Anurima Patra

436 total citations
24 papers, 237 citations indexed

About

Anurima Patra is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Anurima Patra has authored 24 papers receiving a total of 237 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Oncology and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Anurima Patra's work include Radiomics and Machine Learning in Medical Imaging (11 papers), Pancreatic and Hepatic Oncology Research (8 papers) and AI in cancer detection (4 papers). Anurima Patra is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (11 papers), Pancreatic and Hepatic Oncology Research (8 papers) and AI in cancer detection (4 papers). Anurima Patra collaborates with scholars based in India and United States. Anurima Patra's co-authors include Garima Suman, Ajit H. Goenka, Suresh T. Chari, Panagiotis Korfiatis, Shounak Majumder, Joel G. Fletcher, Darryl Wright, Timothy L. Kline, Ananya Panda and Matthew P. Johnson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and Clinical Cancer Research.

In The Last Decade

Anurima Patra

21 papers receiving 233 citations

Peers

Anurima Patra
Xiaofeng Jiang China
Christina Glasner Germany
Vidya Sankar Viswanathan United States
Bernadette Redd United States
Garima Suman United States
Kyunghyun Paeng South Korea
Annalisa Nardone Italy
Touseef Ahmad Qureshi United States
Qiyu Zhao China
Birgid Schömig‐Markiefka Germany
Xiaofeng Jiang China
Anurima Patra
Citations per year, relative to Anurima Patra Anurima Patra (= 1×) peers Xiaofeng Jiang

Countries citing papers authored by Anurima Patra

Since Specialization
Citations

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

Fields of papers citing papers by Anurima Patra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anurima Patra

This figure shows the co-authorship network connecting the top 25 collaborators of Anurima Patra. A scholar is included among the top collaborators of Anurima Patra 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 Anurima Patra. Anurima Patra 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.
Kumar, Chitranjan, et al.. (2025). CT-Guided Percutaneous Lung Biopsy: Important Steps with “Tips and Tricks” for Optimal Yield. Indian journal of radiology and imaging - new series/Indian journal of radiology and imaging/Indian Journal of Radiology & Imaging. 35(4). 516–528.
2.
Dey, Aparajit Ballav, et al.. (2025). The Role of Diagnostic Nasal Endoscopy and Computed Tomography Scan in Chronic Rhinosinusitis in Adults: A Study of Clinical Correlation. Indian Journal of Otolaryngology and Head & Neck Surgery. 77(3). 1552–1557.
3.
Patra, Anurima, Anu Eapen, Ashish Singh, et al.. (2023). Predicting Positive Radial Margin on Restaging MRI of Patients with Low Rectal Cancer: Can We Do Better?. SHILAP Revista de lepidopterología. 34(1). 85–94. 1 indexed citations
4.
Chatterjee, Argha, Akshay Baheti, Bharat Gupta, et al.. (2023). Imaging Recommendations for Diagnosis, Staging, and Management of Hepatic and Biliary Tract Cancer. Indian Journal of Medical and Paediatric Oncology. 44(2). 241–250.
5.
Sen, Saugata, et al.. (2023). Pathological Basis of Imaging in Hepatocellular Carcinoma. SHILAP Revista de lepidopterología. 6(3). 160–172. 1 indexed citations
6.
Janu, Amit, Anurima Patra, Ashish Gulia, et al.. (2023). Imaging Recommendations for Diagnosis, Staging, and Management of Bone Tumors. Indian Journal of Medical and Paediatric Oncology. 44(2). 257–260. 2 indexed citations
7.
8.
Korfiatis, Panagiotis, Anurima Patra, Garima Suman, et al.. (2023). Bounding box-based 3D AI model for user-guided volumetric segmentation of pancreatic ductal adenocarcinoma on standard-of-care CTs. Pancreatology. 23(5). 522–529. 13 indexed citations
9.
Chandramohan, Anuradha, et al.. (2022). MDT stage migration in MRI of significant rectal polyps and early rectal cancers. Abdominal Radiology. 47(8). 2760–2769. 1 indexed citations
10.
Patra, Anurima, Panagiotis Korfiatis, Garima Suman, et al.. (2022). Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis. Gastroenterology. 163(5). 1435–1446.e3. 104 indexed citations
11.
Wright, Darryl, Anurima Patra, Panagiotis Korfiatis, et al.. (2022). Radiomics-based machine learning (ML) classifier for detection of type 2 diabetes on standard-of-care abdomen CTs: a proof-of-concept study. Abdominal Radiology. 47(11). 3806–3816. 7 indexed citations
12.
Patra, Anurima, Garima Suman, Shounak Majumder, et al.. (2022). Volumetric Pancreas Segmentation on Computed Tomography: Accuracy and Efficiency of a Convolutional Neural Network Versus Manual Segmentation in 3D Slicer in the Context of Interreader Variability of Expert Radiologists. Journal of Computer Assisted Tomography. 46(6). 841–847. 14 indexed citations
13.
Suman, Garima, Anurima Patra, Panagiotis Korfiatis, et al.. (2021). Quality gaps in public pancreas imaging datasets: Implications & challenges for AI applications. Pancreatology. 21(5). 1001–1008. 27 indexed citations
14.
Patra, Anurima, et al.. (2021). Publication Parameters for Medical Faculty Promotions: A Survey on the Medical Council of India Amendment 2019 with Review of Literature. SHILAP Revista de lepidopterología. 57. 45–52. 3 indexed citations
15.
Kumar, Vikas, Manoj Kumar Sharma, Balasubramaniam Venkatraman, et al.. (2021). Learning to Generate Missing Pulse Sequence in MRI using Deep Convolution Neural Network Trained with Visual Turing Test. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. 3419–3422. 2 indexed citations
16.
Patra, Anurima, et al.. (2021). Diffuse Infiltrative Non-mass-like Brain Parenchymal Lesions on MRI: Differentiating Lymphomatosis Cerebri from its Mimics. Journal of Clinical Imaging Science. 11. 41–41. 3 indexed citations
17.
Patra, Anurima, Akshay Baheti, Suman Kumar Ankathi, et al.. (2020). Can Post-Treatment MRI Features Predict Pathological Circumferential Resection Margin (pCRM) Involvement in Low Rectal Tumors. Indian Journal of Surgical Oncology. 11(4). 720–725. 4 indexed citations
18.
Patra, Anurima, et al.. (2019). MR Imaging in Neurocritical Care. Indian Journal of Critical Care Medicine. 23(S2). 104–114. 5 indexed citations
19.
Patra, Anurima, et al.. (2019). Crizotinib-Associated Renal Cysts: A Case Series. SHILAP Revista de lepidopterología. 2(2). 130–134. 1 indexed citations
20.
Baheti, Akshay, et al.. (2019). Tumor Response Criteria in Oncoimaging: RECIST Criteria and beyond—Part 1. SHILAP Revista de lepidopterología. 2(2). 98–106. 2 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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