Dewey Odhner

2.1k total citations
86 papers, 1.5k citations indexed

About

Dewey Odhner is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Dewey Odhner has authored 86 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Computer Vision and Pattern Recognition, 35 papers in Radiology, Nuclear Medicine and Imaging and 31 papers in Biomedical Engineering. Recurrent topics in Dewey Odhner's work include Medical Image Segmentation Techniques (43 papers), Medical Imaging and Analysis (23 papers) and Radiomics and Machine Learning in Medical Imaging (18 papers). Dewey Odhner is often cited by papers focused on Medical Image Segmentation Techniques (43 papers), Medical Imaging and Analysis (23 papers) and Radiomics and Machine Learning in Medical Imaging (18 papers). Dewey Odhner collaborates with scholars based in United States, China and France. Dewey Odhner's co-authors include Jayaram K. Udupa, Punam K. Saha, Gábor T. Herman, Hirsch Be, Drew A. Torigian, Yubing Tong, George J. Grevera, Gul Moonis, David B. Hackney and Jian-Guo Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Spine.

In The Last Decade

Dewey Odhner

81 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dewey Odhner United States 20 768 497 429 190 183 86 1.5k
F. Pernuš Slovenia 13 813 1.1× 584 1.2× 511 1.2× 30 0.2× 55 0.3× 31 1.5k
Tobias Heimann Germany 19 988 1.3× 548 1.1× 557 1.3× 38 0.2× 36 0.2× 44 2.0k
A. Nabavi Germany 13 463 0.6× 843 1.7× 229 0.5× 60 0.3× 60 0.3× 28 1.4k
Rhodri Davies United Kingdom 19 706 0.9× 428 0.9× 341 0.8× 31 0.2× 36 0.2× 65 1.5k
Hans Lamecker Germany 20 522 0.7× 271 0.5× 486 1.1× 30 0.2× 37 0.2× 55 1.2k
Cristian Lorenz Germany 18 472 0.6× 421 0.8× 656 1.5× 18 0.1× 80 0.4× 65 1.3k
Stefan Wesarg Germany 20 376 0.5× 398 0.8× 556 1.3× 43 0.2× 132 0.7× 92 1.1k
Mathieu De Craene Spain 21 361 0.5× 852 1.7× 351 0.8× 15 0.1× 64 0.3× 82 1.6k
B. Likar Slovenia 12 1.1k 1.4× 781 1.6× 487 1.1× 31 0.2× 10 0.1× 20 1.9k
Philipp G. Batchelor United Kingdom 3 872 1.1× 732 1.5× 363 0.8× 27 0.1× 10 0.1× 4 1.5k

Countries citing papers authored by Dewey Odhner

Since Specialization
Citations

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

Fields of papers citing papers by Dewey Odhner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dewey Odhner

This figure shows the co-authorship network connecting the top 25 collaborators of Dewey Odhner. A scholar is included among the top collaborators of Dewey Odhner 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 Dewey Odhner. Dewey Odhner 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.
Ilesanmi, Ademola E., et al.. (2023). Auto-segmentation of thoracic brachial plexuses for radiation therapy planning. PubMed. 12466. 75–75.
2.
Jin, Chao, Jayaram K. Udupa, Liming Zhao, et al.. (2022). Object recognition in medical images via anatomy-guided deep learning. Medical Image Analysis. 81. 102527–102527. 20 indexed citations
3.
Li, Jieyu, Jayaram K. Udupa, Yubing Tong, Dewey Odhner, & Drew A. Torigian. (2021). Anatomy recognition in CT images of head and neck region via precision atlases. PubMed. 11596. 108–108. 1 indexed citations
4.
5.
Tong, Yubing, Jayaram K. Udupa, Xingyu Wu, et al.. (2018). Hierarchical model-based object localization for auto-contouring in head and neck radiation therapy planning. PubMed. 10578. 73–73. 7 indexed citations
6.
7.
Tong, Yubing, Jayaram K. Udupa, Drew A. Torigian, et al.. (2017). Chest Fat Quantification via CT Based on Standardized Anatomy Space in Adult Lung Transplant Candidates. PLoS ONE. 12(1). e0168932–e0168932. 27 indexed citations
8.
Sun, Kaiqiong, Jayaram K. Udupa, Dewey Odhner, et al.. (2016). Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration. Medical Physics. 43(3). 1487–1500. 10 indexed citations
9.
Wang, Huiqian, Jayaram K. Udupa, Dewey Odhner, et al.. (2016). Automatic anatomy recognition in whole-body PET/CT images. Medical Physics. 43(1). 613–629. 17 indexed citations
10.
Liu, Jiamin, Jayaram K. Udupa, Punam K. Saha, et al.. (2008). Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis. Medical Physics. 35(8). 3637–3649. 17 indexed citations
11.
Grevera, George J., et al.. (2007). CAVASS: A Computer-Assisted Visualization and Analysis Software System. Journal of Digital Imaging. 20(S1). 101–118. 46 indexed citations
12.
Liu, Jian-Guo, Jayaram K. Udupa, Dewey Odhner, David B. Hackney, & Gul Moonis. (2005). A system for brain tumor volume estimation via MR imaging and fuzzy connectedness. Computerized Medical Imaging and Graphics. 29(1). 21–34. 98 indexed citations
13.
Ringleb, Stacie I., Jayaram K. Udupa, Sorin Siegler, et al.. (2005). The effect of ankle ligament damage and surgical reconstructions on the mechanics of the ankle and subtalar joints revealed by three‐dimensional stress MRI. Journal of Orthopaedic Research®. 23(4). 743–749. 40 indexed citations
14.
Siegler, Sorin, Jayaram K. Udupa, Stacie I. Ringleb, et al.. (2004). Mechanics of the ankle and subtalar joints revealed through a 3D quasi-static stress MRI technique. Journal of Biomechanics. 38(3). 567–578. 81 indexed citations
15.
Udupa, Jayaram K., et al.. (2003). 3DVIEWNIX-AVS: a software package for the separate visualization of arteries and veins in CE-MRA images. Computerized Medical Imaging and Graphics. 27(5). 351–362. 11 indexed citations
16.
Stindel, Éric, Jayaram K. Udupa, Hirsch Be, & Dewey Odhner. (2001). An in vivo analysis of the motion of the peri-talar joint complex based on MR imaging. IEEE Transactions on Biomedical Engineering. 48(2). 236–247. 19 indexed citations
17.
Stindel, Éric, Jayaram K. Udupa, Hirsch Be, Dewey Odhner, & Christine Couture. (1999). 3D MR image analysis of the morphology of the rear foot: application to classification of bones. Computerized Medical Imaging and Graphics. 23(2). 75–83. 41 indexed citations
18.
Stindel, Éric, Jayaram K. Udupa, Hirsch Be, & Dewey Odhner. (1999). A characterization of the geometric architecture of the peritalar joint complex via MRI, an aid to classification of foot type. IEEE Transactions on Medical Imaging. 18(9). 753–763. 26 indexed citations
19.
20.
Herman, Gábor T. & Dewey Odhner. (1991). Performance evaluation of an iterative image reconstruction algorithm for positron emission tomography. IEEE Transactions on Medical Imaging. 10(3). 336–346. 83 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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