Abdel Aziz Taha

4.8k total citations · 2 hit papers
11 papers, 2.3k citations indexed

About

Abdel Aziz Taha is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Abdel Aziz Taha has authored 11 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Abdel Aziz Taha's work include Medical Image Segmentation Techniques (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Retinal Imaging and Analysis (3 papers). Abdel Aziz Taha is often cited by papers focused on Medical Image Segmentation Techniques (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Retinal Imaging and Analysis (3 papers). Abdel Aziz Taha collaborates with scholars based in Germany, Austria and United Kingdom. Abdel Aziz Taha's co-authors include Allan Hanbury, Orhun Utku Aydin, Dietmar Frey, Vince I. Madai, Michelle Livne, Ela M. Akay, Jan Sobesky, Ivana Galinović, Jochen B. Fiebach and Ahmed A. Khalil and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Data Engineering and Frontiers in Neuroscience.

In The Last Decade

Abdel Aziz Taha

11 papers receiving 2.3k citations

Hit 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.

Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool

2015 1.7k citations Abdel Aziz Taha, Allan Hanbury BMC Medical Imaging profile →
An Efficient Algorithm for Calculating the Exact Hausdorff Distance

2015 267 citations Abdel Aziz Taha, Allan Hanbury IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Abdel Aziz Taha Germany	8	935	806	460	410	331	11	2.3k
Zhong Xue United States	27	1.3k 1.4×	943 1.2×	378 0.8×	434 1.1×	330 1.0×	127	2.9k
Horst K. Hahn Germany	31	1.2k 1.3×	796 1.0×	427 0.9×	421 1.0×	239 0.7×	182	3.0k
Wenjia Bai United Kingdom	26	1.3k 1.4×	1.1k 1.4×	534 1.2×	372 0.9×	180 0.5×	91	2.9k
Zeike A. Taylor United Kingdom	23	897 1.0×	694 0.9×	783 1.7×	277 0.7×	360 1.1×	73	2.5k
Ozan Oktay United Kingdom	16	1.3k 1.4×	1.3k 1.6×	475 1.0×	817 2.0×	209 0.6×	29	2.7k
Vicente Grau United Kingdom	30	1.2k 1.3×	943 1.2×	669 1.5×	310 0.8×	283 0.9×	144	3.5k
Yipeng Hu United Kingdom	24	1.1k 1.2×	871 1.1×	617 1.3×	474 1.2×	938 2.8×	91	2.7k
Óscar Cámara Spain	28	1.1k 1.1×	606 0.8×	497 1.1×	220 0.5×	245 0.7×	154	3.0k
Yucheng Tang United States	18	1.2k 1.3×	1.3k 1.7×	482 1.0×	839 2.0×	273 0.8×	85	3.0k
Michiel Schaap Netherlands	23	1.5k 1.6×	1.2k 1.4×	581 1.3×	491 1.2×	405 1.2×	59	2.6k

Countries citing papers authored by Abdel Aziz Taha

Since Specialization

Citations

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

Fields of papers citing papers by Abdel Aziz Taha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Abdel Aziz Taha. 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 Abdel Aziz Taha. The network helps show where Abdel Aziz Taha may publish in the future.

Co-authorship network of co-authors of Abdel Aziz Taha

This figure shows the co-authorship network connecting the top 25 collaborators of Abdel Aziz Taha. A scholar is included among the top collaborators of Abdel Aziz Taha 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 Abdel Aziz Taha. Abdel Aziz Taha 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:

11 of 11 papers shown

1.

Aydin, Orhun Utku, Abdel Aziz Taha, Adam Hilbert, et al.. (2021). An evaluation of performance measures for arterial brain vessel segmentation. BMC Medical Imaging. 21(1). 113–113. 10 indexed citations

2.

Aydin, Orhun Utku, Abdel Aziz Taha, Adam Hilbert, et al.. (2021). On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking. European Radiology Experimental. 5(1). 4–4. 89 indexed citations

3.

Taha, Abdel Aziz, et al.. (2021). Formal Analysis and Estimation of Chance in Datasets Based on Their Properties. IEEE Transactions on Knowledge and Data Engineering. 34(12). 5784–5795. 1 indexed citations

4.

Hilbert, Adam, Vince I. Madai, Ela M. Akay, et al.. (2020). BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation in Patients With Cerebrovascular Disease. Frontiers in Artificial Intelligence. 3. 552258–552258. 56 indexed citations

5.

Livne, Michelle, Jana Rieger, Orhun Utku Aydin, et al.. (2019). A U-Net Deep Learning Framework for High Performance Vessel Segmentation in Patients With Cerebrovascular Disease. Frontiers in Neuroscience. 13. 97–97. 166 indexed citations

6.

Taha, Abdel Aziz & Allan Hanbury. (2015). Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool. BMC Medical Imaging. 15(1). 29–29. 1681 indexed citations breakdown →

7.

Göksel, Orçun, Antonio Foncubierta–Rodríguez, Henning Müller, et al.. (2015). Overview of the VISCERAL Challenge at ISBI 2015. 6–11. 5 indexed citations

8.

Hanbury, Allan, Orçun Göksel, Bjoern Menze, et al.. (2015). VISCERAL-VISual Concept Extraction challenge in RAdioLogy: Organsegmentierung: Übersicht, Einblicke und erste Ergebnisse. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 187(S 01). 4 indexed citations

9.

Taha, Abdel Aziz & Allan Hanbury. (2015). An Efficient Algorithm for Calculating the Exact Hausdorff Distance. IEEE Transactions on Pattern Analysis and Machine Intelligence. 37(11). 2153–2163. 267 indexed citations breakdown →

10.

Taha, Abdel Aziz, et al.. (2014). A formal method for selecting evaluation metrics for image segmentation. 932–936. 15 indexed citations

11.

Göksel, Orçun, Bjoern Menze, Georg Langs, et al.. (2014). VISCERAL | VISual Concept Extraction challenge in RAdioLogy: ISBI 2014 Challenge Organization. 10 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