자료유형 | 학위논문 |
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서명/저자사항 | Development of Segmentation Variability Maps to Improve Brain Tumor Quantitative Assessment Using Multimodal Magnetic Resonance Imaging. |
개인저자 | Rios Piedra, Edgar Anselmo. |
단체저자명 | University of California, Los Angeles. Biomedical Engineering 0289. |
발행사항 | [S.l.]: University of California, Los Angeles., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 215 p. |
기본자료 저록 | Dissertation Abstracts International 79-11B(E). Dissertation Abstract International |
ISBN | 9780438077621 |
학위논문주기 | Thesis (D.Env.)--University of California, Los Angeles, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Advisers: Alex A.T. Bui |
요약 | Glioblastoma multiforme (GBM) is the most common type of primary brain tumor, characterized by a short survival period after diagnosis. As with most other cancers, treatment and follow-up decisions are made largely based on observed changes in t |
요약 | The quantification of tumor measurements is problematic due to the systematic variability introduced while attempting to quantify tumor characteristics in uncertain regions. This issue is primarily observed around the tumor boundary, where it is |
요약 | To address these problems, this dissertation describes a framework to help characterize factors that influence variability in brain tumor boundaries and to optimize their performance through methods that calculate an estimate of expected variabi |
요약 | Altogether, this dissertation project provides further understanding of the sources of variability that arise in GBM across different image analysis methodologies and the integration of these insights into the development of tumor variability ma |
일반주제명 | Medical imaging. Computer science. Biomedical engineering. |
언어 | 영어 |
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