Oscar Acosta

4.3k total citations · 1 hit paper
144 papers, 2.3k citations indexed

About

Oscar Acosta is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Oscar Acosta has authored 144 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Radiology, Nuclear Medicine and Imaging, 54 papers in Radiation and 38 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Oscar Acosta's work include Advanced Radiotherapy Techniques (54 papers), Medical Imaging Techniques and Applications (47 papers) and Radiomics and Machine Learning in Medical Imaging (31 papers). Oscar Acosta is often cited by papers focused on Advanced Radiotherapy Techniques (54 papers), Medical Imaging Techniques and Applications (47 papers) and Radiomics and Machine Learning in Medical Imaging (31 papers). Oscar Acosta collaborates with scholars based in France, Australia and Colombia. Oscar Acosta's co-authors include R. de Crevoisier, C. Lafond, Olivier Salvado, Antoine Simon, Pascal Haigron, Pierrick Bourgeat, Jürgen Fripp, J. Castelli, Juan David Ospina and Sébastien Ourselin and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and NeuroImage.

In The Last Decade

Oscar Acosta

139 papers receiving 2.2k 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. profile →

Peers

Countries citing papers authored by Oscar Acosta

Since Specialization

Citations

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

Fields of papers citing papers by Oscar Acosta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oscar Acosta

