Suvadip Mukherjee

444 total citations
23 papers, 268 citations indexed

About

Suvadip Mukherjee is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Media Technology. According to data from OpenAlex, Suvadip Mukherjee has authored 23 papers receiving a total of 268 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 9 papers in Biophysics and 5 papers in Media Technology. Recurrent topics in Suvadip Mukherjee's work include Cell Image Analysis Techniques (9 papers), Advanced Fluorescence Microscopy Techniques (5 papers) and Image Processing Techniques and Applications (5 papers). Suvadip Mukherjee is often cited by papers focused on Cell Image Analysis Techniques (9 papers), Advanced Fluorescence Microscopy Techniques (5 papers) and Image Processing Techniques and Applications (5 papers). Suvadip Mukherjee collaborates with scholars based in United States, France and India. Suvadip Mukherjee's co-authors include Scott T. Acton, Barry Condron, Xiaojie Huang, Jean‐Christophe Olivo‐Marín, C. Perrey, Nitin Singhal, Saurav Basu, Thibault Lagache, Snehasis Mukherjee and Dipti Prasad Mukherjee and has published in prestigious journals such as Nature Communications, IEEE Transactions on Image Processing and IEEE Transactions on Medical Imaging.

In The Last Decade

Suvadip Mukherjee

23 papers receiving 264 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Suvadip Mukherjee United States 10 106 81 64 48 42 23 268
Md. Khayrul Bashar Japan 10 236 2.2× 73 0.9× 95 1.5× 16 0.3× 41 1.0× 34 416
Yasmin M. Kassim United States 10 163 1.5× 38 0.5× 45 0.7× 81 1.7× 56 1.3× 21 281
Zitao Zeng China 4 162 1.5× 32 0.4× 46 0.7× 121 2.5× 101 2.4× 6 303
Fátima N. S. de Medeiros Brazil 12 203 1.9× 42 0.5× 33 0.5× 185 3.9× 211 5.0× 23 502
Aryan Mobiny United States 8 34 0.3× 36 0.4× 10 0.2× 45 0.9× 81 1.9× 9 280
Sundaresh Ram United States 11 254 2.4× 43 0.5× 56 0.9× 61 1.3× 58 1.4× 46 431
Michael Majurski United States 8 112 1.1× 161 2.0× 83 1.3× 25 0.5× 50 1.2× 19 351
Sergey Kosov Germany 5 130 1.2× 63 0.8× 74 1.2× 63 1.3× 115 2.7× 9 307
E. Priya India 7 57 0.5× 37 0.5× 60 0.9× 28 0.6× 19 0.5× 40 207
D. P. Huijsmans Netherlands 10 275 2.6× 33 0.4× 35 0.5× 14 0.3× 44 1.0× 24 434

Countries citing papers authored by Suvadip Mukherjee

Since Specialization
Citations

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

Fields of papers citing papers by Suvadip Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suvadip Mukherjee

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

All Works

20 of 20 papers shown
1.
Mukherjee, Suvadip, et al.. (2025). Statistical analysis of spatial patterns in tumor microenvironment images. Nature Communications. 16(1). 3090–3090. 1 indexed citations
2.
Mukherjee, Suvadip, et al.. (2022). Domain Adapted Multitask Learning for Segmenting Amoeboid Cells in Microscopy. IEEE Transactions on Medical Imaging. 42(1). 42–54. 9 indexed citations
3.
Mukherjee, Suvadip, et al.. (2022). Spatial Analysis For Histopathology: A Statistical Approach. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). 1–5. 2 indexed citations
4.
Mukherjee, Suvadip, et al.. (2021). A Min-Max Based Hyperparameter Estimation For Domain-Adapted Segmentation Of Amoeboid Cells. HAL (Le Centre pour la Communication Scientifique Directe). 1869–1872. 2 indexed citations
5.
Mukherjee, Suvadip, et al.. (2021). A Robust and Versatile Framework to Compare Spike Detection Methods in Calcium Imaging of Neuronal Activity. HAL (Le Centre pour la Communication Scientifique Directe). 375–379. 1 indexed citations
6.
Mukherjee, Suvadip, Thibault Lagache, & Jean‐Christophe Olivo‐Marín. (2020). Evaluating the Stability of Spatial Keypoints via Cluster Core Correspondence Index. IEEE Transactions on Image Processing. 30. 386–401. 4 indexed citations
7.
Mukherjee, Suvadip, et al.. (2020). Generalizing the Statistical Analysis of Objects’ Spatial Coupling in Bioimaging. IEEE Signal Processing Letters. 27. 1085–1089. 5 indexed citations
8.
Chaudhury, Santanu, Anoop Namboodiri, Srirangaraj Setlur, et al.. (2017). Computer Vision, Graphics, and Image Processing. Lecture notes in computer science. 13 indexed citations
9.
Mukherjee, Suvadip, et al.. (2017). Lung nodule segmentation using deep learned prior based graph cut. 1205–1208. 29 indexed citations
10.
Singhal, Nitin, Suvadip Mukherjee, & C. Perrey. (2017). Automated assessment of endometrium from transvaginal ultrasound using Deep Learned Snake. 13 indexed citations
11.
Mukherjee, Suvadip, et al.. (2015). Visual attraction in Drosophila larvae develops during a critical period and is modulated by crowding conditions. Journal of Comparative Physiology A. 201(10). 1019–1027. 17 indexed citations
12.
Mukherjee, Suvadip & Scott T. Acton. (2015). Oriented filters for vessel contrast enhancement with local directional evidence. 503–506. 14 indexed citations
13.
Mukherjee, Suvadip & Scott T. Acton. (2014). Region Based Segmentation in Presence of Intensity Inhomogeneity Using Legendre Polynomials. IEEE Signal Processing Letters. 22(3). 298–302. 73 indexed citations
14.
Mukherjee, Suvadip, Saurav Basu, Barry Condron, & Scott T. Acton. (2013). Tree2Tree2: Neuron tracing in 3D. smc 9. 448–451. 13 indexed citations
15.
Mukherjee, Suvadip, et al.. (2013). Shape descriptors based on compressed sensing with application to neuron matching. 970–974. 6 indexed citations
16.
Mukherjee, Suvadip & Scott T. Acton. (2013). Vector field convolution medialness applied to neuron tracing. 665–669. 6 indexed citations
17.
Mukherjee, Suvadip, Barry Condron, & Scott T. Acton. (2013). Neuron segmentation with level sets. 17. 1078–1082. 1 indexed citations
18.
Acton, Scott T., Barry Condron, & Suvadip Mukherjee. (2013). Chasing The Neurome: Segmentation And Comparison Of Neurons. INFM-OAR (INFN Catania). 1–4. 1 indexed citations
19.
Mukherjee, Suvadip, Saurav Basu, Barry Condron, & Scott T. Acton. (2012). A geometric-statistical approach toward neuron matching. 1. 772–775. 3 indexed citations
20.
Mukherjee, Suvadip & Bhabatosh Chanda. (2011). A Robust Human Iris Verification Using a Novel Combination of Features. 1. 162–166. 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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