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.
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