What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Computer vision
Sarang Joshi spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Population and Image registration.
Sarang Joshi studies Computational anatomy, a branch of Artificial intelligence.
His study in the field of Segmentation, Respiratory motion and 3d image also crosses realms of Treatment plan.
Sarang Joshi combines subjects such as Visualization, Visual cortex and Atlas with his study of Pattern recognition.
Sarang Joshi has included themes like Medical imaging, Image processing, Monte Carlo method, Radiation therapy and Dosimetry in his Image registration study.
His Geometry research is multidisciplinary, incorporating perspectives in Boundary, Principal component analysis and Algebra.
His most cited work include:
- Unbiased diffeomorphic atlas construction for computational anatomy. (708 citations)
- Principal geodesic analysis for the study of nonlinear statistics of shape (621 citations)
- Volumetric transformation of brain anatomy (460 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Computer vision, Image registration, Pattern recognition and Population.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Diffeomorphism and Atlas.
The concepts of his Computer vision study are interwoven with issues in Imaging phantom, Radiation therapy and Computed tomography.
Sarang Joshi has included themes like Radiation treatment planning, Fiducial marker and Medical imaging in his Image registration study.
His Medical imaging research focuses on Nuclear medicine and how it connects with Magnetic resonance imaging.
His biological study focuses on Active shape model.
He most often published in these fields:
- Artificial intelligence (44.19%)
- Computer vision (34.11%)
- Image registration (18.99%)
What were the highlights of his more recent work (between 2012-2021)?
- Artificial intelligence (44.19%)
- Computer vision (34.11%)
- Diffeomorphism (9.30%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Computer vision, Diffeomorphism, Image registration and Metric.
His Artificial intelligence study incorporates themes from Dimension, Focus and Pattern recognition.
His work deals with themes such as Rotational invariance and Simple extension, which intersect with Pattern recognition.
His studies deal with areas such as Subspace topology, Radiation therapy and Computed tomography as well as Computer vision.
His Image registration research incorporates elements of Radiation treatment planning and Feature.
His Metric research is multidisciplinary, incorporating perspectives in Manifold, Distribution, Information geometry and Applied mathematics.
Between 2012 and 2021, his most popular works were:
- Morphometry of anatomical shape complexes with dense deformations and sparse parameters. (153 citations)
- Intrinsic Polynomials for Regression on Riemannian Manifolds (62 citations)
- A vector momenta formulation of diffeomorphisms for improved geodesic regression and atlas construction (49 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Computer vision
Sarang Joshi mostly deals with Diffeomorphism, Topology, Population, Euclidean geometry and Image registration.
Sarang Joshi focuses mostly in the field of Diffeomorphism, narrowing it down to topics relating to Geodesic and, in certain cases, Shape analysis.
His Topology study combines topics from a wide range of disciplines, such as Residual and Applied mathematics.
Population combines with fields such as Pattern recognition and Artificial intelligence in his investigation.
His research investigates the connection between Pattern recognition and topics such as Human brain that intersect with issues in Neuroimaging.
His research in Image registration intersects with topics in Fiducial marker, Projection, Motion analysis, Matching and Convolutional neural network.
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