Yulia Arzhaeva

1.7k total citations
25 papers, 417 citations indexed

About

Yulia Arzhaeva is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yulia Arzhaeva has authored 25 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Artificial Intelligence and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yulia Arzhaeva's work include AI in cancer detection (8 papers), COVID-19 diagnosis using AI (6 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Yulia Arzhaeva is often cited by papers focused on AI in cancer detection (8 papers), COVID-19 diagnosis using AI (6 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Yulia Arzhaeva collaborates with scholars based in Australia, Netherlands and Germany. Yulia Arzhaeva's co-authors include Bram van Ginneken, Eva M. van Rikxoort, Max A. Viergever, Ivana Išgum, Josien P. W. Pluim, Stefan Klein, Marius Staring, David M. J. Tax, Ryan Lagerstrom and Pim A. de Jong and has published in prestigious journals such as Scientific Reports, Food Chemistry and Pattern Recognition.

In The Last Decade

Yulia Arzhaeva

24 papers receiving 406 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yulia Arzhaeva Australia 11 174 167 113 95 62 25 417
Homero Schiabel Brazil 9 163 0.9× 122 0.7× 223 2.0× 113 1.2× 55 0.9× 71 352
Carl Sabottke United States 9 146 0.8× 41 0.2× 87 0.8× 40 0.4× 51 0.8× 18 531
Riqiang Gao United States 11 213 1.2× 97 0.6× 94 0.8× 115 1.2× 57 0.9× 34 340
Chuan Zhou China 11 183 1.1× 126 0.8× 146 1.3× 67 0.7× 36 0.6× 56 400
Jacob C. Reinhold United States 4 210 1.2× 105 0.6× 86 0.8× 34 0.4× 62 1.0× 7 393
Marek Wodziński Poland 12 163 0.9× 81 0.5× 193 1.7× 46 0.5× 66 1.1× 48 469
Radhika Sivaramakrishna United States 8 188 1.1× 130 0.8× 185 1.6× 87 0.9× 48 0.8× 14 369
Ryohei Nakayama Japan 13 276 1.6× 124 0.7× 245 2.2× 45 0.5× 74 1.2× 63 556
Quoc Dang Vu United Kingdom 7 130 0.7× 99 0.6× 166 1.5× 35 0.4× 38 0.6× 11 249
Turid Torheim United Kingdom 11 284 1.6× 60 0.4× 68 0.6× 42 0.4× 66 1.1× 16 449

Countries citing papers authored by Yulia Arzhaeva

Since Specialization
Citations

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

Fields of papers citing papers by Yulia Arzhaeva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yulia Arzhaeva

