What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Computer vision
Yogesh Rathi mainly focuses on Artificial intelligence, Diffusion MRI, Computer vision, Neuroscience and White matter.
He interconnects Reduction and Pattern recognition in the investigation of issues within Artificial intelligence.
The various areas that he examines in his Diffusion MRI study include Diffusion, Voxel and Spherical harmonics.
His Computer vision research incorporates themes from Kalman filter, Algorithm, Compressed sensing and Transformation.
His Neuroscience study frequently draws parallels with other fields, such as Schizophrenia.
His White matter research integrates issues from Query language, Spatial relation and Dorsolateral prefrontal cortex.
His most cited work include:
- A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury (580 citations)
- Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow (279 citations)
- Tracking Deforming Objects Using Particle Filtering for Geometric Active Contours (155 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Diffusion MRI, Artificial intelligence, White matter, Tractography and Pattern recognition.
Yogesh Rathi has researched Diffusion MRI in several fields, including Schizophrenia, Neuroscience and Voxel.
His Artificial intelligence research is multidisciplinary, relying on both Algorithm and Computer vision.
His work carried out in the field of Computer vision brings together such families of science as Robustness and Compressed sensing.
The Tractography study combines topics in areas such as Fiber, Machine learning and Human Connectome Project.
His study in the field of Kernel principal component analysis and Shape analysis is also linked to topics like Population.
He most often published in these fields:
- Diffusion MRI (54.58%)
- Artificial intelligence (45.02%)
- White matter (30.68%)
What were the highlights of his more recent work (between 2018-2021)?
- Diffusion MRI (54.58%)
- White matter (30.68%)
- Neuroscience (30.28%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Diffusion MRI, White matter, Neuroscience, Tractography and Fractional anisotropy.
Yogesh Rathi combines subjects such as Angular resolution, Biological system and Scanner, Artificial intelligence with his study of Diffusion MRI.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Pattern recognition.
The study incorporates disciplines such as Pathological, Cingulate cortex and Physiology in addition to White matter.
As a part of the same scientific study, Yogesh Rathi usually deals with the Neuroscience, concentrating on Voxel and frequently concerns with Midbrain, Sensory system and Brainstem.
His studies in Tractography integrate themes in fields like Visualization and Human Connectome Project.
Between 2018 and 2021, his most popular works were:
- Limits to anatomical accuracy of diffusion tractography using modern approaches. (80 citations)
- Retrospective harmonization of multi-site diffusion MRI data acquired with different acquisition parameters. (53 citations)
- White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study (39 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Neuroscience
His main research concerns Diffusion MRI, White matter, Artificial intelligence, Tractography and Pattern recognition.
His Diffusion MRI study is concerned with the larger field of Magnetic resonance imaging.
Specifically, his work in White matter is concerned with the study of Fractional anisotropy.
His Artificial intelligence study frequently draws connections to other fields, such as Computer vision.
His work in Tractography covers topics such as Neuroscience which are related to areas like Diffusion imaging, White matter microstructure and White matter changes.
The Segmentation research he does as part of his general Pattern recognition study is frequently linked to other disciplines of science, such as Test retest reproducibility, therefore creating a link between diverse domains of science.
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