M.A. Thomas

3.2k total citations
79 papers, 2.2k citations indexed

About

M.A. Thomas is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Radiation. According to data from OpenAlex, M.A. Thomas has authored 79 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Radiology, Nuclear Medicine and Imaging, 36 papers in Ophthalmology and 20 papers in Radiation. Recurrent topics in M.A. Thomas's work include Retinal Diseases and Treatments (20 papers), Advanced Radiotherapy Techniques (20 papers) and Medical Imaging Techniques and Applications (17 papers). M.A. Thomas is often cited by papers focused on Retinal Diseases and Treatments (20 papers), Advanced Radiotherapy Techniques (20 papers) and Medical Imaging Techniques and Applications (17 papers). M.A. Thomas collaborates with scholars based in United States, United Kingdom and Japan. M.A. Thomas's co-authors include Nancy S. Melberg, Henry J. Kaplan, Mitsutaka Sugita, M. Friedländer, Chandra L. Theesfeld, Stanley Chang, D A Cheresh, Marcus Fruttiger, Nancy M. Holekamp and Dean B. Burgess and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Ophthalmology and The Journal of Urology.

In The Last Decade

M.A. Thomas

74 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M.A. Thomas United States 20 1.4k 1.3k 400 215 193 79 2.2k
Léonidas Zografos Switzerland 33 2.7k 1.9× 1.4k 1.1× 1.1k 2.7× 120 0.6× 78 0.4× 166 4.0k
Nikolaos E. Bechrakis Germany 32 2.4k 1.7× 911 0.7× 764 1.9× 515 2.4× 42 0.2× 220 3.5k
Jonas A. Castelijns Netherlands 26 661 0.5× 1.2k 0.9× 328 0.8× 392 1.8× 17 0.1× 59 2.7k
Alessia Pica Switzerland 22 406 0.3× 489 0.4× 407 1.0× 433 2.0× 74 0.4× 100 2.6k
Dan S. Gombos United States 22 1.2k 0.9× 313 0.2× 457 1.1× 162 0.8× 15 0.1× 87 1.9k
H Schilling Germany 18 1.0k 0.7× 342 0.3× 596 1.5× 40 0.2× 38 0.2× 48 1.3k
Mandeep S. Sagoo United Kingdom 26 1.8k 1.3× 701 0.5× 429 1.1× 274 1.3× 7 0.0× 148 2.5k
Hideyuki Hayashi Japan 22 721 0.5× 705 0.5× 355 0.9× 34 0.2× 37 0.2× 93 1.9k
Taku Wakabayashi Japan 28 2.1k 1.5× 1.7k 1.3× 670 1.7× 278 1.3× 24 0.1× 111 2.9k
Ulrike Schneider Germany 21 555 0.4× 512 0.4× 296 0.7× 44 0.2× 16 0.1× 48 1.5k

Countries citing papers authored by M.A. Thomas

Since Specialization
Citations

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

Fields of papers citing papers by M.A. Thomas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.A. Thomas. 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 M.A. Thomas. The network helps show where M.A. Thomas may publish in the future.

