Ali Emre Kavur

1.3k total citations
8 papers, 109 citations indexed

About

Ali Emre Kavur is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Ali Emre Kavur has authored 8 papers receiving a total of 109 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Artificial Intelligence. Recurrent topics in Ali Emre Kavur's work include Medical Image Segmentation Techniques (3 papers), COVID-19 diagnosis using AI (3 papers) and AI in cancer detection (2 papers). Ali Emre Kavur is often cited by papers focused on Medical Image Segmentation Techniques (3 papers), COVID-19 diagnosis using AI (3 papers) and AI in cancer detection (2 papers). Ali Emre Kavur collaborates with scholars based in Türkiye, Switzerland and Mexico. Ali Emre Kavur's co-authors include M. Alper Selver, Savaş Özkan, Gözde Bozdağı Akar, Bora Baydar, Mustafa Barış, Naciye Sinem Gezer, Oğuz Dıcle, Tim Rädsch, Tobias Roß and Lena Maier‐Hein and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Medical Physics.

In The Last Decade

Ali Emre Kavur

7 papers receiving 107 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ali Emre Kavur Türkiye	4	48	41	35	17	13	8	109
Adi Szeskin Israel	8	92 1.9×	40 1.0×	16 0.5×	38 2.2×	9 0.7×	11	173
Philipp Schad Germany	6	73 1.5×	52 1.3×	48 1.4×	31 1.8×	29 2.2×	11	189
Bora Baydar Türkiye	2	33 0.7×	21 0.5×	20 0.6×	10 0.6×	8 0.6×	3	59
Tzu-Ming Harry Hsu United States	9	51 1.1×	57 1.4×	25 0.7×	29 1.7×	11 0.8×	10	164
Refael Vivanti Israel	4	86 1.8×	47 1.1×	27 0.8×	32 1.9×	7 0.5×	5	130
Zhengqing Xu China	4	56 1.2×	28 0.7×	51 1.5×	12 0.7×	5 0.4×	10	112
Rijo Roy Germany	5	94 2.0×	77 1.9×	78 2.2×	37 2.2×	5 0.4×	6	225
Paul F. Jäger Germany	6	88 1.8×	60 1.5×	65 1.9×	33 1.9×	6 0.5×	18	188
Maxime Blain France	5	61 1.3×	19 0.5×	16 0.5×	23 1.4×	27 2.1×	12	124
Yiwen Zhang China	8	61 1.3×	21 0.5×	17 0.5×	20 1.2×	7 0.5×	20	119

Countries citing papers authored by Ali Emre Kavur

Since Specialization

Citations

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

Fields of papers citing papers by Ali Emre Kavur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali Emre Kavur. 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 Ali Emre Kavur. The network helps show where Ali Emre Kavur may publish in the future.

Co-authorship network of co-authors of Ali Emre Kavur

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

All Works

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8 of 8 papers shown

1.

Özkan, Savaş, et al.. (2024). Cross-Modal Learning via Adversarial Loss and Covariate Shift for Enhanced Liver Segmentation. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(4). 2723–2735. 4 indexed citations

2.

Rädsch, Tim, Annika Reinke, Vivienn Weru, et al.. (2023). Labelling instructions matter in biomedical image analysis. Nature Machine Intelligence. 5(3). 273–283. 37 indexed citations

3.

Kavur, Ali Emre, et al.. (2022). Chain code strategy for lossless storage and transfer of segmented binary medical data. Expert Systems with Applications. 216. 119449–119449. 3 indexed citations

4.

Gezer, Naciye Sinem, et al.. (2020). Reversible 3D compression of segmented medical volumes: usability analysis for teleradiology and storage. Medical Physics. 47(4). 1727–1737. 3 indexed citations

5.

Kavur, Ali Emre, Naciye Sinem Gezer, Mustafa Barış, et al.. (2019). Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors. Diagnostic and Interventional Radiology. 26(1). 11–21. 54 indexed citations

6.

Şahin, Savaş, et al.. (2017). Arduino ve LabVIEW Kullanarak EMG Verilerinden Eşik Seviye Belirleme ile Motor Kontrol Düzeneği Tasarımı. SHILAP Revista de lepidopterología. 22(2). 736–736.

7.

Selver, M. Alper, et al.. (2015). BATIN BÖLGESİ ORGANLARININ MR GÖRÜNTÜLERİNDEN ÇOK AŞAMALI HİYERARŞİK SINIFLAMA İLE BÖLÜTLENMESİ. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi. 30(3). 3 indexed citations

8.

Selver, M. Alper & Ali Emre Kavur. (2015). Implementation and use of 3D pairwise geodesic distance fields for seeding abdominal aortic vessels. International Journal of Computer Assisted Radiology and Surgery. 11(5). 803–816. 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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