Michael I. Miller

604 total citations
12 papers, 441 citations indexed

About

Michael I. Miller is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Psychiatry and Mental health. According to data from OpenAlex, Michael I. Miller has authored 12 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cognitive Neuroscience, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Psychiatry and Mental health. Recurrent topics in Michael I. Miller's work include Medical Image Segmentation Techniques (4 papers), Hearing Loss and Rehabilitation (3 papers) and Hearing, Cochlea, Tinnitus, Genetics (2 papers). Michael I. Miller is often cited by papers focused on Medical Image Segmentation Techniques (4 papers), Hearing Loss and Rehabilitation (3 papers) and Hearing, Cochlea, Tinnitus, Genetics (2 papers). Michael I. Miller collaborates with scholars based in United States, China and Belgium. Michael I. Miller's co-authors include Natalia A. Trayanova, Donald Geman, Raimond L. Winslow, Murray B. Sachs, Susumu Mori, Richard D. Bucholz, Lei Wang, Kevin Mark, R. Edward Hogan and Sarang Joshi and has published in prestigious journals such as PLoS ONE, NeuroImage and Radiology.

In The Last Decade

Michael I. Miller

12 papers receiving 431 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael I. Miller United States 9 122 101 85 83 70 12 441
Ben A. Duffy United States 17 222 1.8× 156 1.5× 220 2.6× 71 0.9× 74 1.1× 26 655
Jennifer L. Cuzzocreo United States 17 102 0.8× 272 2.7× 77 0.9× 89 1.1× 62 0.9× 21 759
Hans Olofsen Netherlands 13 166 1.4× 287 2.8× 28 0.3× 62 0.7× 156 2.2× 16 723
Simon J. Francis Canada 11 52 0.4× 275 2.7× 49 0.6× 126 1.5× 80 1.1× 14 777
Bistra Iordanova United States 11 98 0.8× 278 2.8× 108 1.3× 89 1.1× 21 0.3× 24 792
Francesco Gentile Italy 13 408 3.3× 95 0.9× 48 0.6× 66 0.8× 55 0.8× 43 775
Eva Janoušová Czechia 12 180 1.5× 80 0.8× 32 0.4× 105 1.3× 69 1.0× 31 568
Venkateswaran Rajagopalan United States 16 155 1.3× 174 1.7× 46 0.5× 37 0.4× 107 1.5× 42 778
Zhao Feng China 13 97 0.8× 53 0.5× 120 1.4× 137 1.7× 17 0.2× 34 623
Marjan Acou Belgium 11 67 0.5× 237 2.3× 43 0.5× 41 0.5× 41 0.6× 24 468

Countries citing papers authored by Michael I. Miller

Since Specialization
Citations

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

Fields of papers citing papers by Michael I. Miller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael I. Miller. 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 Michael I. Miller. The network helps show where Michael I. Miller may publish in the future.

Co-authorship network of co-authors of Michael I. Miller

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

All Works

12 of 12 papers shown
1.
Tang, Xiaoying, Karen E. Seymour, Deana Crocetti, et al.. (2019). Response control correlates of anomalous basal ganglia morphology in boys, but not girls, with attention-deficit/hyperactivity disorder. Behavioural Brain Research. 367. 117–127. 12 indexed citations
2.
Ye, Chenfei, Ting Ma, Dan Wu, et al.. (2018). Atlas pre-selection strategies to enhance the efficiency and accuracy of multi-atlas brain segmentation tools. PLoS ONE. 13(7). e0200294–e0200294. 8 indexed citations
3.
Wu, Dan, Can Ceritoglu, Michael I. Miller, & Susumu Mori. (2016). Direct estimation of patient attributes from anatomical MRI based on multi-atlas voting. NeuroImage Clinical. 12. 570–581. 11 indexed citations
4.
Tang, Xiaoying, Deana Crocetti, Kwame S. Kutten, et al.. (2015). Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles. Frontiers in Neuroscience. 9. 50 indexed citations
5.
Winslow, Raimond L., Natalia A. Trayanova, Donald Geman, & Michael I. Miller. (2012). Computational Medicine: Translating Models to Clinical Care. Science Translational Medicine. 4(158). 158rv11–158rv11. 136 indexed citations
6.
Zhang, Jiangyang, Peng Qi, Qing Li, et al.. (2009). Longitudinal characterization of brain atrophy of a Huntington's disease mouse model by automated morphological analyses of magnetic resonance images. NeuroImage. 49(3). 2340–2351. 72 indexed citations
7.
Hogan, R. Edward, Kevin Mark, Indrajit Choudhuri, et al.. (2000). Magnetic resonance imaging deformation-based segmentation of the hippocampus in patients with mesial temporal sclerosis and temporal lobe epilepsy. Journal of Digital Imaging. 13(S1). 217–218. 14 indexed citations
8.
Hogan, R. Edward, Kevin Mark, Lei Wang, et al.. (2000). Mesial Temporal Sclerosis and Temporal Lobe Epilepsy: MR Imaging Deformation-based Segmentation of the Hippocampus in Five Patients. Radiology. 216(1). 291–297. 80 indexed citations
9.
Csernansky, John G., John Haller, Lei Wang, et al.. (1997). A comparison of the hippocampus in schizophrenia and control subjects using automated methods for neuromorphometry. Schizophrenia Research. 24(1-2). 141–141. 1 indexed citations
10.
Miller, Michael I. & Murray B. Sachs. (1984). Representation of voice pitch in discharge patterns of auditory-nerve fibers. Hearing Research. 14(3). 257–279. 43 indexed citations
11.
Sachs, Murray B., Eric D. Young, & Michael I. Miller. (1983). SPEECH ENCODING IN THE AUDITORY NERVE: IMPLICATIONS FOR COCHLEAR IMPLANTSa. Annals of the New York Academy of Sciences. 405(1). 94–113. 13 indexed citations
12.
Miller, Michael I. & Murray B. Sachs. (1981). Temporal representation of CV syllables in populations of auditory-nerve fibers. The Journal of the Acoustical Society of America. 70(S1). S9–S9. 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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