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Efficient Modeling of 3D Shape of Women During Gestation to Assess Risk of Cephalopelvic Disproportion (CPD)
Efficient Modeling of 3D Shape of Women During Gestation to Assess Risk of Cephalopelvic Disproportion (CPD)
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105527
- ISBN
- 9798263345075
- DDC
- 610.73678
- 저자명
- Nayak, Likhit K.
- 서명/저자
- Efficient Modeling of 3D Shape of Women During Gestation to Assess Risk of Cephalopelvic Disproportion (CPD)
- 발행사항
- [Sl] : Georgia Institute of Technology, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 109 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
- 주기사항
- Advisor: Gleason, Rudolph.
- 학위논문주기
- Thesis (Ph.D.)--Georgia Institute of Technology, 2025.
- 초록/해제
- 요약Cephalopelvic disproportion (CPD) is a mismatch in the size of the maternal pelvis and the fetus, which often leads to obstructed labor. Most cases of CPD require C-section for successful delivery and in low resource settings like Ethiopia, there is a lack of adequate facilities with the infrastructure or the expertise to perform a C-section. Currently, obstructed labor is known to account for 11 - 22 % of maternal deaths in Ethiopia. Early assessment of the risk of CPD would enable women in these settings to access the proper healthcare services and improve overall maternal health. This thesis aims to develop an algorithm that would use longitudinal shape modeling to analyze, in real-time, 3D scans of pregnant women and assess the risk of CPD-related obstructed labor at the earliest possible stages of gestation. The longitudinal shape model would be trained on 3D scans of pregnant women across different periods of gestation and would be optimized to run on devices with low computational power. The prognostic value of the model for assessing the risk of CPD would be compared to anthropometric measurements. This model is envisioned to be used by nurses and midwife personnel as part of point-of-care tools for routine antenatal care in low-resource settings.
- 일반주제명
- Womens health
- 일반주제명
- Anthropometry
- 일반주제명
- Maternal mortality
- 일반주제명
- Support vector machines
- 일반주제명
- Computer science
- 일반주제명
- Obstetrics
- 일반주제명
- Public health
- 기본자료저록
- Dissertations Abstracts International. 87-05B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798263345075
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■035 ▼a(MiAaPQ)GeorgiaTech77790
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a610.73678
■1001 ▼aNayak, Likhit K.
■24510▼aEfficient Modeling of 3D Shape of Women During Gestation to Assess Risk of Cephalopelvic Disproportion (CPD)
■260 ▼a[Sl]▼bGeorgia Institute of Technology▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a109 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: B.
■500 ▼aAdvisor: Gleason, Rudolph.
■5021 ▼aThesis (Ph.D.)--Georgia Institute of Technology, 2025.
■520 ▼aCephalopelvic disproportion (CPD) is a mismatch in the size of the maternal pelvis and the fetus, which often leads to obstructed labor. Most cases of CPD require C-section for successful delivery and in low resource settings like Ethiopia, there is a lack of adequate facilities with the infrastructure or the expertise to perform a C-section. Currently, obstructed labor is known to account for 11 - 22 % of maternal deaths in Ethiopia. Early assessment of the risk of CPD would enable women in these settings to access the proper healthcare services and improve overall maternal health. This thesis aims to develop an algorithm that would use longitudinal shape modeling to analyze, in real-time, 3D scans of pregnant women and assess the risk of CPD-related obstructed labor at the earliest possible stages of gestation. The longitudinal shape model would be trained on 3D scans of pregnant women across different periods of gestation and would be optimized to run on devices with low computational power. The prognostic value of the model for assessing the risk of CPD would be compared to anthropometric measurements. This model is envisioned to be used by nurses and midwife personnel as part of point-of-care tools for routine antenatal care in low-resource settings.
■590 ▼aSchool code: 0078.
■650 4▼aWomens health
■650 4▼aAnthropometry
■650 4▼aMaternal mortality
■650 4▼aSupport vector machines
■650 4▼aComputer science
■650 4▼aObstetrics
■650 4▼aPublic health
■690 ▼a0800
■690 ▼a0984
■690 ▼a0380
■690 ▼a0573
■71020▼aGeorgia Institute of Technology.
■7730 ▼tDissertations Abstracts International▼g87-05B.
■790 ▼a0078
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360446▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
