Amit Sethi

4.1k total citations · 2 hit papers
87 papers, 2.1k citations indexed

About

Amit Sethi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Amit Sethi has authored 87 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computer Vision and Pattern Recognition, 39 papers in Artificial Intelligence and 22 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Amit Sethi's work include AI in cancer detection (28 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Advanced Image Processing Techniques (11 papers). Amit Sethi is often cited by papers focused on AI in cancer detection (28 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Advanced Image Processing Techniques (11 papers). Amit Sethi collaborates with scholars based in India, United States and United Kingdom. Amit Sethi's co-authors include Abhishek Vahadane, Neeraj Kumar, Ruchika Verma, Katja Steiger, Iréne Esposito, Maximilian Baust, Tingying Peng, Nassir Navab, Anna Melissa Schlitter and Shadi Albarqouni and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Cancer Research and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Amit Sethi

74 papers receiving 2.1k 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.

A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology

2017 671 citations Neeraj Kumar, Ruchika Verma et al. profile →
Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images

2016 453 citations Abhishek Vahadane, Amit Sethi et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Amit Sethi India	20	1.3k	1.1k	738	321	187	87	2.1k
Óscar Déniz Spain	23	891 0.7×	1.4k 1.3×	210 0.3×	194 0.6×	153 0.8×	112	2.4k
Valery Naranjo Spain	25	588 0.5×	914 0.8×	1.1k 1.5×	120 0.4×	237 1.3×	155	2.3k
Tal Arbel Canada	25	661 0.5×	1.5k 1.3×	987 1.3×	105 0.3×	394 2.1×	97	2.8k
J. Shin United States	7	1.1k 0.9×	848 0.8×	1.0k 1.4×	89 0.3×	271 1.4×	7	2.5k
Weidi Xie United Kingdom	24	1.4k 1.1×	2.5k 2.3×	269 0.4×	133 0.4×	130 0.7×	62	4.0k
Enmin Song China	28	576 0.5×	943 0.9×	773 1.0×	58 0.2×	266 1.4×	142	2.7k
Jacob Scharcanski Brazil	26	515 0.4×	1.1k 1.0×	468 0.6×	97 0.3×	171 0.9×	116	2.1k
Martin Urschler Austria	22	652 0.5×	890 0.8×	789 1.1×	127 0.4×	476 2.5×	87	2.4k
Arnau Oliver Spain	32	1.4k 1.1×	1.8k 1.7×	1.3k 1.8×	150 0.5×	421 2.3×	107	3.6k
Zizhao Zhang United States	19	824 0.6×	789 0.7×	421 0.6×	63 0.2×	98 0.5×	42	1.6k

Countries citing papers authored by Amit Sethi

Since Specialization

Citations

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

Fields of papers citing papers by Amit Sethi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amit Sethi

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

20 of 20 papers shown

Sharma, Ashutosh, et al.. (2025). Towards improving breast cancer detection through multi-modal image generation. Ultrasonics. 153. 107655–107655.

Rogers, Christian, et al.. (2025). Enhancing stroke recovery assessment: A machine learning approach to real-world hand function analysis. International Journal of Medical Informatics. 204. 106077–106077. 1 indexed citations

Khvostikov, Alexander, et al.. (2024). Joint Super-resolution and Tissue Patch Classification for Whole Slide Histological Images. Programming and Computer Software. 50(3). 257–263.

Gann, Peter H., et al.. (2024). Deep Learning Predicts Subtype Heterogeneity and Outcomes in Luminal A Breast Cancer Using Routinely Stained Whole-Slide Images. Cancer Research Communications. 5(1). 157–166. 2 indexed citations

Sethi, Amit, et al.. (2024). Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers. 216–222. 1 indexed citations

Sethi, Amit, Joseph P. Grande, Ulrich Specks, & Fernando C. Fervenza. (2023). Proteomic profile of uninvolved versus crescentic glomeruli in MPO-ANCA-associated vasculitis. Clinical Kidney Journal. 16(7). 1180–1182. 5 indexed citations

Kumar, Neeraj, Peter H. Gann, Stephanie M. McGregor, & Amit Sethi. (2023). Quantification of subtype purity in Luminal A breast cancer predicts clinical characteristics and survival. Breast Cancer Research and Treatment. 200(2). 225–235. 6 indexed citations

Yadav, Subhash, et al.. (2023). Efficient quality control of whole slide pathology images with human-in-the-loop training. Journal of Pathology Informatics. 14. 100306–100306. 10 indexed citations

Sethi, Amit, et al.. (2023). Unsupervised learning framework for temperature compensated damage identification and localization in ultrasonic guided wave SHM with transfer learning. Ultrasonics. 130. 106931–106931. 48 indexed citations

10.

Sethi, Amit, et al.. (2021). Sample Specific Generalized Cross Entropy for Robust Histology Image Classification. 1934–1938. 11 indexed citations

11.

Anand, Deepak, et al.. (2020). Histographs: graphs in histopathology. 23–23. 34 indexed citations

12.

Kumar, Neeraj, Dan Zhao, Dulal K. Bhaumik, Amit Sethi, & Peter H. Gann. (2019). Quantification of intrinsic subtype ambiguity in Luminal A breast cancer and its relationship to clinical outcomes. BMC Cancer. 19(1). 215–215. 10 indexed citations

13.

Schonfeld, Dan, et al.. (2017). Color normalization of histology slides using graph regularized sparse NMF. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10140. 1014010–1014010. 9 indexed citations

14.

Sethi, Amit, Abhishek Vahadane, Ryan Deaton, et al.. (2016). Empirical comparison of color normalization methods for epithelial-stromal classification in H and E images. Journal of Pathology Informatics. 7(1). 17–17. 38 indexed citations

15.

Verma, Ruchika, Neeraj Kumar, Amit Sethi, & Peter H. Gann. (2016). Detecting multiple sub-types of breast cancer in a single patient. 2648–2652. 7 indexed citations

16.

Sachan, Devendra Singh, et al.. (2013). Sports video classification from multimodal information using deep neural networks. National Conference on Artificial Intelligence. 6 indexed citations

17.

Myrvold, Wendy, et al.. (2012). Maximum independent sets of the 120-cell and other regular polytopes. Ars Mathematica Contemporanea. 6(2). 197–210. 2 indexed citations

18.

Loschky, Lester C., et al.. (2010). The role of higher order image statistics in masking scene gist recognition. Attention Perception & Psychophysics. 72(2). 427–444. 38 indexed citations

19.

Loschky, Lester C., et al.. (2007). The importance of information localization in scene gist recognition.. Journal of Experimental Psychology Human Perception & Performance. 33(6). 1431–1450. 61 indexed citations

20.

Furukawa, Yasutaka, Amit Sethi, Jean Ponce, & David Kriegman. (2006). Robust structure and motion from outlines of smooth curved surfaces. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(2). 302–315. 17 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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