Sarah Frisken

2.0k total citations
55 papers, 1.3k citations indexed

About

Sarah Frisken is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Sarah Frisken has authored 55 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 23 papers in Radiology, Nuclear Medicine and Imaging and 14 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Sarah Frisken's work include Medical Image Segmentation Techniques (18 papers), Computer Graphics and Visualization Techniques (13 papers) and Medical Imaging Techniques and Applications (12 papers). Sarah Frisken is often cited by papers focused on Medical Image Segmentation Techniques (18 papers), Computer Graphics and Visualization Techniques (13 papers) and Medical Imaging Techniques and Applications (12 papers). Sarah Frisken collaborates with scholars based in United States, Germany and Canada. Sarah Frisken's co-authors include Ronald N. Perry, Alyn Rockwood, Thouis R. Jones, Alexandra J. Golby, William M. Wells, Steve Pieper, Tina Kapur, Wenya Linda Bi, Parikshit Juvekar and Rahul A. Sastry and has published in prestigious journals such as NeuroImage, Journal of neurosurgery and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Sarah Frisken

49 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sarah Frisken United States 14 548 516 487 232 173 55 1.3k
Christof Rezk‐Salama Germany 14 570 1.0× 372 0.7× 567 1.2× 107 0.5× 70 0.4× 31 891
S. Gottschalk Germany 10 639 1.2× 351 0.7× 1.1k 2.4× 38 0.2× 145 0.8× 19 2.0k
U. Tiede Germany 24 508 0.9× 417 0.8× 924 1.9× 279 1.2× 536 3.1× 66 1.8k
Grand Roman Joldes Australia 23 57 0.1× 509 1.0× 204 0.4× 214 0.9× 757 4.4× 67 1.6k
Xiaohu Guo United States 18 452 0.8× 531 1.0× 241 0.5× 109 0.5× 56 0.3× 73 952
Dirk Bartz Germany 20 707 1.3× 359 0.7× 1.0k 2.1× 102 0.4× 131 0.8× 83 1.4k
William A. Barrett United States 15 262 0.5× 183 0.4× 1.2k 2.5× 235 1.0× 146 0.8× 49 1.7k
Jon Sporring Denmark 16 108 0.2× 99 0.2× 399 0.8× 212 0.9× 95 0.5× 77 940
Tim McInerney Canada 12 352 0.6× 569 1.1× 2.0k 4.2× 661 2.8× 421 2.4× 25 2.8k
Jun‐ichiro Toriwaki Japan 17 181 0.3× 130 0.3× 761 1.6× 253 1.1× 132 0.8× 95 1.3k

Countries citing papers authored by Sarah Frisken

Since Specialization
Citations

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

Fields of papers citing papers by Sarah Frisken

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sarah Frisken

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Frisken. A scholar is included among the top collaborators of Sarah Frisken 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 Sarah Frisken. Sarah Frisken 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.
Dorent, Reuben, Erickson Torio, Nazim Haouchine, et al.. (2024). 223 An Artificial Intelligence Framework for Brain Tumor Delineation in Intraoperative Ultrasound. Neurosurgery. 70(Supplement_1). 60–60.
2.
3.
Juvekar, Parikshit, Erickson Torio, Wenya Linda Bi, et al.. (2023). Mapping Resection Progress by Tool-Tip Tracking during Brain Tumor Surgery for Real-Time Estimation of Residual Tumor. Cancers. 15(3). 825–825. 3 indexed citations
4.
Bourantas, George C., Grand Roman Joldes, Simon K. Warfield, et al.. (2023). SlicerCBM: automatic framework for biomechanical analysis of the brain. International Journal of Computer Assisted Radiology and Surgery. 18(10). 1925–1940. 1 indexed citations
5.
Haouchine, Nazim, Erickson Torio, Parikshit Juvekar, et al.. (2022). A tool-free neuronavigation method based on single-view hand tracking. Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization. 11(4). 1307–1315. 3 indexed citations
6.
Horvath, Samantha, Jean‐Christophe Fillion‐Robin, Samuel Gerber, et al.. (2022). NousNav: A low-cost neuronavigation system for deployment in lower-resource settings. International Journal of Computer Assisted Radiology and Surgery. 17(9). 1745–1750. 9 indexed citations
7.
Frisken, Sarah, Jie Luo, Nazim Haouchine, et al.. (2021). Incorporating Uncertainty Into Path Planning for Minimally Invasive Robotic Neurosurgery. IEEE Transactions on Medical Robotics and Bionics. 4(1). 5–16. 3 indexed citations
8.
Haouchine, Nazim, Parikshit Juvekar, Xin Xiong, et al.. (2021). Estimation of High Framerate Digital Subtraction Angiography Sequences at Low Radiation Dose. Lecture notes in computer science. 12906. 171–180. 5 indexed citations
9.
Haouchine, Nazim, et al.. (2021). Cortical Vessel Segmentation for Neuronavigation Using Vesselness-Enforced Deep Neural Networks. IEEE Transactions on Medical Robotics and Bionics. 4(2). 327–330. 3 indexed citations
10.
Frisken, Sarah, Parikshit Juvekar, Adomas Bunevičius, et al.. (2019). A comparison of thin-plate spline deformation and finite element modeling to compensate for brain shift during tumor resection. International Journal of Computer Assisted Radiology and Surgery. 15(1). 75–85. 8 indexed citations
11.
Toews, Matthew, Elizabeth George, Prashin Unadkat, et al.. (2019). Deformable MRI-Ultrasound registration using correlation-based attribute matching for brain shift correction: Accuracy and generality in multi-site data. NeuroImage. 202. 116094–116094. 18 indexed citations
12.
Toews, Matthew, Jie Luo, Prashin Unadkat, et al.. (2018). Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching. International Journal of Computer Assisted Radiology and Surgery. 13(10). 1525–1538. 34 indexed citations
13.
Luo, Jie, Sarah Frisken, Miaomiao Zhang, et al.. (2018). Using the variogram for vector outlier screening: application to feature-based image registration. International Journal of Computer Assisted Radiology and Surgery. 13(12). 1871–1880. 18 indexed citations
14.
Erdim, Hüseyin, et al.. (2012). High accuracy NC milling simulation using composite adaptively sampled distance fields. Computer-Aided Design. 44(6). 522–536. 48 indexed citations
15.
Lauric, Alexandra, Eric L. Miller, Sarah Frisken, & Adel M. Malek. (2009). Automated detection of intracranial aneurysms based on parent vessel 3D analysis. Medical Image Analysis. 14(2). 149–159. 38 indexed citations
16.
Perry, Ronald N., et al.. (2006). An improved representation for stroke-based fonts. 137–137. 6 indexed citations
17.
Frisken, Sarah. (2006). Designing with distance fields. 58–59. 3 indexed citations
18.
Frisken, Sarah & Ronald N. Perry. (2002). Efficient estimation of 3D Euclidean distance fields from 2D range images. 81–88. 5 indexed citations
19.
Frisken, Sarah & Ronald N. Perry. (2002). Simple and Efficient Traversal Methods for Quadtrees and Octrees. Journal of Graphics Tools. 7(3). 1–11. 104 indexed citations
20.
Perry, Ronald N. & Sarah Frisken. (2001). Kizamu. 47–56. 147 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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