Sunitha B. Thakur

4.2k total citations
85 papers, 2.8k citations indexed

About

Sunitha B. Thakur is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Cancer Research. According to data from OpenAlex, Sunitha B. Thakur has authored 85 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Radiology, Nuclear Medicine and Imaging, 13 papers in Genetics and 12 papers in Cancer Research. Recurrent topics in Sunitha B. Thakur's work include MRI in cancer diagnosis (56 papers), Radiomics and Machine Learning in Medical Imaging (37 papers) and Advanced MRI Techniques and Applications (33 papers). Sunitha B. Thakur is often cited by papers focused on MRI in cancer diagnosis (56 papers), Radiomics and Machine Learning in Medical Imaging (37 papers) and Advanced MRI Techniques and Applications (33 papers). Sunitha B. Thakur collaborates with scholars based in United States, Austria and Italy. Sunitha B. Thakur's co-authors include Elizabeth A. Morris, Katja Pinker, Wei Huang, Maxine S. Jochelson, Doris Leithner, Elizabeth J. Sutton, Jason A. Koutcher, Thomas H. Helbich, D. David Dershaw and Joseph O. Deasy and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Radiology.

In The Last Decade

Sunitha B. Thakur

80 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sunitha B. Thakur United States	29	2.0k	448	394	329	288	85	2.8k
Kyrre E. Emblem Norway	29	1.4k 0.7×	304 0.7×	113 0.3×	400 1.2×	234 0.8×	92	3.1k
Hongyoon Choi South Korea	28	876 0.4×	324 0.7×	194 0.5×	798 2.4×	299 1.0×	139	2.4k
Pascal O. Zinn United States	29	1.1k 0.5×	568 1.3×	116 0.3×	679 2.1×	261 0.9×	111	2.6k
M.E.P. Philippens Netherlands	35	2.4k 1.2×	320 0.7×	62 0.2×	230 0.7×	453 1.6×	149	3.5k
Phedias Diamandis Canada	22	320 0.2×	222 0.5×	362 0.9×	571 1.7×	210 0.7×	60	1.6k
MacLean P. Nasrallah United States	23	543 0.3×	242 0.5×	87 0.2×	319 1.0×	240 0.8×	97	1.5k
Yinyan Wang China	33	1.2k 0.6×	616 1.4×	93 0.2×	662 2.0×	380 1.3×	145	3.3k
Anne Laprie France	20	666 0.3×	153 0.3×	94 0.2×	189 0.6×	174 0.6×	97	1.6k
Floris H. P. van Velden Netherlands	26	1.8k 0.9×	122 0.3×	92 0.2×	103 0.3×	243 0.8×	95	2.4k
Paul E. Sijens Netherlands	31	1.7k 0.8×	115 0.3×	49 0.1×	387 1.2×	89 0.3×	123	2.7k

Countries citing papers authored by Sunitha B. Thakur

Since Specialization

Citations

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

Fields of papers citing papers by Sunitha B. Thakur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunitha B. Thakur. 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 Sunitha B. Thakur. The network helps show where Sunitha B. Thakur may publish in the future.

Co-authorship network of co-authors of Sunitha B. Thakur

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

All Works

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20 of 20 papers shown

Gullo, Roberto Lo, Lynn Han, Sarah Eskreis‐Winkler, et al.. (2024). AI Applications to Breast MRI: Today and Tomorrow. Journal of Magnetic Resonance Imaging. 60(6). 2290–2308. 6 indexed citations

Naranjo, Isaac Daimiel, Arka Bhowmik, Roberto Lo Gullo, et al.. (2024). Assessment of Hypoxia in Breast Cancer: Emerging Functional MR Imaging and Spectroscopy Techniques and Clinical Applications. Journal of Magnetic Resonance Imaging. 61(1). 83–96. 1 indexed citations

Bitencourt, Almir Galvão Vieira, Arka Bhowmik, Roberto Lo Gullo, et al.. (2023). Deuterium MR spectroscopy: potential applications in oncology research. BJR|Open. 6(1). 2 indexed citations

Mikheev, Artem, Varadan Sevilimedu, Linda Moy, et al.. (2023). Multisite MRI Intravoxel Incoherent Motion Repeatability and Reproducibility across 3 T Scanners in a Breast Diffusion Phantom: A BReast Intravoxel Incoherent Motion Multisite (BRIMM) Study. Journal of Magnetic Resonance Imaging. 59(6). 2226–2237. 8 indexed citations

