Sonia Sahu

435 total citations
16 papers, 318 citations indexed

About

Sonia Sahu is a scholar working on Radiology, Nuclear Medicine and Imaging, Hepatology and Oncology. According to data from OpenAlex, Sonia Sahu has authored 16 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Hepatology and 5 papers in Oncology. Recurrent topics in Sonia Sahu's work include Hepatocellular Carcinoma Treatment and Prognosis (9 papers), MRI in cancer diagnosis (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Sonia Sahu is often cited by papers focused on Hepatocellular Carcinoma Treatment and Prognosis (9 papers), MRI in cancer diagnosis (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Sonia Sahu collaborates with scholars based in United States, Austria and Switzerland. Sonia Sahu's co-authors include Rafael Durán, MingDe Lin, Jae Ho Sohn, Julius Chapiro, Yan Zhao, Florian Nima Fleckenstein, Rüdiger Schernthaner, Jean-François H. Geschwind, Francesco Alessandrino and Atul B. Shinagare and has published in prestigious journals such as Radiology, American Journal of Roentgenology and Clinical Gastroenterology and Hepatology.

In The Last Decade

Sonia Sahu

16 papers receiving 316 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sonia Sahu United States 13 149 133 101 82 74 16 318
Denise N. Gansen United States 7 138 0.9× 49 0.4× 67 0.7× 72 0.9× 66 0.9× 8 272
Baerbel Meteling Australia 7 291 2.0× 87 0.7× 146 1.4× 49 0.6× 147 2.0× 8 353
Satoshi Sasayama Japan 6 120 0.8× 149 1.1× 78 0.8× 40 0.5× 61 0.8× 16 342
Woo Jin Lee South Korea 6 292 2.0× 141 1.1× 114 1.1× 119 1.5× 116 1.6× 8 455
Joong-Won Park South Korea 6 190 1.3× 98 0.7× 65 0.6× 94 1.1× 60 0.8× 8 301
Ermanno Notarianni Italy 6 153 1.0× 63 0.5× 86 0.9× 32 0.4× 99 1.3× 16 250
Jennifer A. Shannon Australia 5 196 1.3× 53 0.4× 150 1.5× 43 0.5× 124 1.7× 10 317
Makoto Fujita Japan 9 260 1.7× 52 0.4× 74 0.7× 112 1.4× 75 1.0× 21 367
Vlasios S. Sotirchos United States 11 369 2.5× 133 1.0× 165 1.6× 57 0.7× 122 1.6× 44 455
Florian E. Buisman Netherlands 13 216 1.4× 71 0.5× 259 2.6× 30 0.4× 107 1.4× 22 377

Countries citing papers authored by Sonia Sahu

Since Specialization
Citations

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

Fields of papers citing papers by Sonia Sahu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sonia Sahu

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

All Works

16 of 16 papers shown
1.
2.
Chikarmane, Sona A., Laila Cochón, Ramin Khorasani, Sonia Sahu, & Catherine S. Giess. (2020). Screening Mammography Performance Metrics of 2D Digital Mammography Versus Digital Breast Tomosynthesis in Women With a Personal History of Breast Cancer. American Journal of Roentgenology. 217(3). 587–594. 17 indexed citations
3.
Magudia, Kirti, Olga Laur, Sonia Sahu, et al.. (2019). Women in Radiology: Obtaining Departmental Sponsorship and Building a Sustainable Organization Led by Residents. Journal of the American College of Radiology. 17(3). 441–443. 3 indexed citations
4.
Alessandrino, Francesco, Sonia Sahu, Mizuki Nishino, et al.. (2019). Frequency and imaging features of abdominal immune-related adverse events in metastatic lung cancer patients treated with PD-1 inhibitor. Abdominal Radiology. 44(5). 1917–1927. 33 indexed citations
5.
Alessandrino, Francesco, Lei Qin, Gisele Cruz, et al.. (2019). 5-Fluorouracil induced liver toxicity in patients with colorectal cancer: role of computed tomography texture analysis as a potential biomarker. Abdominal Radiology. 44(9). 3099–3106. 26 indexed citations
6.
Thomas, Richard, Lei Qin, Francesco Alessandrino, et al.. (2018). A review of the principles of texture analysis and its role in imaging of genitourinary neoplasms. Abdominal Radiology. 44(7). 2501–2510. 14 indexed citations
7.
Zhao, Yan, Rafael Durán, Wei Bai, et al.. (2017). Which Criteria Applied in Multi-Phasic CT Can Predict Early Tumor Response in Patients with Hepatocellular Carcinoma Treated Using Conventional TACE: RECIST, mRECIST, EASL or qEASL?. CardioVascular and Interventional Radiology. 41(3). 433–442. 24 indexed citations
8.
Schernthaner, Ruediger E., Reham R. Haroun, Rafael Durán, et al.. (2017). Characteristics of a New X-Ray Imaging System for Interventional Procedures: Improved Image Quality and Reduced Radiation Dose. CardioVascular and Interventional Radiology. 41(3). 502–508. 12 indexed citations
9.
10.
Fleckenstein, Florian Nima, Rüdiger Schernthaner, Rafael Durán, et al.. (2016). 3D Quantitative tumour burden analysis in patients with hepatocellular carcinoma before TACE: comparing single-lesion vs. multi-lesion imaging biomarkers as predictors of patient survival. European Radiology. 26(9). 3243–3252. 25 indexed citations
11.
Fleckenstein, Florian Nima, Rüdiger Schernthaner, Rafael Durán, et al.. (2016). Renal Cell Carcinoma Metastatic to the Liver: Early Response Assessment after Intraarterial Therapy Using 3D Quantitative Tumor Enhancement Analysis. Translational Oncology. 9(5). 377–383. 9 indexed citations
12.
Sohn, Jae Ho, Rafael Durán, Yan Zhao, et al.. (2016). Validation of the Hong Kong Liver Cancer Staging System in Determining Prognosis of the North American Patients Following Intra-arterial Therapy. Clinical Gastroenterology and Hepatology. 15(5). 746–755.e4. 27 indexed citations
13.
Zhao, Yan, Rafael Durán, Julius Chapiro, et al.. (2016). Transarterial Chemoembolization for the Treatment of Advanced-Stage Hepatocellular Carcinoma. Journal of Gastrointestinal Surgery. 20(12). 2002–2009. 27 indexed citations
14.
Schernthaner, Ruediger E., Reham R. Haroun, Rafael Durán, et al.. (2016). Improved Visibility of Metastatic Disease in the Liver During Intra-Arterial Therapy Using Delayed Arterial Phase Cone-Beam CT. CardioVascular and Interventional Radiology. 39(10). 1429–1437. 16 indexed citations
15.
Durán, Rafael, Jae Ho Sohn, Rüdiger Schernthaner, et al.. (2015). Radiologic-pathologic analysis of quantitative 3D tumour enhancement on contrast-enhanced MR imaging: a study of ROI placement. European Radiology. 26(1). 103–113. 28 indexed citations
16.
Schernthaner, Rüdiger, Julius Chapiro, Sonia Sahu, et al.. (2015). Feasibility of a Modified Cone-Beam CT Rotation Trajectory to Improve Liver Periphery Visualization during Transarterial Chemoembolization. Radiology. 277(3). 833–841. 13 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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