Arash Pourtaherian

528 total citations
25 papers, 345 citations indexed

About

Arash Pourtaherian is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition and Pharmacy. According to data from OpenAlex, Arash Pourtaherian has authored 25 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Biomedical Engineering, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Pharmacy. Recurrent topics in Arash Pourtaherian's work include Photoacoustic and Ultrasonic Imaging (7 papers), Soft Robotics and Applications (7 papers) and Infant Health and Development (5 papers). Arash Pourtaherian is often cited by papers focused on Photoacoustic and Ultrasonic Imaging (7 papers), Soft Robotics and Applications (7 papers) and Infant Health and Development (5 papers). Arash Pourtaherian collaborates with scholars based in Netherlands, United States and India. Arash Pourtaherian's co-authors include Peter H. N. de With, H.H.M. Korsten, Nenad Mihajlović, Svitlana Zinger, Harm J. Scholten, R. Arthur Bouwman, Farhad Ghazvinian Zanjani, Afshin Izadian, W. E. Tjon a Ten and Caifeng Shan and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Neurocomputing and Anaesthesia.

In The Last Decade

Arash Pourtaherian

23 papers receiving 322 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arash Pourtaherian Netherlands 11 123 106 69 57 48 25 345
Krishna Subramanyan United States 9 143 1.2× 182 1.7× 50 0.7× 201 3.5× 25 0.5× 44 564
Jérôme Schmid Switzerland 11 163 1.3× 108 1.0× 212 3.1× 59 1.0× 11 0.2× 30 419
Marco Esposito Germany 10 190 1.5× 73 0.7× 128 1.9× 57 1.0× 7 0.1× 14 318
Justus Schock Germany 10 87 0.7× 84 0.8× 106 1.5× 98 1.7× 6 0.1× 28 378
Hamed Saeidi United States 13 231 1.9× 68 0.6× 209 3.0× 46 0.8× 14 0.3× 33 541
Dennis Kundrat Germany 12 262 2.1× 81 0.8× 162 2.3× 63 1.1× 13 0.3× 27 433
Emran Mohammad Abu Anas Canada 11 254 2.1× 72 0.7× 47 0.7× 202 3.5× 8 0.2× 27 412
Sun Zheng China 9 165 1.3× 56 0.5× 41 0.6× 110 1.9× 45 0.9× 47 306
Sophia Bano United Kingdom 12 108 0.9× 157 1.5× 86 1.2× 49 0.9× 12 0.3× 44 412
Siyi Ding China 11 118 1.0× 140 1.3× 51 0.7× 55 1.0× 13 0.3× 26 343

Countries citing papers authored by Arash Pourtaherian

Since Specialization
Citations

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

Fields of papers citing papers by Arash Pourtaherian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arash Pourtaherian

This figure shows the co-authorship network connecting the top 25 collaborators of Arash Pourtaherian. A scholar is included among the top collaborators of Arash Pourtaherian 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 Arash Pourtaherian. Arash Pourtaherian 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.
Bondarev, Egor, et al.. (2025). MEET: Towards Memory-Efficient Temporal Sparse Deep Neural Networks. TU/e Research Portal. 29309–29320. 1 indexed citations
2.
Pourtaherian, Arash, et al.. (2023). STAR: Sparse Thresholded Activation under partial-Regularization for Activation Sparsity Exploration. TU/e Research Portal. 4554–4563. 3 indexed citations
3.
Zanjani, Farhad Ghazvinian, et al.. (2021). Mask-MCNet: Tooth instance segmentation in 3D point clouds of intra-oral scans. Neurocomputing. 453. 286–298. 43 indexed citations
4.
Pourtaherian, Arash, et al.. (2020). Infant Facial Expression Analysis: Towards a Real-Time Video Monitoring System Using R-CNN and HMM. IEEE Journal of Biomedical and Health Informatics. 25(5). 1429–1440. 22 indexed citations
5.
Pourtaherian, Arash, et al.. (2020). Infant Monitoring System for Real-Time and Remote Discomfort Detection. IEEE Transactions on Consumer Electronics. 66(4). 336–345. 10 indexed citations
6.
Khoei, Mina A., Amirreza Yousefzadeh, Arash Pourtaherian, Orlando Moreira, & Jonathan Tapson. (2020). SpArNet: Sparse Asynchronous Neural Network execution for energy efficient inference. TU/e Research Portal. 256–260. 14 indexed citations
7.
Pourtaherian, Arash, et al.. (2020). Infant Monitoring System for Real-Time and Remote Discomfort Detection. TU/e Research Portal. 1–2. 5 indexed citations
8.
Sun, Yue, Caifeng Shan, Tao Tan, et al.. (2019). Detecting discomfort in infants through facial expressions. Physiological Measurement. 40(11). 115006–115006. 12 indexed citations
9.
Shan, Caifeng, et al.. (2019). Catheter segmentation in three-dimensional ultrasound images by feature fusion and model fitting. Journal of Medical Imaging. 6(1). 1–1. 9 indexed citations
10.
Pourtaherian, Arash, Farhad Ghazvinian Zanjani, Svitlana Zinger, et al.. (2018). Robust and semantic needle detection in 3D ultrasound using orthogonal-plane convolutional neural networks. International Journal of Computer Assisted Radiology and Surgery. 13(9). 1321–1333. 37 indexed citations
11.
Pourtaherian, Arash, et al.. (2018). Feature study on catheter detection in three-dimensional ultrasound. TU/e Research Portal. 3. 22–22. 9 indexed citations
12.
Pourtaherian, Arash. (2018). Robust needle detection and visualization for 3D ultrasound image-guided interventions. TU/e Research Portal (Eindhoven University of Technology). 1 indexed citations
13.
Sun, Yue, Caifeng Shan, Tao Tan, et al.. (2018). Video-based discomfort detection for infants. Machine Vision and Applications. 30(5). 933–944. 15 indexed citations
14.
Scholten, Harm J., Arash Pourtaherian, Nenad Mihajlović, H.H.M. Korsten, & R. Arthur Bouwman. (2017). Improving needle tip identification during ultrasound‐guided procedures in anaesthetic practice. Anaesthesia. 72(7). 889–904. 66 indexed citations
15.
Pourtaherian, Arash, et al.. (2016). Automated in-plane visualization of steep needles from 3D ultrasound data volumes. TU/e Research Portal. 1–4. 4 indexed citations
16.
Pourtaherian, Arash, Svitlana Zinger, Nenad Mihajlović, et al.. (2015). Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9875. 987513–987513. 4 indexed citations
17.
Pourtaherian, Arash, et al.. (2015). Fast planar segmentation of depth images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9399. 93990I–93990I. 5 indexed citations
18.
Pourtaherian, Arash, Svitlana Zinger, Peter H. N. de With, H.H.M. Korsten, & Nenad Mihajlović. (2014). Gabor-based needle detection and tracking in three-dimensional ultrasound data volumes. TU/e Research Portal. 3602–3606. 18 indexed citations
19.
Pourtaherian, Arash, Rob G. J. Wijnhoven, & Peter H. N. de With. (2013). TROD: Tracking with occlusion handling and drift correction. 2440–2444. 1 indexed citations
20.
Izadian, Afshin, et al.. (2012). Basic model and governing equation of solar cells used in power and control applications. TU/e Research Portal. 1483–1488. 25 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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