Farzad Khalvati

3.4k total citations
88 papers, 2.0k citations indexed

About

Farzad Khalvati is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Farzad Khalvati has authored 88 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Radiology, Nuclear Medicine and Imaging, 26 papers in Pulmonary and Respiratory Medicine and 22 papers in Computer Vision and Pattern Recognition. Recurrent topics in Farzad Khalvati's work include Radiomics and Machine Learning in Medical Imaging (41 papers), Prostate Cancer Diagnosis and Treatment (16 papers) and Medical Image Segmentation Techniques (12 papers). Farzad Khalvati is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (41 papers), Prostate Cancer Diagnosis and Treatment (16 papers) and Medical Image Segmentation Techniques (12 papers). Farzad Khalvati collaborates with scholars based in Canada, Germany and United States. Farzad Khalvati's co-authors include Masoom A. Haider, Alexander Wong, Khashayar Namdar, Yucheng Zhang, Anastasia Oikonomou, Alexander Wong, Steven Gallinger, Paul J. Karanicolas, Andrew Cameron and Patrik Rogalla and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Farzad Khalvati

82 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Farzad Khalvati Canada 24 1.4k 782 482 405 392 88 2.0k
Alireza Mehrtash United States 16 1.2k 0.9× 443 0.6× 482 1.0× 328 0.8× 190 0.5× 32 1.8k
Sergios Gatidis Germany 32 1.9k 1.4× 615 0.8× 313 0.6× 527 1.3× 239 0.6× 168 3.4k
Yali Zang China 20 1.6k 1.1× 926 1.2× 411 0.9× 298 0.7× 203 0.5× 42 2.1k
Arnaldo Stanzione Italy 30 1.7k 1.2× 914 1.2× 346 0.7× 454 1.1× 260 0.7× 100 2.5k
Pretesh Patel United States 33 1.4k 1.0× 1.3k 1.7× 274 0.6× 636 1.6× 458 1.2× 180 3.1k
Lois Holloway Australia 28 2.6k 1.9× 1.5k 1.9× 448 0.9× 623 1.5× 216 0.6× 260 4.1k
Yong Yin China 21 1.1k 0.8× 799 1.0× 145 0.3× 255 0.6× 202 0.5× 195 1.8k
Yuhua Gu United States 9 2.2k 1.6× 875 1.1× 489 1.0× 671 1.7× 403 1.0× 20 2.5k
Isaac Shiri Switzerland 36 2.9k 2.0× 860 1.1× 544 1.1× 1.4k 3.5× 200 0.5× 174 3.6k
Maria Vakalopoulou France 12 1.1k 0.8× 501 0.6× 223 0.5× 249 0.6× 432 1.1× 30 1.5k

Countries citing papers authored by Farzad Khalvati

Since Specialization
Citations

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

Fields of papers citing papers by Farzad Khalvati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Farzad Khalvati

