Povilas Treigys

482 total citations
39 papers, 335 citations indexed

About

Povilas Treigys is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Povilas Treigys has authored 39 papers receiving a total of 335 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Povilas Treigys's work include Retinal Imaging and Analysis (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Maritime Navigation and Safety (5 papers). Povilas Treigys is often cited by papers focused on Retinal Imaging and Analysis (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Maritime Navigation and Safety (5 papers). Povilas Treigys collaborates with scholars based in Lithuania, Bulgaria and Poland. Povilas Treigys's co-authors include Jolita Bernatavičienė, Virginijus Marcinkevičius, Bożena Kostek, Gintautas Dzemyda, Arvydas Laurinavičius, Olga Kurasova, Aida Laurinavičienė, Artūras Kaklauskas, Miroslav Vozňák and Isidoros Perikos and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and The Journal of the Acoustical Society of America.

In The Last Decade

Povilas Treigys

33 papers receiving 313 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Povilas Treigys Lithuania	12	98	89	73	60	57	39	335
Ahmad Shaf Pakistan	15	131 1.3×	44 0.5×	211 2.9×	21 0.3×	125 2.2×	41	570
Xiaozheng Xie China	5	131 1.3×	64 0.7×	93 1.3×	10 0.2×	128 2.2×	12	344
Wei Xie China	11	100 1.0×	41 0.5×	41 0.6×	44 0.7×	11 0.2×	59	357
Hussam Qassim United States	3	100 1.0×	11 0.1×	139 1.9×	20 0.3×	48 0.8×	4	348
Ljiljana Šerić Croatia	10	79 0.8×	17 0.2×	71 1.0×	15 0.3×	13 0.2×	40	357
Khaled Bayoudh Tunisia	5	135 1.4×	19 0.2×	173 2.4×	25 0.4×	59 1.0×	6	408
Shailender Kumar India	10	183 1.9×	8 0.1×	96 1.3×	26 0.4×	81 1.4×	52	452
Manel Ayadi Saudi Arabia	11	95 1.0×	24 0.3×	81 1.1×	38 0.6×	28 0.5×	34	354

Countries citing papers authored by Povilas Treigys

Since Specialization

Citations

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

Fields of papers citing papers by Povilas Treigys

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Povilas Treigys

This figure shows the co-authorship network connecting the top 25 collaborators of Povilas Treigys. A scholar is included among the top collaborators of Povilas Treigys 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 Povilas Treigys. Povilas Treigys 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

Treigys, Povilas, et al.. (2025). Enhancing Maritime Safety: Estimating Collision Probabilities with Trajectory Prediction Boundaries Using Deep Learning Models. Sensors. 25(5). 1365–1365. 1 indexed citations

Bernatavičienė, Jolita, et al.. (2024). Advancements in prostate zone segmentation: integrating attention mechanisms into the nnU-Net framework. Machine Learning Science and Technology. 5(4). 45003–45003.

Treigys, Povilas, et al.. (2023). Investigation of Machine Learning Methods for Colour Audio Noise Suppression. 1–6. 1 indexed citations

Treigys, Povilas, et al.. (2023). Application of coordinate systems for vessel trajectory prediction improvement using a recurrent neural networks. Engineering Applications of Artificial Intelligence. 123. 106448–106448. 19 indexed citations

Treigys, Povilas, et al.. (2023). Usage of Isotropic MRI Images Impoves Prostate Cancer Localization Results. Baltic Journal of Modern Computing. 11(4). 1 indexed citations

Perikos, Isidoros, et al.. (2023). A Convolutional Autoencoder Approach for Boosting the Specificity of Retinal Blood Vessels Segmentation. Applied Sciences. 13(5). 3255–3255. 6 indexed citations

Treigys, Povilas, et al.. (2023). Investigation of the Lombard effect based on a machine learning approach. International Journal of Applied Mathematics and Computer Science. 33(3).

Bernatavičienė, Jolita, et al.. (2022). Impact of COVID-19-Related Lockdown Measures on Economic and Social Outcomes in Lithuania. Mathematics. 10(15). 2734–2734. 2 indexed citations

Bernatavičienė, Jolita, et al.. (2022). An Overview of Lithuanian Intonation: A Linguistic and Modelling Perspective. Informatica. 795–832. 2 indexed citations

10.

Treigys, Povilas, et al.. (2021). Unsupervised marine vessel trajectory prediction using LSTM network and wild bootstrapping techniques. Nonlinear Analysis Modelling and Control. 26(4). 718–737. 46 indexed citations

11.

Laurinavičius, Arvydas, et al.. (2021). Deep Learning Model for Cell Nuclei Segmentation and Lymphocyte Identification in Whole Slide Histology Images. Informatica. 23–40. 18 indexed citations

12.

Treigys, Povilas, et al.. (2021). High F-score Model for Recognizing Object Visibility in Images with Occluded Objects of Interest. Baltic Journal of Modern Computing. 9(1).

13.

Laurinavičienė, Aida, et al.. (2021). Tumor collagen framework from bright-field histology images predicts overall survival of breast carcinoma patients. Scientific Reports. 11(1). 15474–15474. 13 indexed citations

14.

Treigys, Povilas, et al.. (2020). A Study of Cross-Linguistic Speech Emotion Recognition Based on 2D Feature Spaces. Electronics. 9(10). 1725–1725. 26 indexed citations

15.

Treigys, Povilas, et al.. (2018). Analysis of 2D Feature Spaces for Deep Learning-Based Speech Recognition. Journal of the Audio Engineering Society. 66(12). 1072–1081. 29 indexed citations

16.

Kurasova, Olga, et al.. (2017). A new web-based solution for modelling data mining processes. Simulation Modelling Practice and Theory. 76. 34–46. 27 indexed citations

17.

Treigys, Povilas, et al.. (2016). Automated 2D Segmentation of Prostate in T2-weighted MRI Scans. International Journal of Computers Communications & Control. 12(1). 53–53. 4 indexed citations

18.

Veikutis, Vincentas, et al.. (2010). Analysis of Thermovisual Data of the Radio-Frequency Impact on the Myocardium Damage. Informatica. 21(3). 455–470. 1 indexed citations

19.

Veikutis, Vincentas, et al.. (2009). Monitoring changes in heart tissue temperature and evaluation of graft function after coronary artery bypass grafting surgery. Medicina. 45(3). 221–221. 7 indexed citations

20.

Treigys, Povilas, et al.. (2007). NEURAL NETWORK AS AN OPHTHALMOLOGIC DISEASE CLASSIFIER. Information Technology And Control. 36(4). 11 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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