Evan Calabrese

3.5k total citations
60 papers, 1.8k citations indexed

About

Evan Calabrese is a scholar working on Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health and Cognitive Neuroscience. According to data from OpenAlex, Evan Calabrese has authored 60 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Pediatrics, Perinatology and Child Health and 9 papers in Cognitive Neuroscience. Recurrent topics in Evan Calabrese's work include Advanced Neuroimaging Techniques and Applications (30 papers), Advanced MRI Techniques and Applications (20 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Evan Calabrese is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (30 papers), Advanced MRI Techniques and Applications (20 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Evan Calabrese collaborates with scholars based in United States, France and Australia. Evan Calabrese's co-authors include G. Allan Johnson, Alexandra Badea, Jan G. Bjaalie, Trygve B. Leergaard, Eszter A. Papp, Javier Villanueva-Meyer, Charles Watson, Soonmee Cha, Gary P. Cofer and Yi Qi and has published in prestigious journals such as NeuroImage, JNCI Journal of the National Cancer Institute and Scientific Reports.

In The Last Decade

Evan Calabrese

59 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Evan Calabrese United States	21	1.0k	500	261	229	199	60	1.8k
Shingo Kakeda Japan	24	1.0k 1.0×	459 0.9×	387 1.5×	270 1.2×	74 0.4×	117	2.1k
Domenico Aquino Italy	19	731 0.7×	471 0.9×	308 1.2×	173 0.8×	68 0.3×	63	1.7k
Francesca B. Pizzini Italy	31	901 0.9×	519 1.0×	533 2.0×	201 0.9×	169 0.8×	105	2.8k
Yujin Zhang China	21	881 0.9×	822 1.6×	188 0.7×	103 0.4×	379 1.9×	38	2.3k
Kouhei Kamiya Japan	24	1.0k 1.0×	231 0.5×	494 1.9×	384 1.7×	244 1.2×	73	1.7k
Roy Riascos United States	27	462 0.5×	221 0.4×	378 1.4×	232 1.0×	141 0.7×	129	2.3k
Yibao Wang China	15	1.3k 1.3×	773 1.5×	248 1.0×	124 0.5×	268 1.3×	30	1.8k
Arash Kamali United States	21	1.0k 1.0×	596 1.2×	224 0.9×	148 0.6×	372 1.9×	60	1.6k
Ken Sakaie United States	25	1.1k 1.1×	512 1.0×	364 1.4×	268 1.2×	200 1.0×	82	2.1k
Edward S. Hui Hong Kong	26	1.5k 1.5×	261 0.5×	295 1.1×	218 1.0×	228 1.1×	77	2.5k

Countries citing papers authored by Evan Calabrese

Since Specialization

Citations

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

Fields of papers citing papers by Evan Calabrese

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Evan Calabrese

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

All Works

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20 of 20 papers shown

Jabal, Mohamed Sobhi, Jikai Zhang, Ayush Jain, et al.. (2025). Open-Weight Language Models and Retrieval-Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters. Radiology Artificial Intelligence. 7(3). e240551–e240551. 2 indexed citations

Jackson, Joshua, Eric W. Sankey, Ethan Srinivasan, et al.. (2024). NIMG-05. ARTIFICIAL INTELLIGENCE-BASED RESPONSE ASSESSMENT FOR PATIENTS RECEIVING LASER INTERSTITIAL THERMAL THERAPY. Neuro-Oncology. 26(Supplement_8). viii195–viii195. 1 indexed citations

Chen, Joshua, Yi Li, Gunvant Chaudhari, et al.. (2024). Automated neonatal nnU-Net brain MRI extractor trained on a large multi-institutional dataset. Scientific Reports. 14(1). 4583–4583. 6 indexed citations

Zhang, Jikai, et al.. (2024). Development and Evaluation of Automated Artificial Intelligence–Based Brain Tumor Response Assessment in Patients with Glioblastoma. American Journal of Neuroradiology. 46(5). 990–998. 1 indexed citations

Rudie, Jeffrey D., David Weiß, Evan Calabrese, et al.. (2024). The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset. Radiology Artificial Intelligence. 6(2). e230126–e230126. 10 indexed citations

Roth, Patrick, David Capper, Evan Calabrese, Lia M. Halasz, & Asgeir Store Jakola. (2024). Role of the tumor board when prescribing mutant isocitrate dehydrogenase inhibitors to patients with isocitrate dehydrogenase-mutant glioma. Neuro-Oncology Practice. 12(Supplement_1). i29–i37.

