A. Largent

526 total citations · 1 hit paper
13 papers, 343 citations indexed

About

A. Largent is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, A. Largent has authored 13 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Radiation and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in A. Largent's work include Medical Imaging Techniques and Applications (9 papers), Advanced Radiotherapy Techniques (9 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). A. Largent is often cited by papers focused on Medical Imaging Techniques and Applications (9 papers), Advanced Radiotherapy Techniques (9 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). A. Largent collaborates with scholars based in France, Australia and United States. A. Largent's co-authors include Oscar Acosta, Jean‐Claude Nunes, R. de Crevoisier, C. Lafond, A. Barateau, J. Castelli, Peter B. Greer, Jason Dowling, Hervé Saint‐Jalmes and Eugenia Mylona and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics and Journal of Magnetic Resonance Imaging.

In The Last Decade

A. Largent

13 papers receiving 343 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 methods to generate synthetic CT from MRI in radiotherapy: A literature review

2021 125 citations Jean‐Claude Nunes, A. Largent et al. Physica Medica profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. Largent France	8	283	200	106	66	58	13	343
A. Barateau France	10	350 1.2×	291 1.5×	150 1.4×	92 1.4×	69 1.2×	36	452
Marian Axente United States	8	195 0.7×	73 0.4×	125 1.2×	59 0.9×	28 0.5×	22	287
Donghwi Hwang South Korea	9	484 1.7×	156 0.8×	236 2.2×	73 1.1×	110 1.9×	13	588
Koen A. J. Eppenhof Netherlands	10	240 0.8×	81 0.4×	105 1.0×	59 0.9×	187 3.2×	11	367
Azadeh Akhavanallaf Switzerland	13	528 1.9×	143 0.7×	252 2.4×	108 1.6×	38 0.7×	29	626
Gisèle Pereira United States	8	257 0.9×	102 0.5×	103 1.0×	98 1.5×	43 0.7×	12	359
Benjamin Ziemer United States	11	191 0.7×	128 0.6×	109 1.0×	77 1.2×	28 0.5×	20	312
Shaoyan Pan United States	12	258 0.9×	67 0.3×	121 1.1×	51 0.8×	88 1.5×	35	372
Haonan Xiao Hong Kong	11	227 0.8×	93 0.5×	70 0.7×	61 0.9×	53 0.9×	23	302
Filipa Guerreiro Netherlands	9	219 0.8×	217 1.1×	70 0.7×	125 1.9×	36 0.6×	13	313

Countries citing papers authored by A. Largent

Since Specialization

Citations

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

Fields of papers citing papers by A. Largent

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Largent

This figure shows the co-authorship network connecting the top 25 collaborators of A. Largent. A scholar is included among the top collaborators of A. Largent 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 A. Largent. A. Largent 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:

13 of 13 papers shown

Barateau, A., Oscar Acosta, Jason Dowling, et al.. (2022). A high-performance method of deep learning for prostate MR-only radiotherapy planning using an optimized Pix2Pix architecture. Physica Medica. 103. 108–118. 12 indexed citations

Nunes, Jean‐Claude, A. Largent, Oscar Acosta, et al.. (2021). Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review. Physica Medica. 89. 265–281. 125 indexed citations breakdown →

Largent, A., Kushal Kapse, Scott D. Barnett, et al.. (2021). Image Quality Assessment of Fetal Brain MRI Using Multi‐Instance Deep Learning Methods. Journal of Magnetic Resonance Imaging. 54(3). 818–829. 15 indexed citations

Largent, A., Jean‐Claude Nunes, N. Reynaert, et al.. (2020). Head-and-Neck MRI-only radiotherapy treatment planning: From acquisition in treatment position to pseudo-CT generation. Cancer/Radiothérapie. 24(4). 288–297. 16 indexed citations

Barateau, A., R. de Crevoisier, A. Largent, et al.. (2020). Comparison of CBCT‐based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning. Medical Physics. 47(10). 4683–4693. 46 indexed citations

Largent, A., A. Barateau, Jean‐Claude Nunes, et al.. (2019). Comparison of Deep Learning-Based and Patch-Based Methods for Pseudo-CT Generation in MRI-Based Prostate Dose Planning. International Journal of Radiation Oncology*Biology*Physics. 105(5). 1137–1150. 64 indexed citations

Largent, A., A. Barateau, Jean‐Claude Nunes, et al.. (2019). 45 A comparison of pseudo-CT generation methods for prostate MRI-based dose planning: deep learning, patch-based, atlas-based and bulk-density methods. Physica Medica. 68. 28–28. 2 indexed citations

Largent, A., Jean‐Claude Nunes, Hervé Saint‐Jalmes, et al.. (2019). Pseudo-CT Generation for Mri-only Radiotherapy: Comparative Study Between A Generative Adversarial Network, A U-Net Network, A Patch-Based, and an Atlas Based Methods. 1109–1113. 2 indexed citations

Khene, Z., Karim Bensalah, A. Largent, et al.. (2018). Role of quantitative computed tomography texture analysis in the prediction of adherent perinephric fat. World Journal of Urology. 36(10). 1635–1642. 14 indexed citations

10.

Largent, A., A. Barateau, Jean‐Claude Nunes, et al.. (2018). 29 Pseudo-CT generation for MRI-only radiotherapy treatment planning: comparison between patch-based, atlas-based and bulk density methods. Physica Medica. 56. 17–18. 2 indexed citations

11.

Largent, A., A. Barateau, Jean‐Claude Nunes, et al.. (2018). Pseudo-CT Generation for MRI-Only Radiation Therapy Treatment Planning: Comparison Among Patch-Based, Atlas-Based, and Bulk Density Methods. International Journal of Radiation Oncology*Biology*Physics. 103(2). 479–490. 36 indexed citations

12.

Largent, A., Jean‐Claude Nunes, C. Lafond, et al.. (2017). Planification à partir d’imagerie par résonance magnétique en radiothérapie. Cancer/Radiothérapie. 21(8). 788–798. 5 indexed citations

13.

Largent, A., Jean‐Claude Nunes, C. Lafond, et al.. (2017). Planification à partir d’imagerie par résonance magnétique en radiothérapie. Cancer/Radiothérapie. 21(8). 820–820. 4 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.

Explore authors with similar magnitude of impact