Automatic Detection of Standard Sagittal Plane in the First Trimester of Pregnancy Using 3-D Ultrasound Data.
Fetal nuchal translucency (NT) thickness is one of the most important parameters in prenatal screening. Locating the mid-sagittal plane is one of the key points to measure NT. In this paper, an automatic method for the sagittal plane detection using 3-D ultrasound data is proposed. To avoid unnecessary massive searching and the corresponding huge computation load, a model is proposed to turn the sagittal plane detection problem into a symmetry plane and axis searching problem. The deep belief network (DBN) and a modified circle detection method provide prior knowledge for the searching. The experiments show that in most cases, the result plane has small distance error and angle error at the same time-88.6% of the result planes have a distance error less than 4 mm and 71.0% have angle error less than 20°.
Department of Electronic Engineering, Fudan University, Shanghai, China.
Siqing
S
Nie
Department of Electronic Engineering, Fudan University, Shanghai, China; The Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China. Electronic address: jhyu@fudan.edu.cn.
Jinhua
J
Yu
Ultrasound Department, Shanghai First Maternity and Infant Hospital, Tongji University, Shanghai, China.
Ping
P
Chen
Department of Electronic Engineering, Fudan University, Shanghai, China.
Yuanyuan
Y
Wang
Department of Electronic Engineering, Fudan University, Shanghai, China.
Jian Qiu
JQ
Zhang
D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D048208:Nuchal Translucency Measurement / Q000379:methods*; D011247:Pregnancy; D011261:Pregnancy Trimester, First
3-D ultrasound data; Deep belief network; Sagittal plane detection; Symmetry detection