- Title Information
- Title
- Manifold Learning, Topological Data Analysis, and Their Applications to Medical Imaging
- Type of Resource (primo)
- dissertations
- Name:
Personal
- Name Part
- Meng, Kun
- Role
- Role Term:
Text
- creator
- Name:
Personal
- Name Part
- Eloyan, Ani
- Role
- Role Term:
Text
- Advisor
- Name:
Personal
- Name Part
- Gatsonis, Constantine
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Harrison, Matthew
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Crawford, Lorin
- Role
- Role Term:
Text
- Reader
- Name:
Corporate
- Name Part
- Brown University. Department of Biostatistics
- Role
- Role Term:
Text
- sponsor
- Origin Information
- Copyright Date
- 2022
- Physical Description
- Extent
- , None p.
- digitalOrigin
- born digital
- Note:
thesis
- Thesis (Ph. D.)--Brown University, 2022
- Genre (aat)
- theses
- Abstract
- This dissertation aims to develop several statistical methods for learning the manifold and topology structures of data, provide the corresponding theoretical foundations, and apply the proposed methods to medical imaging. Specifically, this dissertation is concerned with manifold learning, brain networks, and topological data analysis.
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01400410")
- Topic
- Applied mathematics
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/02009945")
- Topic
- Biostatistics
- Language
- Language Term (ISO639-2B)
- English
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20220706