Kerem Can Tezcan

565 total citations
8 papers, 271 citations indexed

About

Kerem Can Tezcan is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Kerem Can Tezcan has authored 8 papers receiving a total of 271 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in Kerem Can Tezcan's work include Advanced MRI Techniques and Applications (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Imaging Techniques and Applications (2 papers). Kerem Can Tezcan is often cited by papers focused on Advanced MRI Techniques and Applications (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Imaging Techniques and Applications (2 papers). Kerem Can Tezcan collaborates with scholars based in Switzerland, Germany and United Kingdom. Kerem Can Tezcan's co-authors include Ender Konukoğlu, Roger Luechinger, Ender Konukoglu, Klaas P. Pruessmann, Christian F. Baumgartner, Sebastian Kozerke, Javier Alvarez-Valle, Ben Glocker, Shruthi Bannur and Aditya Nori and has published in prestigious journals such as Nature Communications, IEEE Transactions on Medical Imaging and Oncotarget.

In The Last Decade

Kerem Can Tezcan

8 papers receiving 268 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Kerem Can Tezcan	164	91	45	38	25	8	271
Kazuaki Nakane	125 0.8×	95 1.0×	44 1.0×	16 0.4×	21 0.8×	33	269
David Dov	158 1.0×	152 1.7×	42 0.9×	27 0.7×	28 1.1×	24	356
Şerban Morcovescu	86 0.5×	46 0.5×	120 2.7×	51 1.3×	10 0.4×	3	275
Soroosh Tayebi Arasteh	217 1.3×	185 2.0×	84 1.9×	35 0.9×	12 0.5×	25	455
Jia Gu	114 0.7×	64 0.7×	165 3.7×	51 1.3×	20 0.8×	35	332
Zhaobang Liu	197 1.2×	92 1.0×	68 1.5×	82 2.2×	21 0.8×	26	368
Firas Khader	192 1.2×	164 1.8×	84 1.9×	32 0.8×	10 0.4×	17	376
Farhad Ghazvinian Zanjani	147 0.9×	185 2.0×	149 3.3×	54 1.4×	16 0.6×	17	353
Shifeng Zhao	81 0.5×	41 0.5×	84 1.9×	52 1.4×	13 0.5×	27	277
Mika Pollari	110 0.7×	30 0.3×	55 1.2×	102 2.7×	11 0.4×	19	236

Countries citing papers authored by Kerem Can Tezcan

Since Specialization

Citations

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

Fields of papers citing papers by Kerem Can Tezcan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kerem Can Tezcan. 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 Kerem Can Tezcan. The network helps show where Kerem Can Tezcan may publish in the future.

Co-authorship network of co-authors of Kerem Can Tezcan

This figure shows the co-authorship network connecting the top 25 collaborators of Kerem Can Tezcan. A scholar is included among the top collaborators of Kerem Can Tezcan 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 Kerem Can Tezcan. Kerem Can Tezcan 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

Castro, Daniel C., Ryutaro Tanno, Anton Schwaighofer, et al.. (2022). Active label cleaning for improved dataset quality under resource constraints. Nature Communications. 13(1). 1161–1161. 55 indexed citations

Tezcan, Kerem Can, et al.. (2020). Unsupervised lesion detection via image restoration with a normative prior. Medical Image Analysis. 64. 101713–101713. 62 indexed citations

Tezcan, Kerem Can, et al.. (2019). Unsupervised Lesion Detection via Image Restoration with a Normative Prior. Repository for Publications and Research Data (ETH Zurich). 109. 540–556. 10 indexed citations

Tezcan, Kerem Can, Christian F. Baumgartner, Roger Luechinger, Klaas P. Pruessmann, & Ender Konukoğlu. (2018). MR Image Reconstruction Using Deep Density Priors. IEEE Transactions on Medical Imaging. 38(7). 1633–1642. 80 indexed citations

Tezcan, Kerem Can, Christian F. Baumgartner, & Ender Konukoğlu. (2017). MR image reconstruction using the learned data distribution as prior.. arXiv (Cornell University). 1 indexed citations

Wissmann, Lukas, Alexander Gotschy, Kerem Can Tezcan, et al.. (2016). Analysis of spatiotemporal fidelity in quantitative 3D first-pass perfusion cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. 19(1). 11–11. 15 indexed citations

Deuster, Constantin von, et al.. (2016). Bayesian intravoxel incoherent motion parameter mapping in the human heart. Journal of Cardiovascular Magnetic Resonance. 19(1). 85–85. 25 indexed citations

Oleksiuk, Olga, Mohammed Abba, Kerem Can Tezcan, et al.. (2015). Single-Molecule Localization Microscopy allows for the analysis of cancer metastasis-specific miRNA distribution on the nanoscale. Oncotarget. 6(42). 44745–44757. 23 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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