This figure shows the co-authorship network connecting the top 25 collaborators of Farzad Khalvati. A scholar is included among the top collaborators of Farzad Khalvati 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 Farzad Khalvati. Farzad Khalvati 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.
Soltanieh, Sahar, et al.. (2025). Federated Learning in Neurology: Bridging Data Privacy and Artificial Intelligence for Brain Health. Seminars in Neurology. 46(1). 38–48.
2.
Namdar, Khashayar, S. Carey, Sandra E. Fischer, et al.. (2025). Non-invasive liver fibrosis screening on CT images using radiomics. BMC Medical Imaging. 25(1). 285–285. 1 indexed citations
3.
Gong, Bo, Farzad Khalvati, Birgit Ertl‐Wagner, & Michael N. Patlas. (2024). Artificial intelligence in emergency neuroradiology: Current applications and perspectives. Diagnostic and Interventional Imaging. 106(4). 135–142. 5 indexed citations
4.
Boutet, Alexandre, Andrew Yang, Vivek Pai, et al.. (2024). Assessing the Emergence and Evolution of Artificial Intelligence and Machine Learning Research in Neuroradiology. American Journal of Neuroradiology. 45(9). 1269–1275. 4 indexed citations
5.
Bhatia, Aashim, Farzad Khalvati, & Birgit Ertl‐Wagner. (2024). Artificial Intelligence in the Future Landscape of Pediatric Neuroradiology: Opportunities and Challenges. American Journal of Neuroradiology. 45(5). 549–553. 5 indexed citations
6.
Zhou, Meng, Matthias Wagner, Uri Tabori, et al.. (2024). Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks. Computers in Biology and Medicine. 185. 109502–109502. 4 indexed citations
7.
Namdar, Khashayar, Uri Tabori, Cynthia Hawkins, et al.. (2024). Identification of Multiclass Pediatric Low-Grade Neuroepithelial Tumor Molecular Subtype with ADC MR Imaging and Machine Learning. American Journal of Neuroradiology. 45(6). 753–760. 2 indexed citations
8.
Namdar, Khashayar, Matthias Wagner, Cynthia Hawkins, et al.. (2024). Improving Deep Learning Models for Pediatric Low-Grade Glioma Tumours Molecular Subtype Identification Using MRI-based 3D Probability Distributions of Tumour Location. Canadian Association of Radiologists Journal. 76(2). 313–323. 4 indexed citations
9.
Wagner, Matthias, Liana Nobre, Khashayar Namdar, et al.. (2023). T2-FLAIR Mismatch Sign in Pediatric Low-Grade Glioma. American Journal of Neuroradiology. 44(7). 841–845. 10 indexed citations
10.
Wagner, Matthias, Khashayar Namdar, Liana Nobre, et al.. (2023). Increased confidence of radiomics facilitating pretherapeutic differentiation of BRAF-altered pediatric low-grade glioma. European Radiology. 34(4). 2772–2781. 8 indexed citations
11.
Wagner, Matthias, Khashayar Namdar, Nicolin Hainc, et al.. (2022). Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse Intrinsic Pontine Glioma. Canadian Association of Radiologists Journal. 74(1). 119–126. 21 indexed citations
12.
Wagner, Matthias, Asthik Biswas, Farzad Khalvati, et al.. (2022). Data governance functions to support responsible data stewardship in pediatric radiology research studies using artificial intelligence. Pediatric Radiology. 52(11). 2111–2119. 7 indexed citations
13.
Khalvati, Farzad, et al.. (2022). Relevance maps: A weakly supervised segmentation method for 3D brain tumours in MRIs. SHILAP Revista de lepidopterología. 2. 1061402–1061402. 3 indexed citations
14.
Khalvati, Farzad, et al.. (2022). Exploring COVID-19–Related Stressors: Topic Modeling Study. Journal of Medical Internet Research. 24(7). e37142–e37142. 16 indexed citations
15.
Wagner, Matthias, Nicolin Hainc, Farzad Khalvati, et al.. (2021). Radiomics of Pediatric Low-Grade Gliomas: Toward a Pretherapeutic Differentiation ofBRAF-Mutated andBRAF-Fused Tumors. American Journal of Neuroradiology. 42(4). 759–765. 36 indexed citations
16.
Salinas-Miranda, Emmanuel, Dominik Deniffel, Xin Dong, et al.. (2021). Prognostic value of early changes in CT-measured body composition in patients receiving chemotherapy for unresectable pancreatic cancer. European Radiology. 31(11). 8662–8670. 28 indexed citations
17.
Wagner, Matthias, et al.. (2021). Radiomics, machine learning, and artificial intelligence—what the neuroradiologist needs to know. Neuroradiology. 63(12). 1957–1967. 104 indexed citations
18.
Oikonomou, Anastasia, Farzad Khalvati, Pascal N. Tyrrell, et al.. (2018). Radiomics analysis at PET/CT contributes to prognosis of recurrence and survival in lung cancer treated with stereotactic body radiotherapy. Scientific Reports. 8(1). 4003–4003. 119 indexed citations
19.
Khalvati, Farzad, Alexander Wong, & Masoom A. Haider. (2015). Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models. BMC Medical Imaging. 15(1). 27–27. 129 indexed citations
20.
Khalvati, Farzad, Aryan Salmanpour, Shahryar Rahnamayan, Masoom A. Haider, & Hamid R. Tizhoosh. (2015). Sequential Registration-Based Segmentation of the Prostate Gland in MR Image Volumes. Journal of Digital Imaging. 29(2). 254–263. 8 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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