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Grant: Discovery Grants Program - Individual

Université d'Ottawa

$25,000.00

Methods for image analysis and summarization of high-dimensional dynamics

EF 2024-25

Résumé
This proposal has two parts: (i) Methods for image analysis and (ii) summarization of high-dimensional dynamics. In the first part, I will investigate mathematical and computational methods for image analysis, with a focus on medical images such as X-Rays and Magnetic Resonance Images (MRIs). Together with my trainees, we will develop new methods for registering, i.e. aligning, images, and also for finding lesions and other abnormalities. These tasks are central to medical image analysis and many computer vision applications such as tracking and change detection. In medical imaging, registration allows us to compare images from different people, or from the same person at different times, and do statistics on groups of images. It turns out that registering images first helps with finding lesions, and finding lesions first helps with registering images. We will attempt to resolve this "chicken-and-egg" problem by developing integrated analysis methods that do both at the same time. The second part of the proposal is about dynamical systems, a term that includes both differential equations and real-world systems that change according to physical rules, such as weather and climate, or planetary motion, or a beating heart. Many dynamical systems are so big and complex that the task of understanding them can seem hopeless at first. Even if we know all the underlying physical rules, it is hard to be sure we've considered all the possible ramifications of those rules. Together with trainees and colleagues, we will develop automatic computational methods for generating summaries of the possible behaviours of a dynamical system. develop an automatic computational method for generating summaries of the possible behaviours of a dynamical system.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2023-05158
Name nom
Schmah, Tanya
Department département
Mathematics and Statistics
Organization id
28
Institution établissement
Université d'Ottawa
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
25000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1508
Committee name en
Mathematics and Statistics
Committee name fr
Mathématiques et statistique
Area of application code
1211
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Medical and health sciences
Area of application fr
Sciences médicales et de la santé
Research subject code
2960
Research subject group en
Applied mathematics
Research subject group fr
Mathématiques appliquées
Research subject en
Mathematical modelling
Research subject fr
Modélisation mathématique
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Methods for image analysis and summarization of high-dimensional dynamics
Keywords
medical image analysis; data-driven dynamical analysis; image registration; anomaly detection; deep learning; latent variable models; dynamic mode decomposition; ergodic quotient; physics-inspired neural networks
Application summary
This proposal has two parts: (i) Methods for image analysis and (ii) summarization of high-dimensional dynamics. In the first part, I will investigate mathematical and computational methods for image analysis, with a focus on medical images such as X-Rays and Magnetic Resonance Images (MRIs). Together with my trainees, we will develop new methods for registering, i.e. aligning, images, and also for finding lesions and other abnormalities. These tasks are central to medical image analysis and many computer vision applications such as tracking and change detection. In medical imaging, registration allows us to compare images from different people, or from the same person at different times, and do statistics on groups of images. It turns out that registering images first helps with finding lesions, and finding lesions first helps with registering images. We will attempt to resolve this "chicken-and-egg" problem by developing integrated analysis methods that do both at the same time. The second part of the proposal is about dynamical systems, a term that includes both differential equations and real-world systems that change according to physical rules, such as weather and climate, or planetary motion, or a beating heart. Many dynamical systems are so big and complex that the task of understanding them can seem hopeless at first. Even if we know all the underlying physical rules, it is hard to be sure we've considered all the possible ramifications of those rules. Together with trainees and colleagues, we will develop automatic computational methods for generating summaries of the possible behaviours of a dynamical system. develop an automatic computational method for generating summaries of the possible behaviours of a dynamical system.