Adrian V. Dalca
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 2%
- Molecular Biology
- Artificial Intelligence top 5%
- Biomedical Engineering
- Co-authors
- Mert R. SabuncuGuha BalakrishnanMichael BrudnoStephen M. RumblePhil LacrouteJohn V. GuttagMarc FiumeArend Sidow
- Topics
- Medical Image Segmentation Techniques (26 papers)Advanced Neural Network Applications (14 papers)Advanced MRI Techniques and Applications (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingHealth Informatics
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Adrian V. Dalca
66 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Radiology, Nuclear Medicine and Imaging 670
- Computer Vision and Pattern Recognition 629
- Molecular Biology 401
- Artificial Intelligence 391
- Biomedical Engineering 233
Countries citing papers authored by Adrian V. Dalca
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).
Fields of papers citing papers by Adrian V. Dalca
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.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 7 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retrainingbreakdown → | 195 |
| 9 | 10 | |
| 10 | 11 | |
| 11 | 20 | |
| 12 | 0 | |
| 13 | 81 | |
| 14 | Learning Multi-Modal Image Registration without Real Data | 1 |
| 15 | A Learning Strategy for Contrast-agnostic MRI Segmentation | 3 |
| 16 | 237 | |
| 17 | Learning Conditional Deformable Templates with Convolutional Networks | 10 |
| 18 | Adaptive Compressed Sensing MRI with Unsupervised Learning. | 4 |
| 19 | 25 | |
| 20 | 405 |
About Adrian V. Dalca
Adrian V. Dalca is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 71 papers that have together received 2.1k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (26 papers), Advanced Neural Network Applications (14 papers) and Advanced MRI Techniques and Applications (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (629 citations), Radiology, Nuclear Medicine and Imaging (670 citations) and Health Informatics (35 citations). Adrian V. Dalca has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Mert R. Sabuncu, Guha Balakrishnan, Michael Brudno, Stephen M. Rumble, Phil Lacroute, John V. Guttag, Marc Fiume, Arend Sidow, John Guttag and Juan Eugenio Iglesias. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.