John S. H. Baxter

933 total citations
68 papers, 569 citations indexed

About

John S. H. Baxter is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, John S. H. Baxter has authored 68 papers receiving a total of 569 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 19 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Neurology. Recurrent topics in John S. H. Baxter's work include Medical Image Segmentation Techniques (14 papers), Neurological disorders and treatments (10 papers) and Medical Imaging Techniques and Applications (9 papers). John S. H. Baxter is often cited by papers focused on Medical Image Segmentation Techniques (14 papers), Neurological disorders and treatments (10 papers) and Medical Imaging Techniques and Applications (9 papers). John S. H. Baxter collaborates with scholars based in Canada, France and United States. John S. H. Baxter's co-authors include Terry M. Peters, Elvis C. S. Chen, A. Jonathan McLeod, Pierre Jannin, Ali R. Khan, Roy Eagleson, Sandrine de Ribaupierre, Claire Haegelen, Martin Rajchl and Oğuz Akın and has published in prestigious journals such as SHILAP Revista de lepidopterología, Radiology and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

John S. H. Baxter

59 papers receiving 554 citations

Peers

John S. H. Baxter

CVPR

RNMI

SURGE

Kang‐Ping Lin Taiwan

Hong‐Seng Gan Malaysia

David G. Gobbi Canada

Cristián Tejos Chile

Lichi Zhang China

Dinggang Shen United States

Charles Huang United States

Norihiro Sugita Japan

Alireza Akhondi‐Asl United States

Brent C. Munsell United States

Kang‐Ping Lin Taiwan

John S. H. Baxter

98 ×0.5

CVPR

246 ×1.3

RNMI

158 ×1.4

60 ×0.6

SURGE

46 ×0.7

Citations per year, relative to John S. H. Baxter John S. H. Baxter (= 1×) peers Kang‐Ping Lin

Countries citing papers authored by John S. H. Baxter

Since Specialization

Citations

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

Fields of papers citing papers by John S. H. Baxter

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John S. H. Baxter. 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 John S. H. Baxter. The network helps show where John S. H. Baxter may publish in the future.

Co-authorship network of co-authors of John S. H. Baxter

This figure shows the co-authorship network connecting the top 25 collaborators of John S. H. Baxter. A scholar is included among the top collaborators of John S. H. Baxter 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 John S. H. Baxter. John S. H. Baxter 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

Baxter, John S. H. & Roy Eagleson. (2025). Exploring the values underlying machine learning research in medical image analysis. Medical Image Analysis. 102. 103494–103494. 2 indexed citations

Jannin, Pierre, et al.. (2024). Generalisation capabilities of machine-learning algorithms for the detection of the subthalamic nucleus in micro-electrode recordings. International Journal of Computer Assisted Radiology and Surgery. 19(12). 2445–2451. 2 indexed citations

Migliaccio, Raffaella, et al.. (2024). Non-local diffusion-based biomarkers in patients with cocaine use disorder. SHILAP Revista de lepidopterología. 4(2). 100202–100202. 1 indexed citations

Migliaccio, Raffaella, et al.. (2024). Analysis of convolutional neural networks for fronto-temporal dementia biomarker discovery. International Journal of Computer Assisted Radiology and Surgery. 19(12). 2339–2349. 1 indexed citations

Batrancourt, Bénédicte, John S. H. Baxter, Isabelle Le Ber, et al.. (2022). An ecological approach to identify distinct neural correlates of disinhibition in frontotemporal dementia. NeuroImage Clinical. 35. 103079–103079. 4 indexed citations

Haegelen, Claire, et al.. (2022). Voxel‐based diktiometry: Combining convolutional neural networks with voxel‐based analysis and its application in diffusion tensor imaging for Parkinson's disease. Human Brain Mapping. 43(16). 4835–4851. 5 indexed citations

Haegelen, Claire, et al.. (2021). PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes. International Journal of Computer Assisted Radiology and Surgery. 16(8). 1361–1370. 7 indexed citations

Baxter, John S. H., et al.. (2021). Automatic cortical target point localisation in MRI for transcranial magnetic stimulation via a multi-resolution convolutional neural network. International Journal of Computer Assisted Radiology and Surgery. 16(7). 1077–1087. 2 indexed citations

Gilmore, Greydon, et al.. (2021). Adapting the listening time for micro-electrode recordings in deep brain stimulation interventions. International Journal of Computer Assisted Radiology and Surgery. 16(8). 1371–1379. 4 indexed citations

10.

Jannin, Pierre, et al.. (2021). Data imputation and compression for Parkinson's disease clinical questionnaires. Artificial Intelligence in Medicine. 114. 102051–102051. 14 indexed citations

11.

Baxter, John S. H., et al.. (2020). Striatal shape alteration as a staging biomarker for Parkinson’s Disease. NeuroImage Clinical. 27. 102272–102272. 6 indexed citations

12.

Baxter, John S. H., Zahra Hosseini, Terry M. Peters, & Maria Drangova. (2017). Cyclic Continuous Max-Flow: A Third Paradigm in Generating Local Phase Shift Maps in MRI. IEEE Transactions on Medical Imaging. 37(2). 568–579. 1 indexed citations

13.

Baxter, John S. H., et al.. (2017). Mixed reality ultrasound guidance system: a case study in system development and a cautionary tale. International Journal of Computer Assisted Radiology and Surgery. 13(4). 495–505. 20 indexed citations

14.

Niemtzow, Richard C., Arnyce R. Pock, Joan Walter, et al.. (2016). Integrative Medicine in the Department of Defense and the Department of Veterans Affairs: Cautious Steps Forward. The Journal of Alternative and Complementary Medicine. 22(3). 171–173. 8 indexed citations

15.

Pock, Arnyce R., et al.. (2016). Acupuncture for the New Millennium: A Photoessay from Beijing, China. Medical Acupuncture. 28(1). 9–15.

16.

McLeod, A. Jonathan, et al.. (2015). Detection and visualization of dural pulsation for spine needle interventions. International Journal of Computer Assisted Radiology and Surgery. 10(6). 947–958. 7 indexed citations

17.

McLeod, A. Jonathan, et al.. (2014). Stationary wavelet transform for under-sampled MRI reconstruction. Magnetic Resonance Imaging. 32(10). 1353–1364. 28 indexed citations

18.

Niemtzow, Richard C., et al.. (2008). Acupuncture Clinical Pain Trial in a Military Medical Center: Outcomes. Medical Acupuncture. 20(4). 255–261. 17 indexed citations

19.

Niemtzow, Richard C., Jeffrey M. Gambel, Joseph M. Helms, et al.. (2006). Integrating Ear and Scalp Acupuncture Techniques into the Care of Blast-Injured United States Military Service Members with Limb Loss. The Journal of Alternative and Complementary Medicine. 12(7). 597–599. 1 indexed citations

20.

Niemtzow, Richard C., et al.. (2006). Integrating Ear and Scalp Acupuncture Techniques into the Care of Blast-Injured United States Military Service Members with Limb Loss. Alternative and Complementary Therapies. 12(5). 244–246. 1 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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