Arunava Chakravarty

742 total citations
18 papers, 531 citations indexed

About

Arunava Chakravarty is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Arunava Chakravarty has authored 18 papers receiving a total of 531 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Ophthalmology and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Arunava Chakravarty's work include Retinal Imaging and Analysis (13 papers), Retinal Diseases and Treatments (6 papers) and Glaucoma and retinal disorders (6 papers). Arunava Chakravarty is often cited by papers focused on Retinal Imaging and Analysis (13 papers), Retinal Diseases and Treatments (6 papers) and Glaucoma and retinal disorders (6 papers). Arunava Chakravarty collaborates with scholars based in India, Netherlands and Austria. Arunava Chakravarty's co-authors include Jayanthi Sivaswamy, Gopal Datt Joshi, Debdoot Sheet, S. R. Krishnadas, Ramanathan Sethuraman, Ursula Schmidt‐Erfurth, Bram van Ginneken, Clara I. Sá‎nchez, Thomas Theelen and Johan H. Mentink and has published in prestigious journals such as Applied Physics Letters, IEEE Transactions on Medical Imaging and Computer Methods and Programs in Biomedicine.

In The Last Decade

Arunava Chakravarty

18 papers receiving 514 citations

Peers

Arunava Chakravarty

RNMI

OPHTH

CVPR

Francisco Fumero Spain

Sajib Saha Australia

Neha Gour India

Ahmed ElTanboly United States

Ling Dai China

Sourya Sengupta Canada

E Simon Barriga United States

Julian Zilly Switzerland

A. Krishna Rao India

Pengxiao Zang United States

Francisco Fumero Spain

Arunava Chakravarty

490 ×1.1

RNMI

389 ×1.2

OPHTH

322 ×1.3

CVPR

79 ×0.8

34 ×0.7

Citations per year, relative to Arunava Chakravarty Arunava Chakravarty (= 1×) peers Francisco Fumero

Countries citing papers authored by Arunava Chakravarty

Since Specialization

Citations

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

Fields of papers citing papers by Arunava Chakravarty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arunava Chakravarty

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

All Works

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18 of 18 papers shown

Chakravarty, Arunava, Sophie Riedl, Julia Mai, et al.. (2024). Morph-SSL: Self-Supervision With Longitudinal Morphing for Forecasting AMD Progression From OCT Volumes. IEEE Transactions on Medical Imaging. 43(9). 3224–3239. 6 indexed citations

Chakravarty, Arunava, Dmitrii Lachinov, Sophie Riedl, et al.. (2024). 3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression From Longitudinal OCTs. IEEE Transactions on Medical Imaging. 43(9). 3200–3210. 4 indexed citations

Lachinov, Dmitrii, Arunava Chakravarty, Christoph Grechenig, Ursula Schmidt‐Erfurth, & Hrvoje Bogunović. (2023). Learning Spatio-Temporal Model of Disease Progression With NeuralODEs From Longitudinal Volumetric Data. IEEE Transactions on Medical Imaging. 43(3). 1165–1179. 12 indexed citations

Chakravarty, Arunava, Johan H. Mentink, Sergey Semin, & Th. Rasing. (2022). Training and pattern recognition by an opto-magnetic neural network. Applied Physics Letters. 120(2). 3 indexed citations

Chakravarty, Arunava, et al.. (2021). Federated Learning for Site Aware Chest Radiograph Screening. 1077–1081. 13 indexed citations

Chakravarty, Arunava, et al.. (2020). A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms. PubMed. 2020. 1128–1131. 7 indexed citations

Chakravarty, Arunava, Johan H. Mentink, C. S. Davies, et al.. (2019). Supervised learning of an opto-magnetic neural network with ultrashort laser pulses. Applied Physics Letters. 114(19). 16 indexed citations

Chakravarty, Arunava & Jayanthi Sivaswamy. (2018). A supervised joint multi-layer segmentation framework for retinal optical coherence tomography images using conditional random field. Computer Methods and Programs in Biomedicine. 165. 235–250. 15 indexed citations

Chakravarty, Arunava & Jayanthi Sivaswamy. (2018). RACE-Net: A Recurrent Neural Network for Biomedical Image Segmentation. IEEE Journal of Biomedical and Health Informatics. 23(3). 1151–1162. 64 indexed citations

10.

Chakravarty, Arunava & Jayanthi Sivaswamy. (2017). Joint optic disc and cup boundary extraction from monocular fundus images. Computer Methods and Programs in Biomedicine. 147. 51–61. 53 indexed citations

11.

Chakravarty, Arunava & Jayanthi Sivaswamy. (2016). Glaucoma classification with a fusion of segmentation and image-based features. 689–692. 37 indexed citations

12.

Sivaswamy, Jayanthi, et al.. (2015). A Comprehensive Retinal Image Dataset for the Assessment of Glaucoma from the Optic Nerve Head Analysis. 198 indexed citations

13.

Chakravarty, Arunava, et al.. (2015). An assistive annotation system for retinal images. 1506–1509. 6 indexed citations

14.

Joshi, Gopal Datt, et al.. (2015). Automated Detection of Glaucoma From Topographic Features of the Optic Nerve Head in Color Fundus Photographs. Journal of Glaucoma. 25(7). 590–597. 25 indexed citations

15.

Chakravarty, Arunava & Jayanthi Sivaswamy. (2014). Coupled Sparse Dictionary for Depth-Based Cup Segmentation from Single Color Fundus Image. Lecture notes in computer science. 17(Pt 1). 747–754. 16 indexed citations

16.

Grinsven, Mark J. J. P. van, Arunava Chakravarty, Jayanthi Sivaswamy, et al.. (2013). A Bag of Words approach for discriminating between retinal images containing exudates or drusen. 1444–1447. 18 indexed citations

17.

Chakravarty, Arunava, et al.. (2013). Visual saliency based bright lesion detection and discrimination in retinal images. 1436–1439. 20 indexed citations

18.

Chakravarty, Arunava & Jayanthi Sivaswamy. (2013). A novel approach for quantification of retinal vessel tortuosity using quadratic polynomial decomposition. 7–12. 18 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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