Giacomo Tarroni

2.7k total citations
30 papers, 377 citations indexed

About

Giacomo Tarroni is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, Giacomo Tarroni has authored 30 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Cardiology and Cardiovascular Medicine and 6 papers in Biomedical Engineering. Recurrent topics in Giacomo Tarroni's work include Cardiac Imaging and Diagnostics (10 papers), Advanced MRI Techniques and Applications (10 papers) and Birth, Development, and Health (5 papers). Giacomo Tarroni is often cited by papers focused on Cardiac Imaging and Diagnostics (10 papers), Advanced MRI Techniques and Applications (10 papers) and Birth, Development, and Health (5 papers). Giacomo Tarroni collaborates with scholars based in Italy, United Kingdom and United States. Giacomo Tarroni's co-authors include Wenjia Bai, Daniel Rueckert, Paul M. Matthews, Hideaki Suzuki, Shuo Wang, Declan P. O’Regan, Enrico Grisan, Stefan Neubauer, Yike Guo and Jian Huang and has published in prestigious journals such as Nature Medicine, Scientific Reports and Radiology.

In The Last Decade

Giacomo Tarroni

28 papers receiving 375 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Giacomo Tarroni Italy 10 172 118 70 61 59 30 377
Kristin McLeod Norway 9 106 0.6× 120 1.0× 53 0.8× 78 1.3× 64 1.1× 17 331
Matthew Sinclair United Kingdom 12 230 1.3× 173 1.5× 87 1.2× 60 1.0× 53 0.9× 23 395
Esther Puyol‐Antón United Kingdom 12 262 1.5× 247 2.1× 91 1.3× 43 0.7× 55 0.9× 40 481
Carlos Martín-Isla Spain 9 219 1.3× 106 0.9× 101 1.4× 31 0.5× 64 1.1× 14 371
Danilo Babin Belgium 12 151 0.9× 120 1.0× 64 0.9× 114 1.9× 54 0.9× 38 355
Cristian Izquierdo Spain 6 203 1.2× 90 0.8× 93 1.3× 23 0.4× 51 0.9× 6 339
Mousumi Bhaduri Canada 12 158 0.9× 94 0.8× 71 1.0× 123 2.0× 75 1.3× 20 381
Pankaj K. Jain India 11 222 1.3× 190 1.6× 39 0.6× 42 0.7× 105 1.8× 12 454
Huaxuan Wen China 12 142 0.8× 38 0.3× 50 0.7× 83 1.4× 126 2.1× 33 540
Carlo Biffi United Kingdom 5 114 0.7× 72 0.6× 38 0.5× 58 1.0× 30 0.5× 8 194

Countries citing papers authored by Giacomo Tarroni

Since Specialization
Citations

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

Fields of papers citing papers by Giacomo Tarroni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giacomo Tarroni

This figure shows the co-authorship network connecting the top 25 collaborators of Giacomo Tarroni. A scholar is included among the top collaborators of Giacomo Tarroni 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 Giacomo Tarroni. Giacomo Tarroni 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.
Tzelepis, Christos, et al.. (2024). DISYRE: Diffusion-Inspired Synthetic Restoration for Unsupervised Anomaly Detection. City Research Online (City University London). 1–5.
2.
Weyde, Tillman, et al.. (2023). Quaternion Anti-Transfer Learning for Speech Emotion Recognition. City Research Online (City University London). 1–5. 1 indexed citations
3.
Chen, Chen, Chen Qin, Cheng Ouyang, et al.. (2022). Enhancing MR image segmentation with realistic adversarial data augmentation. Medical Image Analysis. 82. 102597–102597. 29 indexed citations
4.
Tarroni, Giacomo, et al.. (2021). Anomaly detection through latent space restoration using vector-quantized variational autoencoders. Spiral (Imperial College London). 23 indexed citations
5.
Tarroni, Giacomo, Wenjia Bai, Ozan Oktay, et al.. (2020). Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank. Scientific Reports. 10(1). 2408–2408. 16 indexed citations
6.
Bai, Wenjia, Hideaki Suzuki, Jian Huang, et al.. (2020). A population-based phenome-wide association study of cardiac and aortic structure and function. Nature Medicine. 26(10). 1654–1662. 114 indexed citations
7.
Tarroni, Giacomo, Ozan Oktay, Wenjia Bai, et al.. (2018). Learning-Based Quality Control for Cardiac MR Images. IEEE Transactions on Medical Imaging. 38(5). 1127–1138. 37 indexed citations
8.
Leong, Rupert W., et al.. (2015). Semiautomatic detection of villi in confocal endoscopy for the evaluation of celiac disease. PubMed. 2015. 8143–8146. 5 indexed citations
9.
Tarroni, Giacomo, Silvia Visentin, Erich Cosmi, & Enrico Grisan. (2015). Fully-automated identification and segmentation of aortic lumen from fetal ultrasound images. PubMed. 2015. 153–156. 4 indexed citations
10.
Tarroni, Giacomo, Silvia Visentin, Erich Cosmi, & Enrico Grisan. (2015). A novel approach to aortic intima-media thickness quantification from fetal ultrasound images. Research Padua Archive (University of Padua). 858–861. 1 indexed citations
11.
12.
Tarroni, Giacomo, Silvia Visentin, Erich Cosmi, & Enrico Grisan. (2014). Near-automated quantification of prenatal aortic intima-media thickness from ultrasound images. Computing in Cardiology. 313–316. 2 indexed citations
13.
Marino, Marco, et al.. (2014). Fully automated assessment of left ventricular volumes, function and mass from cardiac MRI. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 109–112. 2 indexed citations
14.
Veronese, E., et al.. (2014). Estimation of prenatal aorta intima-media thickness from ultrasound examination. Physics in Medicine and Biology. 59(21). 6355–6371. 8 indexed citations
15.
Tarroni, Giacomo, et al.. (2011). Automatic quantification of cardiac scar extent from late gadolinium enhancement magnetic resonance imaging. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 405–408. 2 indexed citations
16.
Votta, Emiliano, Daniele De Marchi, Giacomo Tarroni, et al.. (2011). Left ventricular modelling: a quantitative functional assessment tool based on cardiac magnetic resonance imaging. Interface Focus. 1(3). 384–395. 16 indexed citations
17.
Azarine, Arshid, et al.. (2010). Estimation of right ventricular volume, quantitative assessment of wall motion and trabeculae mass in arrhythmogenic right ventricular dysplasia. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 805–808. 2 indexed citations
18.
Tarroni, Giacomo, Federico Veronesi, James J. Walter, et al.. (2010). MRI-based quantification of myocardial perfusion at rest and stress using automated frame-by-frame segmentation and non-rigid registration. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1–4. 5 indexed citations
19.
Strumìa, Renata, et al.. (1992). Skin Lesions in Kidney Transplant Recipients. ˜The œNephron journals/Nephron journals. 62(2). 137–141. 26 indexed citations
20.
Pagano, Patrick J., et al.. (1990). A modelistic approach to evaluate the factors affecting the 137Cs transfer from mother to fetus in cattle.. PubMed. 97(11). 452–6. 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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