Hybrid-feature based cell segmentation from cervical smear images

• Main Authors: Ting-Wei Tseng, 曾亭瑋
• Other Authors: Shyr-Shen Yu
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/55442022767827240003

碩士 === 國立中興大學 === 資訊科學與工程學系 === 105 === Cervical cancer is the top cancer in Taiwan, and can be effectively prevented by cervical smear test. However, deal those smear images by human is inefficient. Computer-Assisted system can reducing human consumption, improve efficiency, but also reduce the fail decision caused by fatigue. The aim of this study was to segment the cytoplasm and the nucleus from the cervical smear image. Which by the determination of cell shape, the image classification for different cutting process, effectively reducing the wrong cutting. This paper uses the images provided by the metal center, and finally uses five different methods to evaluate the segmentation effect of this article.