William T. Katz

3.3k total citations
15 papers, 134 citations indexed

About

William T. Katz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, William T. Katz has authored 15 papers receiving a total of 134 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in William T. Katz's work include Medical Image Segmentation Techniques (7 papers), Neural Networks and Applications (3 papers) and AI in cancer detection (3 papers). William T. Katz is often cited by papers focused on Medical Image Segmentation Techniques (7 papers), Neural Networks and Applications (3 papers) and AI in cancer detection (3 papers). William T. Katz collaborates with scholars based in United States, Australia and Italy. William T. Katz's co-authors include Michael Merickel, John W. Snell, Stephen M. Plaza, Ryan Kennedy, Juan Nunez-Iglesias, Jacquelyn Blackstone, Michael G. Pinette, Angelina Cartin, John C. Goble and John Snell and has published in prestigious journals such as Methods in enzymology on CD-ROM/Methods in enzymology, American Journal of Obstetrics and Gynecology and Frontiers in Neural Circuits.

In The Last Decade

William T. Katz

13 papers receiving 125 citations

Peers

William T. Katz
Zelin Zang China
Worku Jifara China
Ryan Stables United Kingdom
Oana G. Cula United States
Siliang Ma China
Tiago Gonçalves Portugal
Wei-Yu Chen Taiwan
Mustafa Gökhan Uzunbaş United States
Wen Wu China
Zelin Zang China
William T. Katz
Citations per year, relative to William T. Katz William T. Katz (= 1×) peers Zelin Zang

Countries citing papers authored by William T. Katz

Since Specialization
Citations

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

Fields of papers citing papers by William T. Katz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William T. Katz

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

All Works

15 of 15 papers shown
1.
Faletra, Francesco F., Laura Anna Leo, Leyla Elif Sade, et al.. (2024). The Key Role of 3D TEE in Assessing the Morphology of Degenerative Mitral Valve Regurgitation. Journal of Cardiovascular Development and Disease. 11(11). 342–342. 1 indexed citations
2.
Katz, William T. & Stephen M. Plaza. (2019). DVID: Distributed Versioned Image-Oriented Dataservice. Frontiers in Neural Circuits. 13. 5–5. 13 indexed citations
3.
Nunez-Iglesias, Juan, et al.. (2014). Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages. Frontiers in Neuroinformatics. 8. 34–34. 29 indexed citations
4.
Katz, William T. & Michael Merickel. (2005). Automated Segmentation of 3-D Magnetic Resonance Images of the Head. 297–298.
5.
Katz, William T. & Michael Merickel. (2005). Aorta Detection In Magnetic Resonance Images Using Multiple Artificial Neural Networks. 1302–1303. 1 indexed citations
6.
Katz, William T., et al.. (2002). Experience-based learning experiments using Go-Moku. 1405–1410. 4 indexed citations
7.
Pinette, Michael G., et al.. (2001). Successful planned pregnancy following endometrial ablation with the YAG laser. American Journal of Obstetrics and Gynecology. 185(1). 242–243. 13 indexed citations
8.
Snell, John W., et al.. (1995). <title>Three-dimensional stereotactic neurosurgical planner/simulator</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2431. 110–118. 1 indexed citations
9.
Goble, John C., John W. Snell, & William T. Katz. (1994). Semiautomatic Model-Based Segmentation of the Brain from Magnetic Resonance Images. 1 indexed citations
10.
Katz, William T., Michael Merickel, John C. Goble, Neal F. Kassell, & James R. Brookeman. (1993). <title>Segmentation of the brain from 3D magnetic resonance images of the head</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1898. 809–819. 3 indexed citations
11.
Katz, William T., John W. Snell, & Michael Merickel. (1992). [29] Artificial neural networks. Methods in enzymology on CD-ROM/Methods in enzymology. 210. 610–636. 53 indexed citations
12.
Katz, William T., Michael Merickel, Rees Cosgrove, Neal F. Kassell, & James R. Brookeman. (1992). Segmentation of the brain from 3-D magnetic resonance images of the head. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 1920–1921. 3 indexed citations
13.
Merickel, Michael, et al.. (1992). The use of a priori model based information to guide segmentation and classification of MR images. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 60. 2212–2213. 1 indexed citations
14.
Merickel, Michael, et al.. (1992). The use of a Priori model based information to guide segmentation and classification of MR images. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 60. 2785–2786. 1 indexed citations
15.
Katz, William T., et al.. (1989). Translation-invariant aorta segmentation from magnetic resonance images. 327–333 vol.1. 10 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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