Amine Amyar

881 total citations · 1 hit paper
22 papers, 592 citations indexed

About

Amine Amyar is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Amine Amyar has authored 22 papers receiving a total of 592 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Biomedical Engineering and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Amine Amyar's work include Cardiac Imaging and Diagnostics (14 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Medical Imaging Techniques and Applications (10 papers). Amine Amyar is often cited by papers focused on Cardiac Imaging and Diagnostics (14 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Medical Imaging Techniques and Applications (10 papers). Amine Amyar collaborates with scholars based in United States, France and United Kingdom. Amine Amyar's co-authors include Su Ruan, Romain Modzelewski, Hua Li, Pierre Decazes, Arman Rahmim, Fereshteh Yousefirizi, Babak Saboury, Reza Nezafat, Isabelle Gardin and Patrick Pierce and has published in prestigious journals such as Circulation, Radiology and Magnetic Resonance in Medicine.

In The Last Decade

Amine Amyar

19 papers receiving 576 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.

Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation

2020 411 citations Amine Amyar, Romain Modzelewski et al. Computers in Biology and Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Amine Amyar United States	9	508	259	80	73	73	22	592
Jiayu Huo China	9	352 0.7×	189 0.7×	61 0.8×	71 1.0×	91 1.2×	18	495
John A. Onofrey United States	15	610 1.2×	104 0.4×	133 1.7×	70 1.0×	94 1.3×	69	880
Niels Olson United States	6	370 0.7×	467 1.8×	99 1.2×	132 1.8×	137 1.9×	9	734
Xinyuan Zhang China	10	309 0.6×	89 0.3×	107 1.3×	44 0.6×	42 0.6×	36	479
Mingquan Lin United States	11	163 0.3×	117 0.5×	102 1.3×	53 0.7×	56 0.8×	48	397
Liesbeth Vandewinckele Belgium	7	398 0.8×	139 0.5×	39 0.5×	112 1.5×	114 1.6×	11	593
Mostafa Ghelich Oghli Iran	9	237 0.5×	98 0.4×	97 1.2×	39 0.5×	19 0.3×	19	386
Jinlu Ma China	2	651 1.3×	418 1.6×	87 1.1×	70 1.0×	139 1.9×	5	707
Abhirup Banerjee United Kingdom	12	208 0.4×	110 0.4×	139 1.7×	38 0.5×	29 0.4×	51	473
Gustav Müller‐Franzes Germany	11	316 0.6×	239 0.9×	89 1.1×	70 1.0×	99 1.4×	22	567

Countries citing papers authored by Amine Amyar

Since Specialization

Citations

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

Fields of papers citing papers by Amine Amyar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amine Amyar

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

All Works

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20 of 20 papers shown

Amyar, Amine, Jakub Sroubek, Alan Kiang, et al.. (2025). Radiomic Cardiac MRI Signatures for Predicting Ventricular Arrhythmias in Patients With Nonischemic Dilated Cardiomyopathy. JACC Advances. 4(4). 101684–101684. 3 indexed citations

Schulz, Alexander, Amine Amyar, Jennifer Rodriguez, et al.. (2025). Quantitative myocardial blood flow and perfusion reserve with exercise cardiovascular magnetic resonance. Journal of Cardiovascular Magnetic Resonance. 27(2). 101988–101988.

Amyar, Amine, Shiro Nakamori, Long Ngo, et al.. (2025). Cardiovascular magnetic resonance radiologic-pathologic correlation in radiomic analysis of myocardium in non-ischemic dilated cardiomyopathy. Journal of Cardiovascular Magnetic Resonance. 27(1). 101881–101881.

