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.
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.
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.
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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Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification
A. Tsai;A. Yezzi;A.S. Willsky.
IEEE Transactions on Image Processing (2001)
A shape-based approach to the segmentation of medical imagery using level sets
A. Tsai;A. Yezzi;W. Wells;C. Tempany.
IEEE Transactions on Medical Imaging (2003)
Gradient flows and geometric active contour models
S. Kichenassamy;A. Kumar;P. Olver;A. Tannenbaum.
international conference on computer vision (1995)
A geometric snake model for segmentation of medical imagery
A. Yezzi;S. Kichenassamy;A. Kumar;P. Olver.
IEEE Transactions on Medical Imaging (1997)
Conformal curvature flows: From phase transitions to active vision
Satyanad Kichenassamy;Arun Kumar;Peter Olver;Allen Tannenbaum.
Archive for Rational Mechanics and Analysis (1996)
A statistical approach to snakes for bimodal and trimodal imagery
A. Yezzi;A. Tsai;A. Willsky.
international conference on computer vision (1999)
On the relationship between parametric and geometric active contours
Chenyang Xu;A. Yezzi;J.L. Prince.
asilomar conference on signals, systems and computers (2000)
A nonparametric statistical method for image segmentation using information theory and curve evolution
Junmo Kim;J.W. Fisher;A. Yezzi;M. Cetin.
IEEE Transactions on Image Processing (2005)
A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations
Anthony Yezzi;Andy Tsai;Alan Willsky.
Journal of Visual Communication and Image Representation (2002)
Integral Invariants for Shape Matching
S. Manay;D. Cremers;Byung-Woo Hong;A.J. Yezzi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)
Profile was last updated on December 6th, 2021.
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