利用马尔可夫随机场测量第一孕期超声胎儿图像中的颈部透明层厚度

Kalyani Choudhari, Shruti Oza
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引用次数: 0

摘要

背景:第一胎超声评估颈部透明层(NT)厚度最近被推荐为早期筛查产前染色体疾病的最有用的体征。妊娠 11-13+6 周胎儿 NT 厚度增加是染色体异常以及各种胎儿畸形和遗传疾病的常见表型表现。目的:目前,临床医生都是手动进行测量。这种测量可能需要很长时间才能完成,要求操作人员具有很高的能力,而且容易出错。因此,需要一种自动方法来进行 NT 测量。方法:本研究提出了一种基于马尔可夫随机场的方法,可从胎儿图片中根据上下文分割 NT 区域,即使在怀孕早期也能提供快速、廉价的诊断。结果建议方法的最大 NT 厚度误差为 0.03,最小 NT 厚度误差为 0.04。结论所提议的研究工作为自动 NT 厚度测量系统开发了一个原型。本研究提出了一种基于 MRF 的模型,用于从胎儿照片中分割和检测 NT 区域,其误差小于其他方法。
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Measurement of Nuchal Translucency Thickness 
in First Trimester Ultrasound Foetal Images 
Using Markov Random Field
Background: The first-trimester ultrasound assessment of nuchal translucency (NT) thickness has lately been recommended as the most helpful sign in early screening for prenatal chromosomal disorders. Increased foetal NT thickness between 11 and 13+6 weeks of gestation is a frequent phenotypic manifestation of chromosomal abnormalities as well as a variety of foetal deformities and genetic disorders. Purpose: At the moment, clinicians conduct the measurement manually. The measurement may take a long time to complete, requires highly competent operators, and is susceptible to mistakes. So, an automatic method is required for NT measurement. Methods: This study proposes a Markov random Field-based approach for contextually segmenting the NT area from foetal pictures and offering a quick and inexpensive diagnostic even during the early stages of pregnancy. Results: Proposed method gives maximum NT thickness error 0.03 and minimum NT thickness error 0.04. Conclusion: The proposed research work developed a prototype for an automated NT thickness measuring system. This study proposes an MRF-based model for segmentation and detection of NT area from foetal pictures which gives error is less than other methods.
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