Kentaro Mori1,*, Kotaro Kitaya2, Tomomoto Ishikawa2, Yutaka Hata3
Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 335-352, 2021, DOI:10.32604/iasc.2021.01010
Abstract In infertility treatment, it is required to improve a success rate of the treatment. A purpose of this study is to develop a prediction system for pregnancy outcomes using ultrasonic images. In infertility treatment, it is typical to evaluate the endometrial shape by using ultrasonic images. The convolutional neural network (CNN) system developed in the current study predicted pregnancy outcome by velocity information. The velocity information has a movement feature of uterine. It is known that a uterine movement is deep related to infertility. Experiments compared the velocity-based and shape-based systems. The shape-based systems predict the optimal uterine features for… More >
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