Ajay Patel

420 total citations
13 papers, 270 citations indexed

About

Ajay Patel is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Epidemiology. According to data from OpenAlex, Ajay Patel has authored 13 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Epidemiology. Recurrent topics in Ajay Patel's work include Acute Ischemic Stroke Management (5 papers), Medical Imaging Techniques and Applications (4 papers) and Medical Image Segmentation Techniques (4 papers). Ajay Patel is often cited by papers focused on Acute Ischemic Stroke Management (5 papers), Medical Imaging Techniques and Applications (4 papers) and Medical Image Segmentation Techniques (4 papers). Ajay Patel collaborates with scholars based in Netherlands, United States and Germany. Ajay Patel's co-authors include Bram van Ginneken, Rashindra Manniesing, Mathias Prokop, Frederick J. A. Meijer, Ewoud J. van Dijk, Marieke M.B. Seyger, E.M.G.J. de Jong, Mark ter Laan, Manoj Mannil and Dylan Henssen and has published in prestigious journals such as Scientific Reports, Magnetic Resonance in Medicine and IEEE Access.

In The Last Decade

Ajay Patel

12 papers receiving 262 citations

Peers

Ajay Patel

RNMI

NEURO

EPIDE

NEURO

CVPR

Ela M. Akay Germany

Yuefu Zhan China

Ajay Hegde India

Hugo Duarte Portugal

Martha Foltyn Germany

Reuben Dorent United Kingdom

David Robben Belgium

Manudeep Kalra United States

Mohamed Elsharkawy United States

Daniel Ferraz Brazil

Ela M. Akay Germany

Ajay Patel

96 ×0.9

RNMI

32 ×0.4

NEURO

73 ×0.9

EPIDE

47 ×0.7

NEURO

117 ×2.3

CVPR

Citations per year, relative to Ajay Patel Ajay Patel (= 1×) peers Ela M. Akay

Countries citing papers authored by Ajay Patel

Since Specialization

Citations

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

Fields of papers citing papers by Ajay Patel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ajay Patel

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

All Works

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13 of 13 papers shown

1.

Patel, Ajay, et al.. (2024). TinyStyler: Efficient Few-Shot Text Style Transfer with Authorship Embeddings. 13376–13390.

2.

Mannil, Manoj, et al.. (2021). Performance of machine learning algorithms for glioma segmentation of brain MRI: a systematic literature review and meta-analysis. European Radiology. 31(12). 9638–9653. 49 indexed citations

3.

Patel, Ajay, et al.. (2021). Image‐based automated Psoriasis Area Severity Index scoring by Convolutional Neural Networks. Journal of the European Academy of Dermatology and Venereology. 36(1). 68–75. 40 indexed citations

4.

Pegge, Sjoert, et al.. (2020). Cerebral Artery and Vein Segmentation in Four-dimensional CT Angiography Using Convolutional Neural Networks. Radiology Artificial Intelligence. 2(4). e190178–e190178. 12 indexed citations

5.

Patel, Ajay, Floris H.B.M. Schreuder, Catharina J.M. Klijn, et al.. (2019). Intracerebral Haemorrhage Segmentation in Non-Contrast CT. Scientific Reports. 9(1). 17858–17858. 41 indexed citations

6.

Patel, Ajay, et al.. (2019). Image Level Training and Prediction: Intracranial Hemorrhage Identification in 3D Non-Contrast CT. IEEE Access. 7. 92355–92364. 46 indexed citations

7.

Patel, Ajay, et al.. (2019). Multiclass Brain Tissue Segmentation in 4D CT Using Convolutional Neural Networks. IEEE Access. 7. 51557–51569. 11 indexed citations

8.

Patel, Ajay & Rashindra Manniesing. (2018). A convolutional neural network for intracranial hemorrhage detection in non-contrast CT. 14. 46–46. 4 indexed citations

9.

Patel, Ajay, Mathias Prokop, Ewoud J. van Dijk, et al.. (2017). Robust Segmentation of the Full Cerebral Vasculature in 4D CT of Suspected Stroke Patients. Scientific Reports. 7(1). 15622–15622. 35 indexed citations

10.

Patel, Ajay, et al.. (2017). Automatic cerebrospinal fluid segmentation in non-contrast CT images using a 3D convolutional network. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10134. 1013420–1013420. 5 indexed citations

11.

Patel, Ajay, Bram van Ginneken, Frederick J. A. Meijer, et al.. (2016). Robust cranial cavity segmentation in CT and CT perfusion images of trauma and suspected stroke patients. Medical Image Analysis. 36. 216–228. 22 indexed citations

12.

Patel, Ajay, et al.. (2008). A novel technique for CT imaging the brain of the obese patient. Clinical Radiology. 63(5). 575–576. 2 indexed citations

13.

Yang, Yuxin, Gary H. Glover, Peter van Gelderen, et al.. (1998). A comparison of fast MR scan techniques for cerebral activation studies at 1.5 Tesla (Magnetic Resonance in Medicine (1998) 39 (61-67)). Magnetic Resonance in Medicine. 39(3). 3 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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