Federico Bolelli

1.1k total citations
37 papers, 462 citations indexed

About

Federico Bolelli is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Federico Bolelli has authored 37 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 9 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Artificial Intelligence. Recurrent topics in Federico Bolelli's work include Medical Image Segmentation Techniques (13 papers), Digital Image Processing Techniques (11 papers) and AI in cancer detection (6 papers). Federico Bolelli is often cited by papers focused on Medical Image Segmentation Techniques (13 papers), Digital Image Processing Techniques (11 papers) and AI in cancer detection (6 papers). Federico Bolelli collaborates with scholars based in Italy, Spain and Germany. Federico Bolelli's co-authors include Costantino Grana, Federico Pollastri, Stefano Allegretti, Lorenzo Baraldi, Roberto Paredes, Alexandre Anesi, Mattia Di Bartolomeo, Roberto Vezzani, Giulia Ligabue and Riccardo Magistroni and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Federico Bolelli

34 papers receiving 458 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Federico Bolelli Italy 13 200 119 96 84 69 37 462
Nicola Altini Italy 12 102 0.5× 172 1.4× 153 1.6× 18 0.2× 50 0.7× 26 343
Farhad Ghazvinian Zanjani Netherlands 9 149 0.7× 185 1.6× 147 1.5× 40 0.5× 54 0.8× 17 353
Alireza Norouzi Malaysia 10 368 1.8× 173 1.5× 144 1.5× 100 1.2× 86 1.2× 14 643
Mohd Ezane Aziz Malaysia 13 101 0.5× 113 0.9× 57 0.6× 66 0.8× 57 0.8× 43 499
Anjany Sekuboyina Germany 13 95 0.5× 70 0.6× 195 2.0× 73 0.9× 317 4.6× 31 620
Abdolvahab Ehsani Rad Malaysia 8 243 1.2× 157 1.3× 133 1.4× 142 1.7× 120 1.7× 16 496
Avi Ben-Cohen Israel 8 100 0.5× 209 1.8× 262 2.7× 23 0.3× 118 1.7× 10 594
D. R. Sarvamangala India 3 133 0.7× 194 1.6× 207 2.2× 18 0.2× 70 1.0× 5 541
Hyunseok Seo South Korea 9 314 1.6× 244 2.1× 266 2.8× 25 0.3× 84 1.2× 36 571

Countries citing papers authored by Federico Bolelli

Since Specialization
Citations

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

Fields of papers citing papers by Federico Bolelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Federico Bolelli

This figure shows the co-authorship network connecting the top 25 collaborators of Federico Bolelli. A scholar is included among the top collaborators of Federico Bolelli 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 Federico Bolelli. Federico Bolelli 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.
Ficarra, Elisa, et al.. (2025). Taming Mambas for 3D Medical Image Segmentation. IEEE Access. 13. 89748–89759.
2.
Bolelli, Federico, et al.. (2025). Segmenting Maxillofacial Structures in CBCT Volumes. CINECA IRIS Institutial research information system (University of Pisa). 5238–5248.
3.
Bolelli, Federico, et al.. (2025). State-of-the-art review and benchmarking of barcode localization methods. Engineering Applications of Artificial Intelligence. 147. 110259–110259.
4.
Bolelli, Federico, et al.. (2025). Machine Learning-Based Prediction of Emergency Department Prolonged Length of Stay: A Case Study from Italy. AHFE international. 160. 1 indexed citations
5.
Porrello, Angelo, et al.. (2025). Towards Unbiased Continual Learning: Avoiding Forgetting in the Presence of Spurious Correlations. IRIS UNIMORE (University of Modena and Reggio Emilia). 2527–2537. 1 indexed citations
6.
Bolelli, Federico, et al.. (2024). Enhancing Patch-Based Learning for the Segmentation of the Mandibular Canal. IEEE Access. 12. 79014–79024. 7 indexed citations
7.
Dréo, Johann, Sebastian Lobentanzer, Taru Muranen, et al.. (2024). High-level Biomedical Data Integration in a Semantic Knowledge Graph with OncodashKB for finding Personalized Actionable Drugs in Ovarian Cancer. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
8.
Bolelli, Federico, et al.. (2024). A State-of-the-Art Review With Code About Connected Components Labeling on GPUs. IEEE Transactions on Parallel and Distributed Systems. 37(4). 885–904. 2 indexed citations
9.
Bolelli, Federico, et al.. (2024). ClusterFix: A Cluster-Based Debiasing Approach without Protected-Group Supervision. IRIS UNIMORE (University of Modena and Reggio Emilia). 4858–4867. 1 indexed citations
10.
Bartolomeo, Mattia Di, Federico Bolelli, Stefano Allegretti, et al.. (2023). Inferior Alveolar Canal Automatic Detection with Deep Learning CNNs on CBCTs: Development of a Novel Model and Release of Open-Source Dataset and Algorithm. Applied Sciences. 13(5). 3271–3271. 9 indexed citations
11.
Bianchi, Giampaolo, Stefano Puliatti, Natali Rodriguez Peñaranda, et al.. (2023). Artificial intelligence evaluation of confocal microscope prostate images: our preliminary experience. Minerva Urology and Nephrology. 75(5). 545–547. 5 indexed citations
12.
Testa, Francesca, Francesco Fontana, Federico Pollastri, et al.. (2022). Automated Prediction of Kidney Failure in IgA Nephropathy with Deep Learning from Biopsy Images. Clinical Journal of the American Society of Nephrology. 17(9). 1316–1324. 13 indexed citations
13.
Bolelli, Federico, Stefano Allegretti, Roberto Paredes, et al.. (2021). The DeepHealth Toolkit: A Unified Framework to Boost Biomedical Applications. IRIS UNIMORE (University of Modena and Reggio Emilia). 9881–9888. 7 indexed citations
14.
Pollastri, Federico, Federico Bolelli, Giulia Ligabue, et al.. (2021). Confidence Calibration for Deep Renal Biopsy Immunofluorescence Image Classification. IRIS UNIMORE (University of Modena and Reggio Emilia). 1298–1305. 9 indexed citations
15.
Allegretti, Stefano, et al.. (2021). A Heuristic-Based Decision Tree for Connected Components Labeling of 3D Volumes. IRIS UNIMORE (University of Modena and Reggio Emilia). 7751–7758. 1 indexed citations
16.
Allegretti, Stefano, Federico Bolelli, & Costantino Grana. (2020). A Warp Speed Chain-Code Algorithm Based on Binary Decision Trees. IRIS UNIMORE (University of Modena and Reggio Emilia). 20. 1–8. 2 indexed citations
17.
Ligabue, Giulia, Federico Pollastri, Francesco Fontana, et al.. (2020). Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks. Clinical Journal of the American Society of Nephrology. 15(10). 1445–1454. 37 indexed citations
18.
Pollastri, Federico, Federico Bolelli, Roberto Paredes, & Costantino Grana. (2019). Augmenting data with GANs to segment melanoma skin lesions. Multimedia Tools and Applications. 79(21-22). 15575–15592. 60 indexed citations
19.
Pollastri, Federico, et al.. (2018). Improving Skin Lesion Segmentation with Generative Adversarial Networks. IRIS UNIMORE (University of Modena and Reggio Emilia). 442–443. 20 indexed citations
20.
Bolelli, Federico, et al.. (2018). Toward reliable experiments on the performance of Connected Components Labeling algorithms. Journal of Real-Time Image Processing. 17(2). 229–244. 23 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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