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

#	Work	Indexed citations
1	Impact of contrast enhancement phase on CT-based radiomics analysis for predicting post-surgical recurrence in renal cell carcinoma 2025 ·Japanese Journal of Radiology ·Z. Khene, Raj Bhanvadia, Isamu Tachibana, (unknown), (unknown), (unknown), (unknown), (unknown), Oscar Acosta, R. de Crevoisier, Karim Bensalah, Yair Lotan, Vitaly Margulis	0
2	New Deep Learning-Based Approach for Dysphagia Assessment from Videofluoroscopy Swallowing Studies 2024 ·SPIRE - Sciences Po Institutional REpository ·(unknown), Caroline Tessier, (unknown), (unknown), F. Jégoux, Javier Pascau, Oscar Acosta	1
3	Determination of acceptable Hounsfield units uncertainties via a sensitivity analysis for an accurate dose calculation in the context of prostate MRI-only radiotherapy 2023 ·Physical and Engineering Sciences in Medicine ·(unknown), A. Barateau, Peter B. Greer, C. Lafond, Jean‐Claude Nunes, R. de Crevoisier, Jason Dowling, Oscar Acosta	2
4	Clinical Application of Digital and Computational Pathology in Renal Cell Carcinoma: A Systematic Review 2023 ·European Urology Oncology ·Z. Khene, Solène‐Florence Kammerer‐Jacquet, Pierre Bigot, (unknown), Laurence Albigès, Vitaly Margulis, R. de Crevoisier, Oscar Acosta, Nathalie Rioux‐Leclercq, Yair Lotan, Morgan Rouprêt, Karim Bensalah	8
5	Deep learning-based segmentation of prostatic urethra on computed tomography scans for treatment planning 2023 ·Physics and Imaging in Radiation Oncology ·(unknown), (unknown), Eugenia Mylona, (unknown), C. Cozzarini, (unknown), T. Rancati, C. Fiorino, R. de Crevoisier, Oscar Acosta, Javier Pascau	4
6	Selective sparing of bladder and rectum sub-regions in radiotherapy of prostate cancer combining knowledge-based automatic planning and multicriteria optimization 2023 ·Physics and Imaging in Radiation Oncology ·(unknown), Roberta Castriconi, (unknown), (unknown), (unknown), S. Broggi, Javier Pascau, (unknown), C. Cozzarini, R. de Crevoisier, T. Rancati, Oscar Acosta, C. Fiorino	2
7	Deep Learning Methodologies Applied to Digital Pathology in Prostate Cancer: A Systematic Review 2023 ·Diagnostics ·(unknown), (unknown), Oscar Acosta, R. de Crevoisier, (unknown), Delphine Loussouarn, Nathalie Rioux‐Leclercq, Z. Khene, Romain Mathiéu, Karim Bensalah, Thierry Pécot, Solène‐Florence Kammerer‐Jacquet	22
8	A deep learning model to generate synthetic CT for prostate MR-only radiotherapy dose planning: a multicenter study 2023 ·Frontiers in Oncology ·(unknown), (unknown), Jean‐Claude Nunes, (unknown), (unknown), (unknown), (unknown), Jennifer Le Guévelou, Peter B. Greer, Jason Dowling, Oscar Acosta, Igor Bessières, (unknown), (unknown), R. de Crevoisier, C. Lafond, A. Barateau	8
9	Deep Learning-Based Segmentation of Head and Neck Organs-at-Risk with Clinical Partially Labeled Data 2022 ·Entropy ·(unknown), J. Castelli, Antoine Simon, R. de Crevoisier, Oscar Acosta, Javier Pascau	6
10	Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study 2022 ·Clinical and Translational Radiation Oncology ·(unknown), Vincent Andrearczyk, Valentin Oreiller, Daniel Abler, J. Castelli, Oscar Acosta, R. de Crevoisier, Martin Vallières, Mario Jreige, John O. Prior, Adrien Depeursinge	5
11	Head-and-Neck MRI-only radiotherapy treatment planning: From acquisition in treatment position to pseudo-CT generation 2020 ·Cancer/Radiothérapie ·A. Largent, (unknown), (unknown), Jean‐Claude Nunes, N. Reynaert, J. Castelli, É. Chajon, Oscar Acosta, Giulio Gambarota, R. de Crevoisier, Hervé Saint‐Jalmes	16
12	The importance of feature aggregation in radiomics: a head and neck cancer study 2020 ·Scientific Reports ·(unknown), Oscar Acosta, J. Castelli, R. de Crevoisier, Henning Müller, Adrien Depeursinge	11
13	Rectal and Urethro-Vesical Subregions for Toxicity Prediction After Prostate Cancer Radiation Therapy: Validation of Voxel-Based Models in an Independent Population 2020 ·International Journal of Radiation OncologyBiologyPhysics ·Eugenia Mylona, Martin A. Ebert, Angel Kennedy, David Joseph, James W. Denham, Allison Steigler, S. Supiot, Oscar Acosta, R. de Crevoisier	16
14	Local dose analysis to predict acute and late urinary toxicities after prostate cancer radiotherapy: Assessment of cohort and method effects 2020 ·Radiotherapy and Oncology ·Eugenia Mylona, A. Cicchetti, T. Rancati, F. Palorini, C. Fiorino, (unknown), Nicolas Magné, G. Créhange, R. Valdagni, Oscar Acosta, R. de Crevoisier	16
15	Statistical Shape Model to Generate a Planning Library for Cervical Adaptive Radiotherapy 2018 ·IEEE Transactions on Medical Imaging ·B. Rigaud, Antoine Simon, (unknown), Julie Leseur, (unknown), (unknown), J. Castelli, C. Lafond, Oscar Acosta, Pascal Haigron, R. de Crevoisier	34
16	Role of quantitative computed tomography texture analysis in the prediction of adherent perinephric fat 2018 ·World Journal of Urology ·Z. Khene, Karim Bensalah, A. Largent, Shahrokh F. Shariat, G. Verhoest, B. Peyronnet, Oscar Acosta, (unknown), Romain Mathiéu	14
17	Segmentation of pelvic structures for planning CT using a geometrical shape model tuned by a multi-scale edge detector 2014 ·Physics in Medicine and Biology ·Fabio Martínez, Eduardo Romero, (unknown), Antoine Simon, Pascal Haigron, R. de Crevoisier, Oscar Acosta	31
18	Voxel-based population analysis for correlating local dose and rectal toxicity in prostate cancer radiotherapy 2013 ·Physics in Medicine and Biology ·Oscar Acosta, (unknown), Juan David Ospina, Antoine Simon, Pascal Haigron, C. Lafond, R. de Crevoisier	64
19	Cortical surface mapping using topology correction, partial flattening and 3D shape context-based non-rigid registration for use in quantifying atrophy in Alzheimer's disease 2011 ·Journal of Neuroscience Methods ·Oscar Acosta, Jürgen Fripp, Vincent Doré, Pierrick Bourgeat, (unknown), Gaël Chételat, Andrea Rueda, Victor L. Villemagne, Cassandra Szoeke, David Ames, Kathryn A. Ellis, Ralph N. Martins, Colin L. Masters, Christopher C. Rowe, (unknown), (unknown), Di Xiao, Parnesh Raniga, Vincent Barra, Olivier Salvado	13
20	MR-Less High Dimensional Spatial Normalization of 11C PiB PET Images on a Population of Elderly, Mild Cognitive Impaired and Alzheimer Disease Patients 2008 ·Lecture notes in computer science ·Jürgen Fripp, Pierrick Bourgeat, Parnesh Raniga, Oscar Acosta, Victor L. Villemagne, Gareth Jones, Graeme O’Keefe, Christopher C. Rowe, Sébastien Ourselin, Olivier Salvado	19

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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