Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/50726
Title: Novel level set based statistical frameworks for segmentation of MR images
Authors: Mahshid Farzinfar
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 2012
Source: Mahshid, F. (2012). Novel level set based statistical frameworks for segmentation of MR images. Doctoral thesis, Nanyang Technological University, Singapore.
Abstract: In summary, two automated frameworks for segmentation of medical images are proposed. They are the joint curve evolution and the EM-joint shape based algorithms. In addition, the generalization of our frameworks to 3D models of multiple struc- tures. The resulting implementation is tested on a variety of studies to parceling of anatomical structures. The proposed algorithms can be used for surgery navigation and 3D visualization. They could also be applied to neuroscience studies in finding new diseases related to anatomical characteristics and the increase in reliability in diagnosing of illnesses such as schizophrenia.
URI: https://hdl.handle.net/10356/50726
DOI: 10.32657/10356/50726
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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