Co-authorship network of co-authors of M.A. Thomas

This figure shows the co-authorship network connecting the top 25 collaborators of M.A. Thomas. A scholar is included among the top collaborators of M.A. Thomas 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 M.A. Thomas. M.A. Thomas 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.
Guo, Liang, et al.. (2025). Training a deep learning model to predict the anatomy irradiated in fluoroscopic x-ray images. International Journal of Computer Assisted Radiology and Surgery. 20(11). 2345–2353. 1 indexed citations
2.
Malone, C., Darren R. Cullinan, Maria B. Majella Doyle, et al.. (2025). Ultra-selective radiation segmentectomy for early-stage hepatocellular carcinoma. JHEP Reports. 8(1). 101636–101636.
3.
4.
Siegel, Marilyn J., et al.. (2025). Comparison of Radiation Dose and Image Quality in Pediatric Abdominopelvic Photon-Counting Versus Energy-Integrating Detector CT. Journal of Computer Assisted Tomography. 50(1). 73–80. 4 indexed citations
5.
Pan, Tinsu, M.A. Thomas, Yang Lü, & Dershan Luo. (2025). Improving data-driven gated (DDG) PET and CT registration in thoracic lesions: a comparison of AI registration and DDG CT. EJNMMI Physics. 12(1). 87–87.
6.
Duncan, James R., M.A. Thomas, & Alex Barnacle. (2025). Radiation Use in Image-Guided Interventions: Think Differently—Image Utility Over Image Quality. CardioVascular and Interventional Radiology. 48(6). 846–850.
7.
Thomas, M.A., Richard Laforest, Dario Giardinà, et al.. (2024). Addressing lung truncation in 99mTc-MAA SPECT/CT for 90Y microsphere radioembolization treatment planning. EJNMMI Physics. 11(1). 104–104. 3 indexed citations
8.
Sun, Peng, M.A. Thomas, Dershan Luo, & Tinsu Pan. (2024). New full‐counts phase‐matched data‐driven gated (DDG) PET/CT. Medical Physics. 51(7). 4646–4654. 1 indexed citations
9.
Thomas, M.A., et al.. (2022). Impact of acquisition time and misregistration with CT on data-driven gated PET. Physics in Medicine and Biology. 67(8). 85012–85012. 5 indexed citations
10.
Thomas, M.A., et al.. (2022). Exercise in the Genetic Arrhythmia Syndromes – A Review. Clinics in Sports Medicine. 41(3). 485–510. 1 indexed citations
11.
Thomas, M.A. & Tinsu Pan. (2021). Data-driven gated PET/CT: implications for lesion segmentation and quantitation. EJNMMI Physics. 8(1). 64–64. 10 indexed citations
12.
Thomas, M.A., et al.. (2020). Using prediction models to evaluate magnetic resonance image guided radiation therapy plans. Physics and Imaging in Radiation Oncology. 16. 99–102. 3 indexed citations
13.
Pan, Tinsu, Yang Lü, M.A. Thomas, Zhongxing Liao, & Dershan Luo. (2020). New Data-Driven Gated PET/CT Free of Misregistration Artifacts. International Journal of Radiation Oncology*Biology*Physics. 109(5). 1638–1646. 13 indexed citations
14.
Cassidy, Richard J., et al.. (2016). Neurovascular bundle–sparing radiotherapy for prostate cancer using MRI-CT registration: A dosimetric feasibility study. Medical dosimetry. 41(4). 339–343. 15 indexed citations
15.
Constantinescu, Cris S., M.A. Thomas, & A. Zaman. (2006). Atopic Optic Neuritis. Ocular Immunology and Inflammation. 14(2). 125–127. 9 indexed citations
16.
Busquets, Miguel, Gaurav K. Shah, David Callanan, et al.. (2003). OCULAR PHOTODYNAMIC THERAPY WITH VERTEPORFIN FOR CHOROIDAL NEOVASCULARIZATION SECONDARY TO OCULAR HISTOPLASMOSIS SYNDROME. Retina. 23(3). 299–306. 30 indexed citations
17.
Cooper, Blake, M.A. Thomas, & Nancy M. Holekamp. (2000). Open retinotomy after submacular surgery. American Journal of Ophthalmology. 130(6). 838–839. 1 indexed citations
18.
Ibanez, Hector E., Steven Bloom, R. Joseph Olk, et al.. (1994). EXTERNAL ARGON LASER CHOROIDOTOMY VERSUS NEEDLE DRAINAGE TECHNIQUE IN PRIMARY SCLERAL BUCKLE PROCEDURES. Retina. 14(4). 348–350. 13 indexed citations
19.
Thomas, M.A. & Hector E. Ibanez. (1993). Subretinal Endophotocoagulation in the Treatment of Choroidal Neovascularization. American Journal of Ophthalmology. 116(3). 279–285. 8 indexed citations
20.
Thomas, M.A. & Henry J. Kaplan. (1991). Surgical Removal of Subfoveal Neovascularization in the Presumed Ocular Histoplasmosis Syndrome. American Journal of Ophthalmology. 111(1). 1–7. 124 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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