Golnoosh Samei

511 total citations
17 papers, 227 citations indexed

About

Golnoosh Samei is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Golnoosh Samei has authored 17 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Biomedical Engineering and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Golnoosh Samei's work include Advanced Radiotherapy Techniques (6 papers), Medical Imaging and Analysis (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Golnoosh Samei is often cited by papers focused on Advanced Radiotherapy Techniques (6 papers), Medical Imaging and Analysis (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Golnoosh Samei collaborates with scholars based in Switzerland, Canada and Germany. Golnoosh Samei's co-authors include Septimiu E. Salcudean, Claudia Kesch, Christine Tanner, Gábor Székely, Davood Karimi, Guy Nir, Julio Lobo, Peter C. Black, Omid Mohareri and S. Sara Mahdavi and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis and Lecture notes in computer science.

In The Last Decade

Golnoosh Samei

17 papers receiving 225 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Golnoosh Samei Switzerland 8 94 92 87 70 53 17 227
Igor Gyacskov Canada 9 141 1.5× 109 1.2× 132 1.5× 141 2.0× 41 0.8× 18 328
Ruida Cheng United States 9 94 1.0× 106 1.2× 143 1.6× 95 1.4× 34 0.6× 14 309
Heinrich Schulz Germany 7 77 0.8× 134 1.5× 103 1.2× 47 0.7× 57 1.1× 20 326
Julio Lobo Canada 10 51 0.5× 151 1.6× 154 1.8× 119 1.7× 109 2.1× 31 312
Tsuicheng Chiu United States 9 70 0.7× 172 1.9× 135 1.6× 49 0.7× 106 2.0× 29 317
Junko Tokuno Japan 11 86 0.9× 54 0.6× 39 0.4× 102 1.5× 17 0.3× 37 262
Maria Antico Australia 9 57 0.6× 102 1.1× 98 1.1× 39 0.6× 31 0.6× 25 262
Hortense A. Kirişli Netherlands 12 130 1.4× 304 3.3× 104 1.2× 55 0.8× 35 0.7× 20 442
Rongpin Wang China 9 77 0.8× 278 3.0× 85 1.0× 156 2.2× 13 0.2× 14 382
Kei Ichiji Japan 10 40 0.4× 195 2.1× 59 0.7× 77 1.1× 111 2.1× 47 298

Countries citing papers authored by Golnoosh Samei

Since Specialization
Citations

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

Fields of papers citing papers by Golnoosh Samei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Golnoosh Samei

This figure shows the co-authorship network connecting the top 25 collaborators of Golnoosh Samei. A scholar is included among the top collaborators of Golnoosh Samei 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 Golnoosh Samei. Golnoosh Samei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Mahdavi, S. Sara, Golnoosh Samei, Julio Lobo, et al.. (2020). Prostate brachytherapy intraoperative dosimetry using a combination of radiographic seed localization with a C-arm and deformed ultrasound prostate contours. Brachytherapy. 19(5). 589–598. 3 indexed citations
2.
Samei, Golnoosh, Claudia Kesch, Julio Lobo, et al.. (2019). A partial augmented reality system with live ultrasound and registered preoperative MRI for guiding robot-assisted radical prostatectomy. Medical Image Analysis. 60. 101588–101588. 35 indexed citations
3.
Mathur, Prateek, et al.. (2019). On the feasibility of transperineal 3D ultrasound image guidance for robotic radical prostatectomy. International Journal of Computer Assisted Radiology and Surgery. 14(6). 923–931. 7 indexed citations
4.
Samei, Golnoosh, Kwt Tsang, Julio Lobo, et al.. (2018). Fused MRI-ultrasound Augmented-Reality Guidance System For Robot-Assisted Laparoscopic Radical Prostatectomy. 79–80. 4 indexed citations
5.
Samei, Golnoosh, Davood Karimi, Claudia Kesch, et al.. (2018). Prostate segmentation in transrectal ultrasound using magnetic resonance imaging priors. International Journal of Computer Assisted Radiology and Surgery. 13(6). 749–757. 24 indexed citations
6.
Karimi, Davood, Golnoosh Samei, Claudia Kesch, Guy Nir, & Septimiu E. Salcudean. (2018). Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models. International Journal of Computer Assisted Radiology and Surgery. 13(8). 1211–1219. 67 indexed citations
7.
Samei, Golnoosh, Orçun Göksel, Julio Lobo, et al.. (2018). Real-Time FEM-Based Registration of 3-D to 2.5-D Transrectal Ultrasound Images. IEEE Transactions on Medical Imaging. 37(8). 1877–1886. 20 indexed citations
8.
Tanner, Christine, Y. Zur, Golnoosh Samei, et al.. (2016). In vivo validation of spatio-temporal liver motion prediction from motion tracked on MR thermometry images. International Journal of Computer Assisted Radiology and Surgery. 11(6). 1143–1152. 13 indexed citations
9.
Tanner, Christine, Minglei Yang, Golnoosh Samei, & Gábor Székely. (2016). Influence of inter-subject correspondences on liver motion predictions from population models. 44. 286–289. 3 indexed citations
10.
Tanner, Christine, Golnoosh Samei, & Gábor Székely. (2015). Robust exemplar model of respiratory liver motion and individualization using an additional breath-hold image. 44. 1576–1579. 2 indexed citations
11.
Samei, Golnoosh, Christine Tanner, & Gábor Székely. (2014). RIB detection in MR images using shape priors and appearance models. 798–801. 1 indexed citations
12.
Samei, Golnoosh, Gábor Székely, & Christine Tanner. (2014). Detection and Registration of Ribs in MRI Using Geometric and Appearance Models. Lecture notes in computer science. 17(Pt 1). 706–713. 1 indexed citations
13.
Tanner, Christine, Golnoosh Samei, & Gábor Székely. (2014). Improved Reconstruction of 4D-MR Images by Motion Predictions. Lecture notes in computer science. 17(Pt 1). 146–153. 4 indexed citations
14.
Tanner, Christine, Golnoosh Samei, & Gábor Székely. (2013). Investigating anisotropic diffusion for the registration of abdominal MR images. Zenodo (CERN European Organization for Nuclear Research). 484–487. 5 indexed citations
15.
Samei, Golnoosh, et al.. (2013). Population based modeling of respiratory lung motion and prediction from partial information. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8669. 86690U–86690U. 14 indexed citations
16.
Tanner, Christine, et al.. (2012). Review on 4D Models for Organ Motion Compensation. Critical Reviews in Biomedical Engineering. 40(2). 135–154. 21 indexed citations
17.
Samei, Golnoosh, et al.. (2008). Border preserving skin lesion segmentation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6915. 69153A–69153A. 3 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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