Ana Maria Mendonc̨a

3.7k total citations · 1 hit paper
60 papers, 2.0k citations indexed

About

Ana Maria Mendonc̨a is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ana Maria Mendonc̨a has authored 60 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Radiology, Nuclear Medicine and Imaging, 24 papers in Ophthalmology and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ana Maria Mendonc̨a's work include Retinal Imaging and Analysis (27 papers), Glaucoma and retinal disorders (17 papers) and Retinal Diseases and Treatments (16 papers). Ana Maria Mendonc̨a is often cited by papers focused on Retinal Imaging and Analysis (27 papers), Glaucoma and retinal disorders (17 papers) and Retinal Diseases and Treatments (16 papers). Ana Maria Mendonc̨a collaborates with scholars based in Portugal, Netherlands and United States. Ana Maria Mendonc̨a's co-authors include Aurélio Campilho, Behdad Dashtbozorg, Adrián Galdrán, Pedro Costa, Maria Inês Meyer, Michael D. Abràmoff, Meindert Niemeijer, Pedro Quelhas, Luís Mendonça and Guilherme Aresta and has published in prestigious journals such as PLoS ONE, Biomaterials and Scientific Reports.

In The Last Decade

Ana Maria Mendonc̨a

56 papers receiving 1.9k citations

Hit Papers

1 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction

2006 668 citations Ana Maria Mendonc̨a, Aurélio Campilho IEEE Transactions on Medical Imaging profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ana Maria Mendonc̨a Portugal	17	1.5k	1.0k	960	231	151	60	2.0k
Xiangning Wang China	14	444 0.3×	334 0.3×	150 0.2×	127 0.5×	231 1.5×	58	1.4k
Adrián Colomer Spain	16	440 0.3×	226 0.2×	293 0.3×	323 1.4×	37 0.2×	56	796
Rahil Garnavi Australia	20	558 0.4×	319 0.3×	454 0.5×	486 2.1×	23 0.2×	52	1.4k
Darvin Yi United States	12	778 0.5×	212 0.2×	246 0.3×	359 1.6×	32 0.2×	26	1.2k
Yuhui Ma China	14	692 0.5×	262 0.3×	573 0.6×	279 1.2×	23 0.2×	36	1.4k
Luís de Sisternes United States	27	1.8k 1.2×	2.1k 2.0×	219 0.2×	48 0.2×	189 1.3×	79	2.5k
Wan Mimi Diyana Wan Zaki Malaysia	15	431 0.3×	188 0.2×	315 0.3×	131 0.6×	41 0.3×	105	804
H.L. Tanenbaum United States	13	654 0.4×	517 0.5×	519 0.5×	25 0.1×	41 0.3×	21	939
Fábio J. Ayres Canada	16	366 0.2×	121 0.1×	438 0.5×	429 1.9×	186 1.2×	42	954

Countries citing papers authored by Ana Maria Mendonc̨a

Since Specialization

Citations

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

Fields of papers citing papers by Ana Maria Mendonc̨a

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ana Maria Mendonc̨a. 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 Ana Maria Mendonc̨a. The network helps show where Ana Maria Mendonc̨a may publish in the future.

Co-authorship network of co-authors of Ana Maria Mendonc̨a

This figure shows the co-authorship network connecting the top 25 collaborators of Ana Maria Mendonc̨a. A scholar is included among the top collaborators of Ana Maria Mendonc̨a 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 Ana Maria Mendonc̨a. Ana Maria Mendonc̨a is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

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

Campilho, Aurélio, et al.. (2024). CLARE-XR: explainable regression-based classification of chest radiographs with label embeddings. Scientific Reports. 14(1). 31024–31024.

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

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

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

Campilho, Aurélio, et al.. (2023). Lightweight multi-scale classification of chest radiographs via size-specific batch normalization. Computer Methods and Programs in Biomedicine. 236. 107558–107558. 5 indexed citations

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

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

Pedrosa, João, Guilherme Aresta, Carlos Ferreira, et al.. (2022). Assessing clinical applicability of COVID-19 detection in chest radiography with deep learning. Scientific Reports. 12(1). 6596–6596. 5 indexed citations

10.

Araújo, Teresa, Guilherme Aresta, Luís Mendonça, et al.. (2020). DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images. Medical Image Analysis. 63. 101715–101715. 95 indexed citations

11.

Cunha, A., et al.. (2020). Conventional Filtering Versus U-Net Based Models for Pulmonary Nodule Segmentation in CT Images. Journal of Medical Systems. 44(4). 81–81. 31 indexed citations

12.

Melo, Tânia, Ana Maria Mendonc̨a, & Aurélio Campilho. (2020). Microaneurysm detection in color eye fundus images for diabetic retinopathy screening. Computers in Biology and Medicine. 126. 103995–103995. 37 indexed citations

13.

Araújo, Teresa, Guilherme Aresta, Luís Mendonça, et al.. (2020). Data Augmentation for Improving Proliferative Diabetic Retinopathy Detection in Eye Fundus Images. IEEE Access. 8. 182462–182474. 43 indexed citations

14.

Remeseiro, Beatriz, Ana Maria Mendonc̨a, & Aurélio Campilho. (2020). Automatic classification of retinal blood vessels based on multilevel thresholding and graph propagation. The Visual Computer. 37(6). 1247–1261. 11 indexed citations

15.

Costa, Pedro, Teresa Araújo, Guilherme Aresta, et al.. (2019). EyeWeS: Weakly Supervised Pre-Trained Convolutional Neural Networks for Diabetic Retinopathy Detection. TECNALIA Publications (Fundación TECNALIA Research & Innovation). 1–6. 25 indexed citations

16.

Ferreira, Carlos, et al.. (2019). Quantitative Assessment of Central Serous Chorioretinopathy in Angiographic Sequences of Retinal Images. Open Repository of the University of Porto (University of Porto). 2. 1–4. 4 indexed citations

17.

Araújo, Teresa, Ana Maria Mendonc̨a, & Aurélio Campilho. (2018). Parametric model fitting-based approach for retinal blood vessel caliber estimation in eye fundus images. PLoS ONE. 13(4). e0194702–e0194702. 8 indexed citations

18.

Cunha, A., et al.. (2018). An unsupervised metaheuristic search approach for segmentation and volume measurement of pulmonary nodules in lung CT scans. Expert Systems with Applications. 119. 415–428. 24 indexed citations

19.

Costa, Pedro, Adrián Galdrán, Maria Inês Meyer, et al.. (2017). End-to-End Adversarial Retinal Image Synthesis. IEEE Transactions on Medical Imaging. 37(3). 781–791. 288 indexed citations

20.

Mendonc̨a, Ana Maria, et al.. (2013). Automatic Lane Segmentation in TLC Images Using the Continuous Wavelet Transform. Computational and Mathematical Methods in Medicine. 2013. 1–19. 5 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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