Naranjo, Isaac Daimiel, Peter Gibbs, Roberto Lo Gullo, et al.. (2022). Breast Lesion Classification with Multiparametric Breast MRI Using Radiomics and Machine Learning: A Comparison with Radiologists’ Performance. Cancers. 14(7). 1743–1743. 23 indexed citations

Marino, Maria Adele, Daly Avendaño, Varadan Sevilimedu, et al.. (2022). Limited value of multiparametric MRI with dynamic contrast-enhanced and diffusion-weighted imaging in non-mass enhancing breast tumors. European Journal of Radiology. 156. 110523–110523. 9 indexed citations

Naranjo, Isaac Daimiel, Peter Gibbs, Roberto Lo Gullo, et al.. (2021). Radiomics and Machine Learning with Multiparametric Breast MRI for Improved Diagnostic Accuracy in Breast Cancer Diagnosis. Diagnostics. 11(6). 919–919. 41 indexed citations

Ochoa‐Albiztegui, R. Elena, Varadan Sevilimedu, João V. Horvat, et al.. (2020). Pharmacokinetic Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging at 7T for Breast Cancer Diagnosis and Characterization. Cancers. 12(12). 3763–3763. 3 indexed citations

Horvat, João V., Aditi Iyer, Elizabeth A. Morris, et al.. (2019). Histogram Analysis and Visual Heterogeneity of Diffusion-Weighted Imaging with Apparent Diffusion Coefficient Mapping in the Prediction of Molecular Subtypes of Invasive Breast Cancers. Contrast Media & Molecular Imaging. 2019. 1–9. 16 indexed citations

10.

Leithner, Doris, Blanca Bernard‐Davila, Danny F. Martinez, et al.. (2019). Radiomic Signatures Derived from Diffusion-Weighted Imaging for the Assessment of Breast Cancer Receptor Status and Molecular Subtypes. Molecular Imaging and Biology. 22(2). 453–461. 59 indexed citations

11.

Horvat, João V., Manuela Durando, Sujata Patil, et al.. (2018). Apparent diffusion coefficient mapping using diffusion-weighted MRI: impact of background parenchymal enhancement, amount of fibroglandular tissue and menopausal status on breast cancer diagnosis. European Radiology. 28(6). 2516–2524. 24 indexed citations

12.

Plaza, Michael J., Elizabeth A. Morris, & Sunitha B. Thakur. (2015). Diffusion tensor imaging in the normal breast: influences of fibroglandular tissue composition and background parenchymal enhancement. Clinical Imaging. 40(3). 506–511. 14 indexed citations

13.

Iacconi, Chiara, et al.. (2014). Impact of fibroglandular tissue and background parenchymal enhancement on diffusion weighted imaging of breast lesions. European Journal of Radiology. 83(12). 2137–2143. 17 indexed citations

14.

Rizwan, Asif, Inna Serganova, Raya Khanin, et al.. (2013). Relationships between LDH-A, Lactate, and Metastases in 4T1 Breast Tumors. Clinical Cancer Research. 19(18). 5158–5169. 88 indexed citations

15.

Serganova, Inna, Asif Rizwan, Xiaohui Ni, et al.. (2011). Metabolic Imaging: A Link between Lactate Dehydrogenase A, Lactate, and Tumor Phenotype. Clinical Cancer Research. 17(19). 6250–6261. 90 indexed citations

16.

Ballangrud, Åse, Stella Lymberis, Sunitha B. Thakur, et al.. (2011). Magnetic resonance spectroscopy imaging in radiotherapy planning for recurrent gliomaa). Medical Physics. 38(5). 2724–2730. 4 indexed citations

17.

Su, Yuzhuo, et al.. (2008). Spectrum separation resolves partial‐volume effect of MRSI as demonstrated on brain tumor scans. NMR in Biomedicine. 21(10). 1030–1042. 16 indexed citations

18.

Bartella, Lia, Elizabeth A. Morris, D. David Dershaw, et al.. (2006). Proton MR Spectroscopy with Choline Peak as Malignancy Marker Improves Positive Predictive Value for Breast Cancer Diagnosis: Preliminary Study. Radiology. 239(3). 686–692. 184 indexed citations

19.

Narayana, A., Jenghwa Chang, Sunitha B. Thakur, et al.. (2004). Use of MR spectroscopy and functional imaging in the treatment planning of gliomas. International Journal of Radiation Oncology*Biology*Physics. 60(1). S222–S223. 3 indexed citations

20.

Narayana, A., Jason C. Chang, Sunitha B. Thakur, et al.. (2004). Use of MR spectroscopy and functional imaging in the treatment planning of gliomas. International Journal of Radiation Oncology*Biology*Physics. 60. S222–S223.

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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