What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Mathematical analysis
His primary scientific interests are in Artificial intelligence, Computer vision, Image segmentation, Active contour model and Segmentation.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Algorithm and Pattern recognition.
His Algorithm research includes themes of Shape analysis and Topology.
His work carried out in the field of Computer vision brings together such families of science as Kalman filter, Energy functional and Radiance.
His studies deal with areas such as Image registration, Robustness and Maxima and minima as well as Image segmentation.
His research integrates issues of Active vision, Computational geometry, Feature and Image processing in his study of Active contour model.
His most cited work include:
- A shape-based approach to the segmentation of medical imagery using level sets (779 citations)
- Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification (753 citations)
- Gradient flows and geometric active contour models (615 citations)
What are the main themes of his work throughout his whole career to date?
Anthony Yezzi focuses on Artificial intelligence, Computer vision, Segmentation, Image segmentation and Active contour model.
Anthony Yezzi combines subjects such as Algorithm and Pattern recognition with his study of Artificial intelligence.
Anthony Yezzi studied Computer vision and Surface that intersect with Point.
His Segmentation study integrates concerns from other disciplines, such as Signed distance function, Real image and Boundary.
His Image segmentation research incorporates themes from Gradient descent, Smoothing and Maxima and minima.
His Active contour model study combines topics from a wide range of disciplines, such as Feature, Metric, Topology, Edge detection and Sobolev space.
He most often published in these fields:
- Artificial intelligence (58.52%)
- Computer vision (41.85%)
- Segmentation (35.19%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (58.52%)
- Segmentation (35.19%)
- Pattern recognition (16.30%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Segmentation, Pattern recognition, Applied mathematics and Gradient descent.
As part of his studies on Artificial intelligence, Anthony Yezzi frequently links adjacent subjects like Algorithm.
His studies in Algorithm integrate themes in fields like Image segmentation, Polygon, Inversion, Smoothness and Signal.
The subject of his Segmentation research is within the realm of Computer vision.
His study in the field of Edge detection also crosses realms of Anatomical structures.
His Active contour model study in the realm of Pattern recognition interacts with subjects such as Set.
Between 2015 and 2021, his most popular works were:
- K-nearest neighbor driving active contours to delineate biological tumor volumes (21 citations)
- Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography. (20 citations)
- A smart and operator independent system to delineate tumours in Positron Emission Tomography scans. (20 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Statistics
Anthony Yezzi mainly investigates Artificial intelligence, Segmentation, Pattern recognition, Active contour model and Region of interest.
Anthony Yezzi undertakes interdisciplinary study in the fields of Artificial intelligence and Tracing through his research.
His Pattern recognition research includes elements of Positron emission tomography, Standardized uptake value, Computed tomography and Similarity.
His research investigates the connection between Similarity and topics such as Gold standard that intersect with issues in Image segmentation, Tomography, Radiation treatment planning, Radiation therapy and Radiomics.
His research in Active contour model focuses on subjects like Linear discriminant analysis, which are connected to Modality and Minification.
His study looks at the relationship between Region of interest and fields such as Imaging phantom, as well as how they intersect with chemical problems.
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