D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 107 Citations 47,039 415 World Ranking 101 National Ranking 67
Medicine D-index 121 Citations 54,774 423 World Ranking 1464 National Ranking 883

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Magnetic resonance imaging
  • Internal medicine

His primary areas of investigation include Magnetic resonance imaging, Artificial intelligence, Computer vision, White matter and Neuroscience. His study on Magnetic resonance imaging is covered under Radiology. Artificial intelligence is closely attributed to Pattern recognition in his work.

His Computer vision study combines topics in areas such as Visualization and Surface. His work carried out in the field of White matter brings together such families of science as Hyperintensity, Diffusion MRI, Anatomy, Pathology and Human brain. His work in Neuroscience addresses subjects such as Psychosis, which are connected to disciplines such as Temporal lobe, Schizophrenia, First episode, Gyrus and Laterality.

His most cited work include:

  • 3D Slicer as an image computing platform for the Quantitative Imaging Network. (2428 citations)
  • Multi-modal volume registration by maximization of mutual information (1753 citations)
  • Adaptive segmentation of MRI data (1196 citations)

What are the main themes of his work throughout his whole career to date?

Ron Kikinis mainly focuses on Artificial intelligence, Computer vision, Magnetic resonance imaging, Segmentation and Radiology. His research combines Pattern recognition and Artificial intelligence. His Computer vision research incorporates elements of Surface, Computer graphics, Finite element method and Medical imaging.

He is involved in the study of Magnetic resonance imaging that focuses on White matter in particular. Ron Kikinis is interested in Scale-space segmentation, which is a branch of Segmentation. The Neuroscience study combines topics in areas such as Schizophrenia, Diffusion MRI and Audiology.

He most often published in these fields:

  • Artificial intelligence (39.81%)
  • Computer vision (28.84%)
  • Magnetic resonance imaging (26.06%)

What were the highlights of his more recent work (between 2012-2021)?

  • Artificial intelligence (39.81%)
  • Computer vision (28.84%)
  • Magnetic resonance imaging (26.06%)

In recent papers he was focusing on the following fields of study:

Artificial intelligence, Computer vision, Magnetic resonance imaging, Pattern recognition and Diffusion MRI are his primary areas of study. His research links Neuroimaging with Artificial intelligence. His Computer vision study incorporates themes from Neuronavigation, Visualization and Biopsy.

His Magnetic resonance imaging study is concerned with Radiology in general. The study incorporates disciplines such as White matter and Anatomy in addition to Diffusion MRI. His research integrates issues of Image processing, 3d slicer and Ultrasound in his study of Segmentation.

Between 2012 and 2021, his most popular works were:

  • Robust Radiomics feature quantification using semiautomatic volumetric segmentation. (294 citations)
  • Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease (256 citations)
  • 3D Slicer: A Platform for Subject-Specific Image Analysis, Visualization, and Clinical Support (239 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Internal medicine
  • Magnetic resonance imaging

Ron Kikinis mostly deals with Artificial intelligence, White matter, Diffusion MRI, Pattern recognition and Magnetic resonance imaging. His biological study spans a wide range of topics, including Neuroimaging and Computer vision. His Computer vision research is multidisciplinary, relying on both Electrical impedance tomography, Software suite and Bioinformatics.

His work on Tractography as part of general White matter research is often related to Gray, thus linking different fields of science. His Diffusion MRI research is multidisciplinary, incorporating elements of Middle temporal gyrus, Schizophrenia, Prefrontal cortex and Pathology. His research in Magnetic resonance imaging intersects with topics in Lesion, Segmentation, Anesthesia, Image processing and Dementia.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

3D Slicer as an image computing platform for the Quantitative Imaging Network.

Andriy Fedorov;Reinhard Beichel;Jayashree Kalpathy-Cramer;Julien Finet.
Magnetic Resonance Imaging (2012)

2584 Citations

Multi-modal volume registration by maximization of mutual information

William M. Wells;William M. Wells;Paul A. Viola;Paul A. Viola;Hideki Atsumi;Shin Nakajima.
Medical Image Analysis (1996)

2497 Citations

Adaptive segmentation of MRI data

W.M. Wells;W.E.L. Grimson;R. Kikinis;F.A. Jolesz.
IEEE Transactions on Medical Imaging (1996)

1658 Citations

Nonlinear anisotropic filtering of MRI data

G. Gerig;O. Kubler;R. Kikinis;F.A. Jolesz.
IEEE Transactions on Medical Imaging (1992)

1436 Citations

Abnormalities of the left temporal lobe and thought disorder in schizophrenia. A quantitative magnetic resonance imaging study.

Martha Elizabeth Shenton;Ron Kikinis;Ferenc A. Jolesz;Seth D. Pollak.
The New England Journal of Medicine (1992)

1373 Citations

Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images.

Yoshinobu Sato;Shin Nakajima;Nobuyuki Shiraga;Hideki Atsumi.
Medical Image Analysis (1998)

1296 Citations

Statistical validation of image segmentation quality based on a spatial overlap index.

Kelly H. Zou;Kelly H. Zou;Simon K. Warfield;Aditya Bharatha;Clare M.C. Tempany.
Academic Radiology (2004)

1206 Citations

Magnetic resonance imaging study of hippocampal volume in chronic, combat-related posttraumatic stress disorder.

Tamara V. Gurvits;Tamara V. Gurvits;Martha Elizabeth Shenton;Martha Elizabeth Shenton;Hiroto Hokama;Hiroto Hokama;Hirokazu Ohta;Hirokazu Ohta.
Biological Psychiatry (1996)

1092 Citations

Processing and visualization for diffusion tensor MRI.

Carl-Fredrik Westin;Stephan E. Maier;Hatsuho Mamata;Arya Nabavi.
Medical Image Analysis (2002)

1001 Citations

Development and implementation of intraoperative magnetic resonance imaging and its neurosurgical applications.

Peter McL. Black;Thomas Moriarty;Eben Alexander;Philip Stieg.
Neurosurgery (1997)

909 Citations

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