T.J. Hebert

2.8k total citations · 1 hit paper
49 papers, 2.1k citations indexed

About

T.J. Hebert is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, T.J. Hebert has authored 49 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Computer Vision and Pattern Recognition and 11 papers in Biomedical Engineering. Recurrent topics in T.J. Hebert's work include Medical Imaging Techniques and Applications (18 papers), Medical Image Segmentation Techniques (10 papers) and Advanced X-ray and CT Imaging (10 papers). T.J. Hebert is often cited by papers focused on Medical Imaging Techniques and Applications (18 papers), Medical Image Segmentation Techniques (10 papers) and Advanced X-ray and CT Imaging (10 papers). T.J. Hebert collaborates with scholars based in United States, Germany and Canada. T.J. Hebert's co-authors include Richard M. Leahy, Austin Roorda, Fernando Romero‐Borja, Melanie C. W. Campbell, Hope M Queener, William J. Donnelly, R. M. Macfarlane, Reinhold Wannemacher, W. Lenth and Sucharita Gopal and has published in prestigious journals such as The Journal of Chemical Physics, Applied Physics Letters and Brain Research.

In The Last Decade

T.J. Hebert

47 papers receiving 2.0k citations

Hit Papers

Adaptive optics scanning laser ophthalmoscopy 2002 2026 2010 2018 2002 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T.J. Hebert United States 15 983 645 506 355 314 49 2.1k
Scot S. Olivier United States 19 431 0.4× 798 1.2× 596 1.2× 123 0.3× 212 0.7× 126 2.1k
Federica Villa Italy 30 597 0.6× 821 1.3× 413 0.8× 110 0.3× 54 0.2× 165 3.4k
C. E. Campbell United States 28 325 0.3× 253 0.4× 293 0.6× 102 0.3× 359 1.1× 127 2.7k
Claudio Bruschini Switzerland 25 417 0.4× 512 0.8× 152 0.3× 70 0.2× 14 0.0× 147 2.2k
Erez N. Ribak Israel 19 97 0.1× 300 0.5× 110 0.2× 323 0.9× 52 0.2× 108 1.3k
Alberto Tosi Italy 41 1.7k 1.7× 1.7k 2.6× 798 1.6× 113 0.3× 9 0.0× 233 5.7k
Phillip Sutton Australia 3 154 0.2× 1.1k 1.7× 47 0.1× 801 2.3× 41 0.1× 6 3.5k
H. P. Urbach Netherlands 34 101 0.1× 2.0k 3.0× 17 0.0× 165 0.5× 125 0.4× 241 4.1k
A. H. Greenaway United Kingdom 25 87 0.1× 467 0.7× 28 0.1× 395 1.1× 17 0.1× 104 2.0k
Franco Zappa Italy 45 1.5k 1.5× 1.4k 2.2× 1.1k 2.2× 125 0.4× 2 0.0× 251 7.2k

Countries citing papers authored by T.J. Hebert

Since Specialization
Citations

This map shows the geographic impact of T.J. Hebert'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 T.J. Hebert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.J. Hebert more than expected).

Fields of papers citing papers by T.J. Hebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T.J. Hebert. 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 T.J. Hebert. The network helps show where T.J. Hebert may publish in the future.

