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.
MRI profile and response to endovascular reperfusion after stroke (DEFUSE 2): a prospective cohort study
2012578 citationsMaarten G. Lansberg, Matús Straka et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Matús Straka'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 Matús Straka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matús Straka more than expected).
This network shows the impact of papers produced by Matús Straka. 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 Matús Straka. The network helps show where Matús Straka may publish in the future.
Co-authorship network of co-authors of Matús Straka
This figure shows the co-authorship network connecting the top 25 collaborators of Matús Straka.
A scholar is included among the top collaborators of Matús Straka 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 Matús Straka. Matús Straka is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tu, Hans T.H., Bruce Campbell, Søren Christensen, et al.. (2011). Worse Stroke Outcome In Atrial Fibrillation Links To More Severe Hypoperfusion. Stroke. 42(3).1 indexed citations
6.
Campbell, Bruce, Archana Purushotham, Søren Christensen, et al.. (2011). The Acute Diffusion Lesion Reliably Represents Infarct Core: Clinically Relevant Reversibility Is Rare. Stroke. 42(3).1 indexed citations
7.
Lee, Jun, Maarten G. Lansberg, Michael Mlynash, et al.. (2011). The Combination Of Reperfusion And Recanalization Predicts Favorable Outcome Better Than Reperfusion Or Recanalization Alone In Target Mismatch Patients. Stroke. 42(3).1 indexed citations
Lansberg, Maarten G., Jun Lee, Sören Christensen, et al.. (2010). DEFUSE and EPITHET: Two Different Studies With One Consistent Message. Stroke. 41(4).2 indexed citations
11.
Silva, Deidre Anne De, Michael Mlynash, Maarten G. Lansberg, et al.. (2010). Large and Severe Baseline PWI Volumes Predict Poor Response to Intravenous tPA vs. Placebo in the Pooled DEFUSE-EPITHET Database. Stroke. 41(4).1 indexed citations
12.
Christensen, Sören, Bruce Campbell, Natàlia Pérez de la Ossa, et al.. (2010). Optimal Perfusion Thresholds for Prediction of Tissue Destined for Infarction in the Combined EPITHET and DEFUSE Dataset. Stroke. 41(4).14 indexed citations
13.
Mlynash, Michael, Deidre Anne De Silva, Maarten G. Lansberg, et al.. (2010). Optimal Definition of the Malignant Profile in the DEFUSE-EPITHET Pooled Database. Stroke. 41(4).4 indexed citations
14.
Campbell, Bruce, Søren Christensen, Mark Parsons, et al.. (2010). Very Low Cerebral Blood Volume Predicts Hemorrhagic Transformation Better Than Diffusion Lesion Volume in Acute Ischemic Stroke. Stroke. 41(4).1 indexed citations
15.
Straka, Matús, Maarten G. Lansberg, Søren Christensen, et al.. (2010). Is Reduced CBV a Reliable Surrogate Marker for Infarct Core and Can It Be Used to Identify Mismatch. Stroke. 41(4).1 indexed citations
16.
Lee, Jun, Maarten G. Lansberg, Michael Mlynash, et al.. (2010). Validation of the Malignant Profile in the DEFUSE-EPITHET Pooled Database. Stroke. 41(4).1 indexed citations
Šrámek, Miloš, et al.. (2004). The f3d tools for processing and visualization of volumetric data. Journal of Medical Informatics & Technologies. 7.4 indexed citations
19.
Straka, Matús, et al.. (2003). 3D watershed transform combined with a probabilistic atlas for medical image segmentation. Journal of Medical Informatics & Technologies. 6.19 indexed citations
20.
Straka, Matús, et al.. (2003). Bone Segmentation in CT Angiography Data Using a Probabilistic Atlas.. Vision Modeling and Visualization. 505–512.10 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.