Alejandro F. Frangi

33.3k total citations · 5 hit papers
492 papers, 17.1k citations indexed

About

Alejandro F. Frangi is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Alejandro F. Frangi has authored 492 papers receiving a total of 17.1k indexed citations (citations by other indexed papers that have themselves been cited), including 179 papers in Radiology, Nuclear Medicine and Imaging, 159 papers in Computer Vision and Pattern Recognition and 92 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Alejandro F. Frangi's work include Medical Image Segmentation Techniques (111 papers), Intracranial Aneurysms: Treatment and Complications (70 papers) and Cerebrovascular and Carotid Artery Diseases (68 papers). Alejandro F. Frangi is often cited by papers focused on Medical Image Segmentation Techniques (111 papers), Intracranial Aneurysms: Treatment and Complications (70 papers) and Cerebrovascular and Carotid Artery Diseases (68 papers). Alejandro F. Frangi collaborates with scholars based in United Kingdom, Spain and United States. Alejandro F. Frangi's co-authors include Jian Yang, Jingyu Yang, David Zhang, Nassir Navab, Joachim Hornegger, William M. Wells, Wiro J. Niessen, Max A. Viergever, Julia A. Schnabel and Daniel Rueckert and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Alejandro F. Frangi

468 papers receiving 16.5k citations

Hit Papers

Two-dimensional pca: a new approach to appearance-based f... 2004 2026 2011 2018 2004 2015 2005 2015 2020 500 1000 1.5k 2.0k 2.5k
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.

  1. Two-dimensional pca: a new approach to appearance-based face representation and recognition
    2004 2.5k citations Jian Yang, David Zhang et al. profile →
  2. Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015
    2015 1.8k citations Nassir Navab, Alejandro F. Frangi et al. Lecture notes in computer science profile →
  3. KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition
    2005 608 citations Jian Yang, Alejandro F. Frangi et al. profile →
  4. Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015
    2015 346 citations Alejandro F. Frangi, Nassir Navab et al. Lecture notes in computer science profile →
  5. CS 2 -Net: Deep learning segmentation of curvilinear structures in medical imaging
    2020 240 citations Yitian Zhao, Huazhu Fu et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alejandro F. Frangi United Kingdom 54 6.7k 4.4k 2.6k 2.3k 2.2k 492 17.1k
Wiro J. Niessen Netherlands 70 4.5k 0.7× 7.3k 1.6× 2.6k 1.0× 3.7k 1.6× 2.1k 1.0× 541 19.5k
Jerry L. Prince United States 63 9.0k 1.3× 9.7k 2.2× 3.7k 1.4× 1.1k 0.5× 1.8k 0.8× 582 21.8k
Nicholas Ayache France 77 11.6k 1.7× 8.0k 1.8× 4.5k 1.7× 1.2k 0.5× 1.9k 0.9× 447 23.2k
Sébastien Ourselin United Kingdom 76 5.1k 0.8× 10.2k 2.3× 4.7k 1.8× 1.7k 0.8× 594 0.3× 812 26.7k
Milan Sonka United States 63 6.2k 0.9× 11.2k 2.5× 4.7k 1.8× 3.7k 1.6× 1.8k 0.8× 418 23.4k
Simon K. Warfield United States 68 4.6k 0.7× 7.8k 1.8× 2.4k 0.9× 3.7k 1.6× 400 0.2× 449 21.5k
Frederik Maes Belgium 50 5.1k 0.8× 5.3k 1.2× 2.1k 0.8× 1.1k 0.5× 711 0.3× 307 13.5k
Paul Suetens Belgium 63 6.2k 0.9× 7.0k 1.6× 4.2k 1.6× 889 0.4× 850 0.4× 429 17.4k
Max A. Viergever Netherlands 85 13.9k 2.1× 17.9k 4.0× 6.4k 2.4× 3.9k 1.7× 1.6k 0.7× 563 35.8k
Joseph V. Hajnal United Kingdom 80 3.2k 0.5× 11.2k 2.5× 2.5k 0.9× 2.2k 1.0× 841 0.4× 546 24.4k

Countries citing papers authored by Alejandro F. Frangi

Since Specialization
Citations

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

Fields of papers citing papers by Alejandro F. Frangi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alejandro F. Frangi. 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 Alejandro F. Frangi. The network helps show where Alejandro F. Frangi may publish in the future.

