Salar Razavi

460 total citations
10 papers, 190 citations indexed

About

Salar Razavi is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Salar Razavi has authored 10 papers receiving a total of 190 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Molecular Biology. Recurrent topics in Salar Razavi's work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Smart Agriculture and AI (3 papers). Salar Razavi is often cited by papers focused on AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Smart Agriculture and AI (3 papers). Salar Razavi collaborates with scholars based in Türkiye and Canada. Salar Razavi's co-authors include Hülya Yalçın, Mustafa E. Kamaşak, Susan J. Done, Dimitrios Androutsos, April Khademi, Fatma Tokat and İmam Şamil Yetik and has published in prestigious journals such as Computers in Biology and Medicine, Journal of Pathology Informatics and Istanbul Technical University Academic Open Archive (Istanbul Technical University).

In The Last Decade

Salar Razavi

10 papers receiving 182 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Salar Razavi Türkiye	6	89	77	59	41	37	10	190
Jason Causey United States	7	64 0.7×	21 0.3×	169 2.9×	14 0.3×	6 0.2×	13	253
Rayees Ahmad Dar India	4	149 1.7×	37 0.5×	114 1.9×	38 0.9×	34 0.9×	12	259
Suyash Bhardwaj India	3	46 0.5×	201 2.6×	42 0.7×	16 0.4×	103 2.8×	9	303
Muhammad Aminu United States	6	23 0.3×	8 0.1×	30 0.5×	24 0.6×	17 0.5×	17	133
Jasper Linmans Netherlands	7	61 0.7×	175 2.3×	39 0.7×	31 0.8×		9	278
Petr Walczysko Germany	7	24 0.3×	28 0.4×	15 0.3×	10 0.2×	2 0.1×	8	135
N.A. Kriti India	7	102 1.1×	19 0.2×	83 1.4×	48 1.2×	9 0.2×	11	160
Xiaoyue Xie China	4	11 0.1×	196 2.5×	17 0.3×	5 0.1×	79 2.1×	12	292
Alice Porebski France	8	22 0.2×	7 0.1×	7 0.1×	102 2.5×	18 0.5×	19	156
Dewei Hu United States	6	22 0.2×	9 0.1×	39 0.7×	45 1.1×		17	180

Countries citing papers authored by Salar Razavi

Since Specialization

Citations

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

Fields of papers citing papers by Salar Razavi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Salar Razavi

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

All Works

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10 of 10 papers shown

Razavi, Salar, et al.. (2022). MiNuGAN: Dual Segmentation of Mitoses and Nuclei Using Conditional GANs on Multi-center Breast H&E Images. Journal of Pathology Informatics. 13. 100002–100002. 17 indexed citations

Razavi, Salar, et al.. (2020). Nuclei Segmentation in Hematoxylin and Eosin (H&E)-Stained Histopathological Images Using a Deep Neural Network. 2. 1–5. 1 indexed citations

Razavi, Salar, et al.. (2019). Automated segmentation of cell membranes to evaluate HER2 status in whole slide images using a modified deep learning network. Computers in Biology and Medicine. 110. 164–174. 66 indexed citations

Kamaşak, Mustafa E., et al.. (2018). Segmentation of the main structures in Hematoxylin and Eosin images. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1–4. 2 indexed citations

Razavi, Salar, et al.. (2018). An Automated and Accurate Methodology to Assess Ki-67 Labeling Index of Immunohistochemical Staining Images of Breast Cancer Tissues. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1–5. 5 indexed citations

Kamaşak, Mustafa E., et al.. (2018). Automated cell segmentation and spot detection in fluorescence in situ hybridization staining to assess HER2 status in breast cancer. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 10. 1–4. 1 indexed citations

Razavi, Salar, et al.. (2017). Automatically diagnosing HER2 amplification status for breast cancer patients using large FISH images. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 6 indexed citations

Razavi, Salar & Hülya Yalçın. (2017). Using convolutional neural networks for plant classification. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1–4. 8 indexed citations

Razavi, Salar & Hülya Yalçın. (2016). Plant classification using group of features. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1957–1960. 3 indexed citations

10.

Yalçın, Hülya & Salar Razavi. (2016). Plant classification using convolutional neural networks. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1–5. 81 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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