José V. Manjón

9.1k total citations · 5 hit papers
85 papers, 5.8k citations indexed

About

José V. Manjón is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Psychiatry and Mental health. According to data from OpenAlex, José V. Manjón has authored 85 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Vision and Pattern Recognition, 30 papers in Radiology, Nuclear Medicine and Imaging and 19 papers in Psychiatry and Mental health. Recurrent topics in José V. Manjón's work include Medical Image Segmentation Techniques (33 papers), Image and Signal Denoising Methods (24 papers) and Advanced Neuroimaging Techniques and Applications (18 papers). José V. Manjón is often cited by papers focused on Medical Image Segmentation Techniques (33 papers), Image and Signal Denoising Methods (24 papers) and Advanced Neuroimaging Techniques and Applications (18 papers). José V. Manjón collaborates with scholars based in Spain, France and Canada. José V. Manjón's co-authors include Pierrick Coupé, Montserrat Robles, D. Louis Collins, Luis Martí‐Bonmatí, Vladimir Fonov, Antoni Buades, Juan José Lull, Gracián García‐Martí, Jens C. Pruessner and Simon Fristed Eskildsen and has published in prestigious journals such as PLoS ONE, NeuroImage and Stroke.

In The Last Decade

José V. Manjón

80 papers receiving 5.7k citations

Hit Papers

Adaptive non‐local means denoising of MR images with spat... 2008 2026 2014 2020 2009 2010 2008 2016 2013 250 500 750
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.

  1. Adaptive non‐local means denoising of MR images with spatially varying noise levels
    2009 754 citations José V. Manjón, Pierrick Coupé et al. profile →
  2. Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation
    2010 501 citations Pierrick Coupé, José V. Manjón et al. NeuroImage profile →
  3. MRI denoising using Non-Local Means
    2008 416 citations José V. Manjón, José Carbonell‐Caballero et al. Medical Image Analysis profile →
  4. volBrain: An Online MRI Brain Volumetry System
    2016 391 citations José V. Manjón, Pierrick Coupé profile →
  5. Diffusion Weighted Image Denoising Using Overcomplete Local PCA
    2013 312 citations José V. Manjón, Pierrick Coupé et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
José V. Manjón Spain 38 2.2k 2.1k 1.2k 924 891 85 5.8k
Pierrick Coupé France 44 2.7k 1.2× 2.8k 1.3× 1.3k 1.2× 1.1k 1.2× 1.0k 1.2× 139 7.7k
Koen Van Leemput United States 36 2.3k 1.0× 2.3k 1.1× 1.5k 1.3× 1.1k 1.2× 873 1.0× 104 6.6k
Dzung L. Pham United States 44 3.2k 1.4× 3.5k 1.6× 1.2k 1.0× 1.2k 1.3× 576 0.6× 194 9.8k
Pew‐Thian Yap United States 47 3.2k 1.5× 3.2k 1.5× 2.2k 2.0× 890 1.0× 700 0.8× 305 8.7k
Vladimir Fonov Canada 39 2.5k 1.1× 1.1k 0.5× 2.0k 1.8× 1.1k 1.2× 1.1k 1.2× 146 6.8k
Zhaohua Ding United States 38 2.7k 1.2× 2.8k 1.3× 1.2k 1.1× 277 0.3× 428 0.5× 124 6.7k
Bennett A. Landman United States 49 6.2k 2.8× 2.7k 1.3× 1.9k 1.7× 1.2k 1.3× 808 0.9× 465 11.0k
Torsten Rohlfing United States 48 3.4k 1.6× 1.7k 0.8× 1.9k 1.6× 657 0.7× 524 0.6× 124 8.2k
Colin Studholme United States 48 3.4k 1.5× 2.2k 1.0× 1.6k 1.4× 452 0.5× 863 1.0× 147 8.4k
David W. Shattuck United States 35 2.5k 1.1× 1.8k 0.8× 1.8k 1.6× 730 0.8× 480 0.5× 87 5.8k

Countries citing papers authored by José V. Manjón

Since Specialization
Citations

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

Fields of papers citing papers by José V. Manjón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José V. Manjón. 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 José V. Manjón. The network helps show where José V. Manjón may publish in the future.

