João Pedrosa

895 total citations
51 papers, 506 citations indexed

About

João Pedrosa is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, João Pedrosa has authored 51 papers receiving a total of 506 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Radiology, Nuclear Medicine and Imaging, 23 papers in Cardiology and Cardiovascular Medicine and 11 papers in Biomedical Engineering. Recurrent topics in João Pedrosa's work include Cardiac Imaging and Diagnostics (14 papers), Cardiovascular Function and Risk Factors (14 papers) and COVID-19 diagnosis using AI (11 papers). João Pedrosa is often cited by papers focused on Cardiac Imaging and Diagnostics (14 papers), Cardiovascular Function and Risk Factors (14 papers) and COVID-19 diagnosis using AI (11 papers). João Pedrosa collaborates with scholars based in Portugal, Belgium and Germany. João Pedrosa's co-authors include Jan D’hooge, Jens‐Uwe Voigt, Pedro Santos, M Orlowska, Aniela Petrescu, Ana P. Pinheiro, Tiago T. V. Vinhoza, Ana Castro, Marta Cvijić and S Bezy and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Transactions on Medical Imaging.

In The Last Decade

João Pedrosa

40 papers receiving 499 citations

Peers

João Pedrosa

RNMI

CCM

PRM

CVPR

Emran Mohammad Abu Anas Canada

Alexander F. Kolen Netherlands

Shaojie Tang China

Maartje M. Nillesen Netherlands

Joseph Meyer United States

Angela Lee United Kingdom

Youjun Liu China

Sitthichok Chaichulee Thailand

Luca Neri Italy

Ofer Barnea Israel

Emran Mohammad Abu Anas Canada

João Pedrosa

202 ×0.7

RNMI

62 ×0.3

CCM

254 ×1.5

46 ×0.6

PRM

72 ×1.7

CVPR

Citations per year, relative to João Pedrosa João Pedrosa (= 1×) peers Emran Mohammad Abu Anas

Countries citing papers authored by João Pedrosa

Since Specialization

Citations

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

Fields of papers citing papers by João Pedrosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of João Pedrosa

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

Pedrosa, João, et al.. (2025). Grad-CAM: The impact of large receptive fields and other caveats. Computer Vision and Image Understanding. 258. 104383–104383. 2 indexed citations

Filipe, Vítor, et al.. (2025). Segmentation of coronary calcifications with a domain knowledge-based lightweight 3D convolutional neural network. Computers in Biology and Medicine. 196(Pt B). 110798–110798. 1 indexed citations

Santos, Carolina Gonçalves, et al.. (2025). Validation of a deep learning approach for epicardial adipose tissue segmentation in computed tomography. The International Journal of Cardiovascular Imaging. 42(3). 551–559.

Filipe, Vítor, et al.. (2024). Lightweight 3D CNN for the Segmentation of Coronary Calcifications and Calcium Scoring. 346–351. 2 indexed citations

Tabassian, Mahdi, et al.. (2024). BEAS-Net: A Shape-Prior-Based Deep Convolutional Neural Network for Robust Left Ventricular Segmentation in 2-D Echocardiography. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 71(11). 1565–1576.

Pedrosa, João, et al.. (2023). Lesion-Aware Chest Radiography Abnormality Classification with Object Detection Framework. 6. 806–813.

Pedrosa, João, et al.. (2023). Deep Feature-Based Automated Chest Radiography Compliance Assessment. 64–67.

Coimbra, Miguel, et al.. (2023). Deep Learning for Segmentation of the Left Ventricle in Echocardiography. 159–162.

Pedrosa, João, et al.. (2023). STERN: Attention-driven Spatial Transformer Network for abnormality detection in chest X-ray images. Artificial Intelligence in Medicine. 147. 102737–102737. 6 indexed citations

10.

Pedrosa, João, et al.. (2023). Semi-supervised Multi-structure Segmentation in Chest X-Ray Imaging. 814–820. 3 indexed citations

11.

Coimbra, Miguel, et al.. (2023). Assisted probe guidance in cardiac ultrasound: A review. Frontiers in Cardiovascular Medicine. 10. 1056055–1056055. 12 indexed citations

12.

Mauger, Charlène, Kathleen Gilbert, Vicky Y. Wang, et al.. (2023). Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping. Scientific Reports. 13(1). 8118–8118.

13.

Talou, Gonzalo D. Maso, Kathleen Gilbert, Vicky Y. Wang, et al.. (2023). MITEA: A dataset for machine learning segmentation of the left ventricle in 3D echocardiography using subject-specific labels from cardiac magnetic resonance imaging. Frontiers in Cardiovascular Medicine. 9. 1016703–1016703. 8 indexed citations

14.

Pedrosa, João, et al.. (2022). Attention-driven Spatial Transformer Network for Abnormality Detection in Chest X-Ray Images. 252–257. 2 indexed citations

15.

Orlowska, M, Alessandro Ramalli, Aniela Petrescu, et al.. (2020). A Novel 2-D Speckle Tracking Method for High-Frame-Rate Echocardiography. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 67(9). 1764–1775. 16 indexed citations

16.

Pedrosa, João, Jürgen Duchenne, Sandro Queirós, et al.. (2019). Non-invasive myocardial performance mapping using 3D echocardiographic stress–strain loops. Physics in Medicine and Biology. 64(11). 115026–115026. 1 indexed citations

17.

Petrescu, Aniela, Pedro Santos, M Orlowska, et al.. (2019). Velocities of Naturally Occurring Myocardial Shear Waves Increase With Age and in Cardiac Amyloidosis. JACC. Cardiovascular imaging. 12(12). 2389–2398. 58 indexed citations

18.

Santos, Pedro, Aniela Petrescu, João Pedrosa, et al.. (2018). Natural Shear Wave Imaging in the Human Heart: Normal Values, Feasibility, and Reproducibility. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 66(3). 442–452. 51 indexed citations

19.

Pinheiro, Ana P., et al.. (2016). Minho Affective Sentences (MAS): Probing the roles of sex, mood, and empathy in affective ratings of verbal stimuli. Behavior Research Methods. 49(2). 698–716. 22 indexed citations

20.

Pedrosa, João, Daniel Barbosa, Nuno Almeida, et al.. (2015). Cardiac Chamber Volumetric Assessment Using 3D Ultrasound - A Review. Current Pharmaceutical Design. 22(1). 105–121. 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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