Nakamori, Shiro, Amine Amyar, Ahmed S. Fahmy, et al.. (2024). Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy. Circulation. 150(1). 7–18. 9 indexed citations

Morales, Manuel A., Shiro Nakamori, Amine Amyar, et al.. (2024). Deformation-encoding Deep Learning Transformer for High-Frame-Rate Cardiac Cine MRI. Radiology Cardiothoracic Imaging. 6(3). e230177–e230177. 2 indexed citations

Amyar, Amine, Shiro Nakamori, Long Ngo, et al.. (2023). Abstract 12353: Unveiling the Hidden Insights: Cardiac Magnetic Resonance Radiomics Signature of the Myocardial Disease in Non-Ischemic Dilated Cardiomyopathy. Circulation. 148(Suppl_1).

Amyar, Amine, Ahmed S. Fahmy, Rui Guo, et al.. (2023). Scanner‐Independent MyoMapNet for Accelerated Cardiac MRI T₁ Mapping Across Vendors and Field Strengths. Journal of Magnetic Resonance Imaging. 59(1). 179–189. 3 indexed citations

Amyar, Amine, Shiro Nakamori, Jennifer Rodriguez, et al.. (2023). Gadolinium-Free Cardiac MRI Myocardial Scar Detection by 4D Convolution Factorization. Lecture notes in computer science. 14221. 639–648. 1 indexed citations

Nakamori, Shiro, Amine Amyar, Manuel A. Morales, et al.. (2023). Accelerated Cardiac MRI Cine with Use of Resolution Enhancement Generative Adversarial Inline Neural Network. Radiology. 307(5). e222878–e222878. 20 indexed citations

10.

Amyar, Amine, et al.. (2022). Multi-task multi-scale learning for outcome prediction in 3D PET images. Computers in Biology and Medicine. 151(Pt A). 106208–106208. 12 indexed citations

11.

Guo, Rui, Hossam El‐Rewaidy, Xiaoying Cai, et al.. (2022). Accelerated cardiac T1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T1 estimation approach. Journal of Cardiovascular Magnetic Resonance. 24(1). 6–6. 26 indexed citations

12.

Amyar, Amine, et al.. (2022). Weakly Supervised Tumor Detection in PET Using Class Response for Treatment Outcome Prediction. Journal of Imaging. 8(5). 130–130. 8 indexed citations

13.

Guo, Rui, Zhensen Chen, Amine Amyar, et al.. (2022). Improving accuracy of myocardial T₁ estimation in MyoMapNet. Magnetic Resonance in Medicine. 88(6). 2573–2582. 3 indexed citations

14.

Guo, Rui, Haikun Qi, Amine Amyar, et al.. (2022). Quantification of changes in myocardial T₁* values with exercise cardiac MRI using a free‐breathing non‐electrocardiograph radial imaging. Magnetic Resonance in Medicine. 88(4). 1720–1733. 4 indexed citations

15.

Yousefirizi, Fereshteh, et al.. (2021). Artificial Intelligence-Based Detection, Classification and Prediction/Prognosis in PET Imaging: Towards Radiophenomics. arXiv (Cornell University). 1 indexed citations

16.

Yousefirizi, Fereshteh, Pierre Decazes, Amine Amyar, et al.. (2021). AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging. PET Clinics. 17(1). 183–212. 44 indexed citations

17.

Amyar, Amine, Romain Modzelewski, Hua Li, & Su Ruan. (2020). Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation. Computers in Biology and Medicine. 126. 104037–104037. 411 indexed citations breakdown →

18.

Amyar, Amine, et al.. (2020). RADIOGAN:Deep Convolutional Conditional Generative Adversarial Network to Generate PET Images. arXiv (Cornell University). 28–33. 2 indexed citations

19.

Amyar, Amine, Su Ruan, Isabelle Gardin, et al.. (2019). 3-D RPET-NET: Development of a 3-D PET Imaging Convolutional Neural Network for Radiomics Analysis and Outcome Prediction. IEEE Transactions on Radiation and Plasma Medical Sciences. 3(2). 225–231. 27 indexed citations

20.

Amyar, Amine, Pierre Decazes, Su Ruan, & Romain Modzelewski. (2019). Contribution of class activation map on WB PET deep features for primary tumour classification. 60. 1212–1212. 1 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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