Florent Tixier

4.3k total citations · 3 hit papers
56 papers, 3.0k citations indexed

About

Florent Tixier is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Florent Tixier has authored 56 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Oncology and 13 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Florent Tixier's work include Radiomics and Machine Learning in Medical Imaging (47 papers), Medical Imaging Techniques and Applications (25 papers) and MRI in cancer diagnosis (9 papers). Florent Tixier is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (47 papers), Medical Imaging Techniques and Applications (25 papers) and MRI in cancer diagnosis (9 papers). Florent Tixier collaborates with scholars based in France, United States and United Kingdom. Florent Tixier's co-authors include Dimitris Visvikis, Mathieu Hatt, Catherine Cheze Le Rest, Olivier Pradier, Laurent Corcos, N. Albarghach, Jean‐Philippe Metges, Paul E. Kinahan, Larry A. Pierce and R. Perdrisot and has published in prestigious journals such as PLoS ONE, Scientific Reports and Physics in Medicine and Biology.

In The Last Decade

Florent Tixier

51 papers receiving 3.0k citations

Hit Papers

Intratumor Heterogeneity Characterized by Textural Featur... 2011 2026 2016 2021 2011 2014 2016 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Florent Tixier France 22 2.7k 908 757 548 334 56 3.0k
Fanny Orlhac France 21 2.9k 1.0× 914 1.0× 833 1.1× 499 0.9× 254 0.8× 48 3.1k
Cuishan Liang China 11 2.2k 0.8× 1.0k 1.1× 610 0.8× 755 1.4× 400 1.2× 14 2.7k
Zelan Ma China 12 2.3k 0.8× 1.1k 1.2× 630 0.8× 795 1.5× 454 1.4× 18 2.8k
Catherine Cheze Le Rest France 29 3.9k 1.4× 1.1k 1.2× 1.1k 1.4× 516 0.9× 351 1.1× 74 4.2k
Mengjie Fang China 31 2.5k 0.9× 1.4k 1.6× 564 0.7× 657 1.2× 365 1.1× 65 3.0k
Ronald Boellard Netherlands 4 3.8k 1.4× 1.4k 1.6× 1000 1.3× 703 1.3× 482 1.4× 4 4.2k
Martin Vallières Canada 22 3.0k 1.1× 1.1k 1.2× 816 1.1× 405 0.7× 196 0.6× 48 3.3k
Thibaud Coroller United States 16 2.5k 0.9× 1.5k 1.7× 763 1.0× 408 0.7× 252 0.8× 32 2.9k
Shaofeng Duan China 28 1.9k 0.7× 855 0.9× 449 0.6× 460 0.8× 314 0.9× 141 2.3k
Sylvain Reuzé France 12 1.7k 0.6× 565 0.6× 436 0.6× 372 0.7× 195 0.6× 18 2.0k

Countries citing papers authored by Florent Tixier

Since Specialization
Citations

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

Fields of papers citing papers by Florent Tixier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Florent Tixier

This figure shows the co-authorship network connecting the top 25 collaborators of Florent Tixier. A scholar is included among the top collaborators of Florent Tixier 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 Florent Tixier. Florent Tixier 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
2.
Tixier, Florent, et al.. (2025). The Role of AI in the Evaluation of Neuroendocrine Tumors: Current State of the Art. Seminars in Nuclear Medicine. 55(3). 345–357. 4 indexed citations
3.
Tixier, Florent, et al.. (2025). Radiomics in Early Detection of Pancreatic Ductal Adenocarcinoma: A Close Look at Its Current Status and Challenges to Clinical Implementation. Canadian Association of Radiologists Journal. 77(1). 107–118. 2 indexed citations
7.
Tixier, Florent, et al.. (2025). Early detection of pancreatic cancer on computed tomography: advancements with deep learning. PubMed. 2(5). umaf028–umaf028. 1 indexed citations
8.
Oviedo, Felipe, Florent Tixier, Satomi Kawamoto, et al.. (2025). Benchmarking robustness of automated CT pancreas segmentation: achieving human-level reliability through human-in-the-loop optimization. PubMed. 2(6). umaf040–umaf040. 1 indexed citations
9.
Azadi, Javad, Sheila Sheth, Satomi Kawamoto, et al.. (2024). Radiomics machine learning algorithm facilitates detection of small pancreatic neuroendocrine tumors on CT. Diagnostic and Interventional Imaging. 106(1). 28–40. 9 indexed citations
10.
Visvikis, Dimitris, Michel Koole, Ian S. Armstrong, et al.. (2021). Advances in PET/CT Imaging. 1 indexed citations
11.
Tixier, Florent, et al.. (2021). Evaluation of conventional and deep learning based image harmonization methods in radiomics studies. Physics in Medicine and Biology. 66(24). 245009–245009. 21 indexed citations
12.
Huang, Raymond Y., Robert J. Young, Benjamin M. Ellingson, et al.. (2020). Volumetric analysis of IDH-mutant lower-grade glioma: a natural history study of tumor growth rates before and after treatment. Neuro-Oncology. 22(12). 1822–1830. 26 indexed citations
13.
14.
Tixier, Florent, Catherine Cheze Le Rest, Ulrike Schick, et al.. (2020). Transcriptomics in cancer revealed by Positron Emission Tomography radiomics. Scientific Reports. 10(1). 5660–5660. 16 indexed citations
15.
Um, Hyemin, et al.. (2019). Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets. Physics in Medicine and Biology. 64(16). 165011–165011. 84 indexed citations
16.
Hatt, Mathieu, Florent Tixier, Marie-Charlotte Desseroit, et al.. (2019). Revisiting the identification of tumor sub-volumes predictive of residual uptake after (chemo)radiotherapy: influence of segmentation methods on 18F-FDG PET/CT images. Scientific Reports. 9(1). 14925–14925. 5 indexed citations
17.
Desseroit, Marie-Charlotte, Dimitris Visvikis, Florent Tixier, et al.. (2016). Development of a nomogram combining clinical staging with 18F-FDG PET/CT image features in non-small-cell lung cancer stage I–III. European Journal of Nuclear Medicine and Molecular Imaging. 43(8). 1477–1485. 92 indexed citations
18.
Hatt, Mathieu, Florent Tixier, Larry A. Pierce, et al.. (2016). Characterization of PET/CT images using texture analysis: the past, the present… any future?. European Journal of Nuclear Medicine and Molecular Imaging. 44(1). 151–165. 353 indexed citations breakdown →
19.
Grootjans, Willem, Florent Tixier, Dennis Vriens, et al.. (2015). Impact of Optimal Respiratory Gated Positron Emission Tomography on Characterisation of Intra-Tumour Heterogeneity in Lung Cancer Patients. Data Archiving and Networked Services (DANS). 1 indexed citations
20.
Tixier, Florent, Catherine Cheze Le Rest, Mathieu Hatt, et al.. (2011). Intratumor Heterogeneity Characterized by Textural Features on Baseline 18F-FDG PET Images Predicts Response to Concomitant Radiochemotherapy in Esophageal Cancer. Journal of Nuclear Medicine. 52(3). 369–378. 574 indexed citations breakdown →

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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