Co-authorship network of co-authors of T.J. Hebert

This figure shows the co-authorship network connecting the top 25 collaborators of T.J. Hebert. A scholar is included among the top collaborators of T.J. Hebert 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 T.J. Hebert. T.J. Hebert 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.
Romero‐Borja, Fernando, et al.. (2005). Optical slicing of human retinal tissue in vivo with the adaptive optics scanning laser ophthalmoscope. Applied Optics. 44(19). 4032–4032. 54 indexed citations
2.
Hebert, T.J.. (2003). A union of deterministic and stochastic methods for image reconstruction. IEEE Conference on Nuclear Science Symposium and Medical Imaging. 1117–1119. 1 indexed citations
3.
Hebert, T.J., et al.. (1998). Bayesian pixel classification using spatially variant finite mixtures and the generalized EM algorithm. IEEE Transactions on Image Processing. 7(7). 1014–1028. 152 indexed citations
4.
Gopal, Sucharita & T.J. Hebert. (1998). Priors and constraints in Bayesian image segmentation based on finite mixtures. IEEE Transactions on Nuclear Science. 45(4). 2113–2118. 1 indexed citations
5.
Hebert, T.J., et al.. (1995). Inhibition of lordosis in female hamsters and rats by 8-OH-DPAT treatment. Physiology & Behavior. 57(3). 523–527. 10 indexed citations
6.
Hebert, T.J., Sucharita Gopal, & Paul H. Murphy. (1995). A fully automated optimization algorithm for determining the 3-D patient contour from photo-peak projection data in SPECT. IEEE Transactions on Medical Imaging. 14(1). 122–131. 11 indexed citations
7.
Hebert, T.J., et al.. (1995). Androgenic-anabolic steroids modify β-endorphin immunoreactivity in the rat brain. Brain Research. 669(2). 255–262. 31 indexed citations
8.
Hebert, T.J. & Keming Lu. (1995). Expectation-maximization algorithms, null spaces, and MAP image restoration. IEEE Transactions on Image Processing. 4(8). 1084–1095. 13 indexed citations
9.
Hebert, T.J., et al.. (1994). Maximum Likelihood Preprocessing for Improved Filtered Back-Projection Reconstructions. Journal of Computer Assisted Tomography. 18(2). 283–291. 3 indexed citations
10.
Hebert, T.J., et al.. (1994). Effects of hormonal treatment and history on scopolamine inhibition of lordosis. Physiology & Behavior. 56(5). 835–839. 8 indexed citations
11.
Gopal, Sucharita & T.J. Hebert. (1994). Pre-reconstruction restoration of SPECT projection images by a neural network. IEEE Transactions on Nuclear Science. 41(4). 1620–1625. 2 indexed citations
12.
Hebert, T.J. & Sucharita Gopal. (1992). The GEM MAP algorithm with 3-D SPECT system response. IEEE Transactions on Medical Imaging. 11(1). 81–90. 17 indexed citations
13.
Hebert, T.J., et al.. (1992). Generation of SnO by photoproduction and ‐mobilization of oxygen atoms in krypton matrices doped with N2O and Sn. Berichte der Bunsengesellschaft für physikalische Chemie. 96(8). 1032–1037. 5 indexed citations
14.
Hebert, T.J., R. M. Macfarlane, & W. Lenth. (1991). Visible CW-pumped upconversion lasers. 386–393. 1 indexed citations
15.
Leahy, Richard M., et al.. (1991). Applications of Markov random fields in medical imaging.. PubMed. 363. 1–14. 17 indexed citations
16.
Macfarlane, R. M., Reinhold Wannemacher, T.J. Hebert, & W. Lenth. (1990). Upconversion laser action at 450.2 and 483.0 nm in Tm:YLiF 4. Conference on Lasers and Electro-Optics. 1 indexed citations
17.
Hebert, T.J., et al.. (1990). Time-resolved fluorescence spectroscopy of matrix-isolated silver atoms after pulsed excitation of inner-shell transitions. The Journal of Chemical Physics. 92(3). 1575–1580. 7 indexed citations
18.
Hebert, T.J., Reinhold Wannemacher, W. Lenth, & R. M. Macfarlane. (1990). Blue and green cw upconversion lasing in Er:YLiF4. Applied Physics Letters. 57(17). 1727–1729. 126 indexed citations
19.
Hebert, T.J., et al.. (1989). Energy transfer in silver-doped rare gas matrices. The Journal of Chemical Physics. 91(3). 1417–1422. 16 indexed citations
20.
Hebert, T.J. & Richard M. Leahy. (1989). A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors. IEEE Transactions on Medical Imaging. 8(2). 194–202. 443 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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