Ján Margeta

662 total citations
9 papers, 220 citations indexed

About

Ján Margeta is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ján Margeta has authored 9 papers receiving a total of 220 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Cognitive Neuroscience, 3 papers in Biomedical Engineering and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ján Margeta's work include Hearing Loss and Rehabilitation (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Imaging and Analysis (2 papers). Ján Margeta is often cited by papers focused on Hearing Loss and Rehabilitation (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Imaging and Analysis (2 papers). Ján Margeta collaborates with scholars based in France, Denmark and United Kingdom. Ján Margeta's co-authors include Nicholas Ayache, Daniel Lee, Antonio Criminisi, Pau Medrano−Gracia, Mustafa Elattar, Ahmed S. Fahmy, Avan Suinesiaputra, Alan H. Kadish, Alistair A. Young and Ayman M. Khalifa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Medical Image Analysis and Journal of Clinical Medicine.

In The Last Decade

Ján Margeta

7 papers receiving 217 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ján Margeta France	5	122	86	54	41	35	9	220
Fatemeh Abdolali Iran	8	101 0.8×	42 0.5×	19 0.4×	95 2.3×	85 2.4×	18	311
Jyothi Samanth India	8	76 0.6×	43 0.5×	95 1.8×	45 1.1×	50 1.4×	24	308
Chiun-Li Chin Taiwan	9	52 0.4×	70 0.8×	21 0.4×	73 1.8×	48 1.4×	39	267
Parisa Gifani Iran	9	186 1.5×	65 0.8×	66 1.2×	43 1.0×	90 2.6×	22	310
Yunbi Liu China	10	218 1.8×	87 1.0×	14 0.3×	71 1.7×	113 3.2×	17	368
Shanxing Ou China	11	94 0.8×	86 1.0×	116 2.1×	66 1.6×	39 1.1×	36	325
Mohammed Yaqoob Qatar	6	45 0.4×	32 0.4×	77 1.4×	43 1.0×	42 1.2×	11	201
Yujia Xu United Kingdom	7	150 1.2×	42 0.5×	16 0.3×	48 1.2×	98 2.8×	11	286
Caizi Li China	7	59 0.5×	52 0.6×	14 0.3×	35 0.9×	28 0.8×	14	150

Countries citing papers authored by Ján Margeta

Since Specialization

Citations

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

Fields of papers citing papers by Ján Margeta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ján Margeta

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

All Works

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9 of 9 papers shown

Li, W., et al.. (2025). A systematic review of automated temporal bone segmentation methods. SHILAP Revista de lepidopterología. 10. 100195–100195.

Margeta, Ján, et al.. (2024). Deep reinforcement learning and convolutional autoencoders for anomaly detection of congenital inner ear malformations in clinical CT images. Computerized Medical Imaging and Graphics. 113. 102343–102343. 5 indexed citations

Hussain, Raabid, Ján Margeta, Zihao Wang, et al.. (2023). Anatomical Variations of the Human Cochlea Using an Image Analysis Tool. Journal of Clinical Medicine. 12(2). 509–509. 9 indexed citations

Margeta, Ján, Raabid Hussain, Dan Gnansia, et al.. (2022). A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies. Journal of Clinical Medicine. 11(22). 6640–6640. 19 indexed citations

Margeta, Ján, et al.. (2022). Deep Reinforcement Learning for Detection of Abnormal Anatomies. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 3. 3 indexed citations

Margeta, Ján, et al.. (2015). Fine-tuned convolutional neural nets for cardiac MRI acquisition plane recognition. Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization. 5(5). 339–349. 64 indexed citations

Margeta, Ján, Loïc Le Folgoc, Yuki Komatsu, et al.. (2015). Local late gadolinium enhancement features to identify the electrophysiological substrate of post-infarction ventricular tachycardia: a machine learning approach. Journal of Cardiovascular Magnetic Resonance. 17. P234–P234.

Suinesiaputra, Avan, Brett R. Cowan, Mustafa Elattar, et al.. (2013). A collaborative resource to build consensus for automated left ventricular segmentation of cardiac MR images. Medical Image Analysis. 18(1). 50–62. 119 indexed citations

Bojanić, Nebojša, et al.. (1968). [Cavernous hemangioma of maxillary sinus].. PubMed. 96(9). 915–9. 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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