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.
SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining
2023195 citationsBenjamin Billot, Douglas N. Greve et al.Medical Image Analysisprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Adrian V. Dalca
Since
Specialization
Citations
This map shows the geographic impact of Adrian V. Dalca'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 Adrian V. Dalca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian V. Dalca more than expected).
This network shows the impact of papers produced by Adrian V. Dalca. 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 Adrian V. Dalca. The network helps show where Adrian V. Dalca may publish in the future.
Co-authorship network of co-authors of Adrian V. Dalca
This figure shows the co-authorship network connecting the top 25 collaborators of Adrian V. Dalca.
A scholar is included among the top collaborators of Adrian V. Dalca 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 Adrian V. Dalca. Adrian V. Dalca is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Young, Sean I., Adrian V. Dalca, Enzo Ferrante, et al.. (2023). Supervision by Denoising. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(9). 7279–7291.3 indexed citations
Billot, Benjamin, Douglas N. Greve, Oula Puonti, et al.. (2023). SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining. Medical Image Analysis. 86. 102789–102789.195 indexed citations breakdown →
Hoffmann, Malte, Benjamin Billot, Juan Eugenio Iglesias, Bruce Fischl, & Adrian V. Dalca. (2020). Learning Multi-Modal Image Registration without Real Data. arXiv (Cornell University).1 indexed citations
15.
Billot, Benjamin, Douglas N. Greve, Koen Van Leemput, et al.. (2020). A Learning Strategy for Contrast-agnostic MRI Segmentation. 75–93.3 indexed citations
Dalca, Adrian V., et al.. (2019). Learning Conditional Deformable Templates with Convolutional Networks. DSpace@MIT (Massachusetts Institute of Technology). 32. 804–816.10 indexed citations
18.
Dalca, Adrian V., et al.. (2019). Adaptive Compressed Sensing MRI with Unsupervised Learning.. arXiv (Cornell University).4 indexed citations
19.
Dalca, Adrian V., Katherine L. Bouman, William T. Freeman, et al.. (2018). Medical Image Imputation From Image Collections. IEEE Transactions on Medical Imaging. 38(2). 504–514.25 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.