Aria Pezeshk

1.4k total citations · 1 hit paper
33 papers, 991 citations indexed

About

Aria Pezeshk is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Aria Pezeshk has authored 33 papers receiving a total of 991 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 16 papers in Artificial Intelligence and 14 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Aria Pezeshk's work include Radiomics and Machine Learning in Medical Imaging (16 papers), Lung Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (10 papers). Aria Pezeshk is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (16 papers), Lung Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (10 papers). Aria Pezeshk collaborates with scholars based in United States, Thailand and Germany. Aria Pezeshk's co-authors include Berkman Sahiner, Nicholas Petrick, H. Kenny, Lubomir M. Hadjiiski, Ronald M. Summers, Karen Drukker, Maryellen L. Giger, Xiaosong Wang, Richard L. Tutwiler and Wei-Jie Chen and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Aria Pezeshk

33 papers receiving 960 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning in medical imaging and radiation therapy

2018 527 citations Berkman Sahiner, Aria Pezeshk et al. Medical Physics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aria Pezeshk United States	12	654	296	264	201	192	33	991
Junjie Hu China	17	678 1.0×	224 0.8×	109 0.4×	267 1.3×	153 0.8×	60	1.1k
Wei Shao United States	18	339 0.5×	193 0.7×	298 1.1×	145 0.7×	156 0.8×	77	1.1k
Fa Wu China	9	692 1.1×	471 1.6×	78 0.3×	333 1.7×	209 1.1×	19	1.1k
Phillip Chlap Australia	10	359 0.5×	198 0.7×	112 0.4×	182 0.9×	117 0.6×	30	792
Xiaokun Liang China	18	910 1.4×	181 0.6×	237 0.9×	268 1.3×	506 2.6×	71	1.3k
Takayuki Ishida Japan	22	1.0k 1.6×	351 1.2×	704 2.7×	289 1.4×	258 1.3×	105	1.6k
Ester Bonmati United Kingdom	11	564 0.9×	204 0.7×	139 0.5×	480 2.4×	286 1.5×	25	985
Jue Jiang United States	18	658 1.0×	343 1.2×	275 1.0×	349 1.7×	156 0.8×	59	1.3k
Tom Doel United Kingdom	10	668 1.0×	504 1.7×	220 0.8×	681 3.4×	223 1.2×	16	1.7k
Avishek Chatterjee Netherlands	17	815 1.2×	340 1.1×	283 1.1×	77 0.4×	247 1.3×	38	1.2k

Countries citing papers authored by Aria Pezeshk

Since Specialization

Citations

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

Fields of papers citing papers by Aria Pezeshk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aria Pezeshk

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Arbabian, Amin, et al.. (2024). Productivity Enhancement in Semiconductor Manufacturing with Ai-Enabled Operations Digital Twin Platform. 280–283. 2 indexed citations

Bukowski, Julia V., et al.. (2023). Mapping DNN Embedding Manifolds for Network Generalization Prediction. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 31. 6513–6522. 1 indexed citations

Fermüller, Cornelia, Yiannis Aloimonos, Gary M. Levine, et al.. (2023). Semi‐supervised training using cooperative labeling of weakly annotated data for nodule detection in chest CT. Medical Physics. 50(7). 4255–4268. 2 indexed citations

Pezeshk, Aria, et al.. (2021). Test Data Reuse for the Evaluation of Continuously Evolving Classification Algorithms Using the Area under the Receiver Operating Characteristic Curve. SIAM Journal on Mathematics of Data Science. 3(2). 692–714. 3 indexed citations

Petrick, Nicholas, et al.. (2020). Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans. Medical Physics. 47(5). 2150–2160. 16 indexed citations

Kenny, H., Nicholas Petrick, Aria Pezeshk, et al.. (2019). Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images. 6 indexed citations

Kalpathy–Cramer, Jayashree, Nancy A. Obuchowski, Andrew J. Buckler, et al.. (2018). Evaluation of Simulated Lesions as Surrogates to Clinical Lesions for Thoracic CT Volumetry: The Results of an International Challenge. Academic Radiology. 26(7). e161–e173. 3 indexed citations

Pezeshk, Aria, et al.. (2018). Computational insertion of microcalcification clusters on mammograms: reader differentiation from native clusters and computer-aided detection comparison. Journal of Medical Imaging. 5(4). 1–1. 2 indexed citations

Sahiner, Berkman, Aria Pezeshk, Lubomir M. Hadjiiski, et al.. (2018). Deep learning in medical imaging and radiation therapy. Medical Physics. 46(1). e1–e36. 527 indexed citations breakdown →

10.

Solomon, Justin, Pooyan Sahbaee, Martin Sedlmair, et al.. (2017). Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT. Physics in Medicine and Biology. 62(18). 7280–7299. 9 indexed citations

11.

Sahiner, Berkman, Weijie Chen, Aria Pezeshk, & Nicholas Petrick. (2017). Comparison of two classifiers when the data sets are imbalanced: the power of the area under the precision-recall curve as the figure of merit versus the area under the ROC curve. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10136. 101360G–101360G. 11 indexed citations

12.

Chen, Wei-Jie, Berkman Sahiner, F. W. Samuelson, Aria Pezeshk, & Nicholas Petrick. (2016). Calibration of medical diagnostic classifier scores to the probability of disease. Statistical Methods in Medical Research. 27(5). 1394–1409. 14 indexed citations

13.

Pezeshk, Aria, Nicholas Petrick, & Berkman Sahiner. (2016). Seamless lesion insertion in digital mammography: methodology and reader study. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9785. 97850J–97850J. 5 indexed citations

14.

Pezeshk, Aria, Nicholas Petrick, Wei-Jie Chen, & Berkman Sahiner. (2016). Seamless Lesion Insertion for Data Augmentation in CAD Training. IEEE Transactions on Medical Imaging. 36(4). 1005–1015. 33 indexed citations

15.

Pezeshk, Aria, et al.. (2015). Seamless Insertion of Pulmonary Nodules in Chest CT Images. IEEE Transactions on Biomedical Engineering. 62(12). 2812–2827. 18 indexed citations

16.

Pezeshk, Aria, Lucreţiu M. Popescu, & Berkman Sahiner. (2015). CT image quality evaluation for detection of signals with unknown location, size, contrast and shape using unsupervised methods. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9416. 94160J–94160J. 2 indexed citations

17.

Pezeshk, Aria, Berkman Sahiner, Weijie Chen, & Nicholas Petrick. (2015). Improving CAD performance by seamless insertion of pulmonary nodules in chest CT exams. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9414. 94140A–94140A. 3 indexed citations

18.

Pezeshk, Aria & Richard L. Tutwiler. (2011). Automatic Feature Extraction and Text Recognition From Scanned Topographic Maps. IEEE Transactions on Geoscience and Remote Sensing. 49(12). 5047–5063. 53 indexed citations

19.

Pezeshk, Aria & Richard L. Tutwiler. (2010). Improved Multi Angled Parallelism for separation of text from intersecting linear features in scanned topographic maps. 1078–1081. 13 indexed citations

20.

Pezeshk, Aria & Richard L. Tutwiler. (2010). Extended character defect model for recognition of text from maps. 1. 85–88. 12 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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