Co-authorship network of co-authors of Alejandro F. Frangi

This figure shows the co-authorship network connecting the top 25 collaborators of Alejandro F. Frangi. A scholar is included among the top collaborators of Alejandro F. Frangi 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 Alejandro F. Frangi. Alejandro F. Frangi 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.
Lassila, Toni, et al.. (2024). Accelerated simulation methodologies for computational vascular flow modelling. Journal of The Royal Society Interface. 21(211). 20230565–20230565. 8 indexed citations
2.
Wang, Xingce, et al.. (2024). Vector-Aware Anisotropic Gauge Equivariant Mesh Convolution Network for 3D Aneurysm Detection. Research Explorer (The University of Manchester). 248–256. 1 indexed citations
3.
Xie, Jianyang, Quanyong Yi, Yufei Wu, et al.. (2023). Deep segmentation of OCTA for evaluation and association of changes of retinal microvasculature with Alzheimer’s disease and mild cognitive impairment. British Journal of Ophthalmology. 108(3). 432–439. 24 indexed citations
4.
Frangi, Alejandro F., Marleen de Bruijne, Demián Wassermann, & Nassir Navab. (2023). Information Processing in Medical Imaging. Lecture notes in computer science. 9 indexed citations
5.
Aviyente, Selin, Alejandro F. Frangi, Erik Meijering, et al.. (2023). From Nano to Macro: An overview of the IEEE Bio Image and Signal Processing Technical Committee. IEEE Signal Processing Magazine. 40(4). 61–71. 1 indexed citations
6.
Xia, Yan, et al.. (2023). High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning. Computer Methods and Programs in Biomedicine. 230. 107355–107355. 14 indexed citations
7.
Frood, Russell, Matthew Clark, Cathy Burton, et al.. (2022). Discovery of Pre-Treatment FDG PET/CT-Derived Radiomics-Based Models for Predicting Outcome in Diffuse Large B-Cell Lymphoma. Cancers. 14(7). 1711–1711. 20 indexed citations
8.
Zhang, Xiaoqin, Runhua Jiang, Pengcheng Huang, et al.. (2022). Dynamic feature learning for COVID-19 segmentation and classification. Computers in Biology and Medicine. 150. 106136–106136. 6 indexed citations
9.
Frood, Russell, Christopher Burton, Charalampos Tsoumpas, et al.. (2021). Baseline PET/CT imaging parameters for prediction of treatment outcome in Hodgkin and diffuse large B cell lymphoma: a systematic review. European Journal of Nuclear Medicine and Molecular Imaging. 48(10). 3198–3220. 51 indexed citations
10.
Attanasio, Aleks, Bruno Scaglioni, Matteo Leonetti, et al.. (2020). Autonomous Tissue Retraction in Robotic Assisted Minimally Invasive Surgery – A Feasibility Study. IEEE Robotics and Automation Letters. 5(4). 6528–6535. 46 indexed citations
11.
Lassila, Toni, et al.. (2019). Population‐specific modelling of between/within‐subject flow variability in the carotid arteries of the elderly. International Journal for Numerical Methods in Biomedical Engineering. 36(1). e3271–e3271. 9 indexed citations
12.
Frangi, Alejandro F., et al.. (2018). Multi-Task Learning Approach for Natural Images' Quality Assessment. Journal of Telecommunication Electronic and Computer Engineering (JTEC). 10. 1–7. 2 indexed citations
13.
Huang, Yawen, Ling Shao, & Alejandro F. Frangi. (2017). Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning. IEEE Transactions on Medical Imaging. 37(3). 815–827. 56 indexed citations
14.
Craene, Mathieu De, Gemma Piella, Óscar Cámara, et al.. (2011). Temporal diffeomorphic free-form deformation: Application to motion and strain estimation from 3D echocardiography. Medical Image Analysis. 16(2). 427–450. 90 indexed citations
15.
Pashaei, Ali, et al.. (2009). A mesh-less approach for fast estimation of electrical activation time in the ventricular wall. Research Explorer (The University of Manchester). 209–212. 2 indexed citations
16.
Barber, D C, Estanislao Oubel, Alejandro F. Frangi, & D. Rodney Hose. (2007). Efficient computational fluid dynamics mesh generation by image registration. Medical Image Analysis. 11(6). 648–662. 58 indexed citations
17.
Frangi, Alejandro F., Amir A. Amini, & E. Bullitt. (2005). Vascular Imaging. IEEE Transactions on Medical Imaging. 1 indexed citations
18.
Yang, Jian, Jian Yang, Zhong Jin, et al.. (2004). Essence of kernel Fisher discriminant: KPCA plus LDA. Pattern Recognition. 37(10). 2097–2100. 116 indexed citations
19.
Yang, Jian, Jian Yang, Alejandro F. Frangi, Jingyu Yang, & Jingyu Yang. (2003). A new kernel Fisher discriminant algorithm with application to face recognition. Neurocomputing. 56. 415–421. 27 indexed citations
20.
Frangi, Alejandro F.. (1996). A new regularized BE formulation for Kirchhoff plates. European Journal of Mechanics - A/Solids. 15(5). 915–931. 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Wiro J. Niessen Breakdown of academic impact, for papers by Jerry L. Prince Breakdown of academic impact, for papers by Nicholas Ayache Breakdown of academic impact, for papers by Sébastien Ourselin Breakdown of academic impact, for papers by Milan Sonka Breakdown of academic impact, for papers by Simon K. Warfield Breakdown of academic impact, for papers by Frederik Maes Breakdown of academic impact, for papers by Paul Suetens Breakdown of academic impact, for papers by Max A. Viergever Breakdown of academic impact, for papers by Joseph V. Hajnal
Rankless by CCL
2026