Walsh, Kyle M., Mackenzie Price, David R. Raleigh, et al.. (2024). Grade-stratified meningioma risk among individuals who are non-Hispanic Black and interactions with male sex. JNCI Journal of the National Cancer Institute. 117(2). 366–374. 1 indexed citations

Isikbay, Masis, M. Travis Caton, Jared Narvid, et al.. (2024). Deep learning segmentation-based bone removal from computed tomography of the brain improves subdural hematoma detection. Journal of Neuroradiology. 52(1). 101231–101231. 1 indexed citations

Calabrese, Evan, Yvonne W. Wu, Jessica L. Wisnowski, et al.. (2023). Correlating Quantitative MRI-based Apparent Diffusion Coefficient Metrics with 24-month Neurodevelopmental Outcomes in Neonates from the HEAL Trial. Radiology. 308(3). e223262–e223262. 7 indexed citations

10.

Isikbay, Masis, M. Travis Caton, & Evan Calabrese. (2023). A Deep Learning Approach for Automated Bone Removal from Computed Tomography Angiography of the Brain. Journal of Digital Imaging. 36(3). 964–972. 3 indexed citations

11.

Rudie, Jeffrey D., Evan Calabrese, David Weiß, et al.. (2022). Longitudinal Assessment of Posttreatment Diffuse Glioma Tissue Volumes with Three-dimensional Convolutional Neural Networks. Radiology Artificial Intelligence. 4(5). e210243–e210243. 14 indexed citations

12.

Calabrese, Evan, John Mongan, Kimberly M. Ray, et al.. (2022). Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer. Radiology. 306(3). e213199–e213199. 25 indexed citations

13.

Calabrese, Evan, Jeffrey D. Rudie, Andreas M. Rauschecker, et al.. (2022). Combining radiomics and deep convolutional neural network features from preoperative MRI for predicting clinically relevant genetic biomarkers in glioblastoma. Neuro-Oncology Advances. 4(1). 56 indexed citations

14.

Rauschecker, Andreas M., Michael Tran Duong, David Weiß, et al.. (2021). Interinstitutional Portability of a Deep Learning Brain MRI Lesion Segmentation Algorithm. Radiology Artificial Intelligence. 4(1). e200152–e200152. 16 indexed citations

15.

Rockcastle, Siobhan, et al.. (2021). Comparing perceptions of a dimmable LED lighting system between a real space and a virtual reality display. Lighting Research & Technology. 53(8). 701–725. 37 indexed citations

16.

Callen, Andrew L., Sara M. Dupont, Jason F. Talbott, et al.. (2020). The regional pattern of abnormal cerebrovascular reactivity in HIV-infected, virally suppressed women. Journal of NeuroVirology. 26(5). 734–742. 11 indexed citations

17.

Ketcha, Michael D., Alexandra Badea, Evan Calabrese, et al.. (2018). Connectome smoothing via low-rank approximations. IEEE Transactions on Medical Imaging. 38(6). 1446–1456. 17 indexed citations

18.

Calabrese, Evan, Syed M. Adil, Gary P. Cofer, et al.. (2018). Postmortem diffusion MRI of the entire human spinal cord at microscopic resolution. NeuroImage Clinical. 18. 963–971. 26 indexed citations

19.

Gyengési, Erika, et al.. (2013). Semi-automated 3D segmentation of major tracts in the rat brain: comparing DTI with standard histological methods. Brain Structure and Function. 219(2). 539–550. 18 indexed citations

20.

Calabrese, Evan, G. Allan Johnson, & Charles Watson. (2012). An ontology-based segmentation scheme for tracking postnatal changes in the developing rodent brain with MRI. NeuroImage. 67. 375–384. 17 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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