Co-authorship network of co-authors of José V. Manjón

This figure shows the co-authorship network connecting the top 25 collaborators of José V. Manjón. A scholar is included among the top collaborators of José V. Manjón 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 José V. Manjón. José V. Manjón 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
1.
Aliena‐Valero, Alicia, Irene Escudero‐Martínez, Fernando Aparici, et al.. (2025). Automatic etiological classification of stroke thrombus digital photographs using a deep learning model. Frontiers in Neurology. 16. 1534845–1534845.
2.
Gadea, Marién, Fernando Aparici, María de la Iglesia-Vayá, et al.. (2025). DeepCERES: A deep learning method for cerebellar lobule segmentation using ultra-high resolution multimodal MRI. NeuroImage. 308. 121063–121063. 2 indexed citations
3.
Coupé, Pierrick, Boris Mansencal, José V. Manjón, et al.. (2025). Lifespan Tree of Brain Anatomy: Diagnostic Values for Motor and Cognitive Neurodegenerative Diseases. Human Brain Mapping. 46(13). e70336–e70336.
4.
Yamamoto, Takayuki, Boris Mansencal, Vincent Planche, et al.. (2024). Vulnerability of Thalamic Nuclei at CSF Interface During the Entire Course of Multiple Sclerosis. Neurology Neuroimmunology & Neuroinflammation. 11(3). e200222–e200222. 5 indexed citations
5.
Alarcón, Teresa E., et al.. (2024). MRI Rician Noise Reduction Using Recurrent Convolutional Neural Networks. IEEE Access. 12. 128272–128284. 1 indexed citations
6.
Planche, Vincent, Boris Mansencal, José V. Manjón, et al.. (2024). Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan. Brain Communications. 6(2). fcae055–fcae055. 4 indexed citations
7.
Kreilkamp, Barbara A. K., José V. Manjón, Pierrick Coupé, et al.. (2023). Midbrain structure volume, estimated myelin and functional connectivity in idiopathic generalised epilepsy. Epilepsy & Behavior. 140. 109084–109084.
8.
Coupé, Pierrick, et al.. (2023). Lifespan neurodegeneration of the human brain in multiple sclerosis. Human Brain Mapping. 44(17). 5602–5611. 11 indexed citations
9.
Planche, Vincent, José V. Manjón, Boris Mansencal, et al.. (2022). Structural progression of Alzheimer’s disease over decades: the MRI staging scheme. Brain Communications. 4(3). fcac109–fcac109. 61 indexed citations
10.
Coupé, Pierrick, José V. Manjón, Catherine Helmer, et al.. (2021). Distinct Hippocampal Subfields Atrophy in Older People With Vascular Brain Injuries. Stroke. 52(5). 1741–1750. 8 indexed citations
11.
Manjón, José V., José E. Romero, & Pierrick Coupé. (2021). Deep learning based MRI contrast synthesis using full volume prediction using full volume prediction. Biomedical Physics & Engineering Express. 8(1). 15013–15013. 5 indexed citations
12.
Reid, Lee B., Eloy Martínez‐Heras, José V. Manjón, et al.. (2021). Fully automated delineation of the optic radiation for surgical planning using clinically feasible sequences. Human Brain Mapping. 42(18). 5911–5926. 4 indexed citations
13.
Ta, Vinh‐Thong, et al.. (2020). DeepLesionBrain: Towards a broader deep-learning generalization for\n multiple sclerosis lesion segmentation. arXiv (Cornell University). 44 indexed citations
14.
Coupé, Pierrick, Catherine Helmer, José V. Manjón, et al.. (2020). Differential annualized rates of hippocampal subfields atrophy in aging and future Alzheimer's clinical syndrome. Neurobiology of Aging. 90. 75–83. 35 indexed citations
15.
Planche, Vincent, José E. Romero, José V. Manjón, et al.. (2018). Regional hippocampal vulnerability in early multiple sclerosis: Dynamic pathological spreading from dentate gyrus to CA1. Human Brain Mapping. 39(4). 1814–1824. 43 indexed citations
16.
Xie, Long, Laura E.M. Wisse, Sandhitsu R. Das, et al.. (2016). Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI. Lecture notes in computer science. 9901. 564–571. 27 indexed citations
17.
Coupé, Pierrick, Simon Fristed Eskildsen, José V. Manjón, et al.. (2012). SNIPE: A New Method to Identify Imaging Biomarker for Early Detection of Alzheimer’s Disease. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
18.
Escartí, María J., María de la Iglesia-Vayá, Luis Martí‐Bonmatí, et al.. (2010). Increased amygdala and parahippocampal gyrus activation in schizophrenic patients with auditory hallucinations: An fMRI study using independent component analysis. Schizophrenia Research. 117(1). 31–41. 60 indexed citations
19.
Coupé, Pierrick, et al.. (2010). Robust Rician noise estimation for MR images. Medical Image Analysis. 14(4). 483–493. 176 indexed citations
20.
Bristow, Michael, José V. Manjón, M. Louis Lauzon, et al.. (2004). A novel method demonstrates that gray and white matter have measurable differences in cerebral perfusion and apparent diffusion coefficient values in stroke penumbra. Stroke. 35. 263–263. 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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