This figure shows the co-authorship network connecting the top 25 collaborators of Yulia Arzhaeva. A scholar is included among the top collaborators of Yulia Arzhaeva 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 Yulia Arzhaeva. Yulia Arzhaeva 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.
Barlow, Robert, et al.. (2025). Improving traceability and quality control in the red-meat industry through computer vision-driven physical meat feature tracking. Food Chemistry. 480. 143830–143830. 3 indexed citations
2.
Arzhaeva, Yulia, Mohammad Ali Armin, Chương V. Nguyen, et al.. (2024). Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis. 1–5.
3.
Wang, Dadong, et al.. (2024). Attention-based multi-residual network for lung segmentation in diseased lungs with custom data augmentation. Scientific Reports. 14(1). 28983–28983. 3 indexed citations
4.
Wang, Dadong, Yulia Arzhaeva, Maoying Qiao, et al.. (2020). Automated Pneumoconiosis Detection on Chest X-Rays Using Cascaded Learning with Real and Synthetic Radiographs. UNSWorks (University of New South Wales, Sydney, Australia). 1–6. 17 indexed citations
5.
Bryce, Nicole S., Justine Stehn, Stefan Zahler, et al.. (2019). High-Content Imaging of Unbiased Chemical Perturbations Reveals that the Phenotypic Plasticity of the Actin Cytoskeleton Is Constrained. Cell Systems. 9(5). 496–507.e5. 12 indexed citations
6.
Nickson, Carolyn, P. Procopio, Lisa Devereux, et al.. (2018). Prospective Validation of the NCI Breast Cancer Risk Assessment Tool and the Autodensity Mammographic Density Tool on 40,000 Australian Screening Program Participants. Journal of Global Oncology. 4(Supplement 2). 49s–49s. 2 indexed citations
7.
Bischof, Leanne, Martin Převorovský, Charalampos Rallis, et al.. (2016). Spotsizer: High-Throughput Quantitative Analysis of Microbial Growth. BioTechniques. 61(4). 191–201. 9 indexed citations
8.
Lagerstrom, Ryan, Katherine Holt, Yulia Arzhaeva, et al.. (2014). Pollen Image Classification Using the Classifynder System: Algorithm Comparison and a Case Study on New Zealand Honey. Advances in experimental medicine and biology. 823. 207–226. 18 indexed citations
9.
Bednarz, Tomasz, Dadong Wang, Yulia Arzhaeva, et al.. (2014). Cloud Based Toolbox for Image Analysis, Processing and Reconstruction Tasks. Advances in experimental medicine and biology. 823. 191–205. 6 indexed citations
10.
Wang, Dadong, Tomasz Bednarz, Yulia Arzhaeva, et al.. (2013). Cloud based Services for Biomedical Image Analysis. 350–357. 2 indexed citations
11.
Lagerstrom, Ryan, et al.. (2013). A comparison of classification algorithms within the Classifynder pollen imaging system. AIP conference proceedings. 250–259. 5 indexed citations
12.
Rikxoort, Eva M. van, Ivana Išgum, Yulia Arzhaeva, et al.. (2009). Adaptive local multi-atlas segmentation: Application to the heart and the caudate nucleus. Medical Image Analysis. 14(1). 39–49. 120 indexed citations
13.
Arzhaeva, Yulia, David M. J. Tax, & Bram van Ginneken. (2009). Dissimilarity-based classification in the absence of local ground truth: Application to the diagnostic interpretation of chest radiographs. Pattern Recognition. 42(9). 1768–1776. 22 indexed citations
14.
Arzhaeva, Yulia, Mathias Prokop, Keelin Murphy, et al.. (2009). Automated estimation of progression of interstitial lung disease in CT images. Medical Physics. 37(1). 63–73. 17 indexed citations
15.
Arzhaeva, Yulia, Laurens Hogeweg, Pim A. de Jong, Max A. Viergever, & Bram van Ginneken. (2009). Global and Local Multi-valued Dissimilarity-Based Classification: Application to Computer-Aided Detection of Tuberculosis. Lecture notes in computer science. 12(Pt 2). 724–731. 15 indexed citations
16.
Arzhaeva, Yulia, et al.. (2007). Computer‐aided detection of interstitial abnormalities in chest radiographs using a reference standard based on computed tomography. Medical Physics. 34(12). 4798–4809. 28 indexed citations
17.
Rikxoort, Eva M. van, Yulia Arzhaeva, & Bram van Ginneken. (2007). Automatic segmentation of the liver in computed tomography scans with voxel classification and atlas matching. 42 indexed citations
18.
Arzhaeva, Yulia, Eva M. van Rikxoort, & Bram van Ginneken. (2007). Automated segmentation of caudate nucleus in MR brain images with voxel classification. 4 indexed citations
19.
Arzhaeva, Yulia, Bram van Ginneken, & David M. J. Tax. (2006). Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiographs. 367–370. 3 indexed citations
20.
Arzhaeva, Yulia, David M. J. Tax, & Bram van Ginneken. (2006). Improving computer-aided diagnosis of interstitial disease in chest radiographs by combining one-class and two-class classifiers. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6144. 614458–614458. 3 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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