This figure shows the co-authorship network connecting the top 25 collaborators of Andrzej Skalski. A scholar is included among the top collaborators of Andrzej Skalski 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 Andrzej Skalski. Andrzej Skalski 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.
Skalski, Andrzej, et al.. (2025). DECODE-3DViz: Efficient WebGL-Based High-Fidelity Visualization of Large-Scale Images using Level of Detail and Data Chunk Streaming. Journal of Imaging Informatics in Medicine. 38(6). 4148–4166. 1 indexed citations
2.
Skalski, Andrzej, et al.. (2024). Vessel Geometry Estimation for Patients with Peripheral Artery Disease. Sensors. 24(19). 6441–6441.
3.
Galyfos, George, et al.. (2024). Using a novel three-dimensional holographic technology to perform open vascular surgery procedures. Journal of Vascular Surgery Cases and Innovative Techniques. 10(2). 101440–101440. 4 indexed citations
4.
Kurzyna, Marcin, et al.. (2024). Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition. Cancers. 16(10). 1894–1894. 4 indexed citations
5.
Wodziński, Marek, et al.. (2023). DRU-Net: Pulmonary Artery Segmentation via Dense Residual U-Network with Hybrid Loss Function. Sensors. 23(12). 5427–5427. 6 indexed citations
6.
Skalski, Andrzej, et al.. (2023). Metrological Analysis of HoloLens 2 for Visual Marker-Based Surgical Navigation. 1–6. 2 indexed citations
7.
Wodziński, Marek, et al.. (2022). Deep learning-based framework for automatic cranial defect reconstruction and implant modeling. Computer Methods and Programs in Biomedicine. 226. 107173–107173. 18 indexed citations
8.
Wodziński, Marek, et al.. (2021). Semi-Supervised Deep Learning-Based Image Registration Method with Volume Penalty for Real-Time Breast Tumor Bed Localization. Sensors. 21(12). 4085–4085. 12 indexed citations
9.
Wodziński, Marek & Andrzej Skalski. (2020). Multistep, automatic and nonrigid image registration method for histology samples acquired using multiple stains. Physics in Medicine and Biology. 66(2). 25006–25006. 11 indexed citations
10.
Wodziński, Marek, et al.. (2020). Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network. Sensors. 20(19). 5695–5695. 7 indexed citations
11.
Wodziński, Marek, Andrzej Skalski, Alexander Witkowski, Giovanni Pellacani, & Joanna Łudzik. (2019). Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy. PubMed. 2019. 4754–4757. 22 indexed citations
12.
Skalski, Andrzej, Jacek Jakubowski, & Tomasz Drewniak. (2018). LEFMIS: locally-oriented evaluation framework for medical image segmentation algorithms. Physics in Medicine and Biology. 63(16). 165016–165016. 3 indexed citations
13.
Wodziński, Marek, et al.. (2018). Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms. Physics in Medicine and Biology. 63(3). 35024–35024. 8 indexed citations
14.
Skalski, Andrzej, et al.. (2018). Artificial database expansion based on hand position variability for palm vein biometric system. 58. 1–6. 3 indexed citations
15.
Skalski, Andrzej, Jacek Jakubowski, & Tomasz Drewniak. (2016). Kidney tumor segmentation and detection on Computed Tomography data. 238–242. 15 indexed citations
16.
17.
Skalski, Andrzej, et al.. (2012). Aplikacja wspierająca proces konturowania organów w danych medycznych. Pomiary, Automatyka, Kontrola. 323–326.
18.
Skalski, Andrzej. (2012). Modelowanie struktur anatomicznych dla potrzeb planowania leczenia w procesie radioterapii nowotworu prostaty. Pomiary Automatyka Kontrola. 372–375.
19.
Zieliński, Tomasz P., et al.. (2012). Comparison of ASM and AAM-based segmentation of prostate image in the CT scans for radiotherapy planning. 53–57. 4 indexed citations
20.
Skalski, Andrzej & Tomasz P. Zieliński. (2008). Segmentacja i dopasowywanie cyfrowych obrazów medycznych: przetwarzanie nagrań wideo-endoskopowych strun głosowych oraz danych tomograficznych zmian rakowych. Pomiary, Automatyka, Kontrola. 330–333. 1 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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