A Study on Automatic Detection of Uterine' Cervical Pap- Smears by Image Processing

영상처리를 이용한 자궁경부 세포진의 자동탐색 방법에 관한 연구

  • Un, Sung-Kyung (Department of Computer Science Pohang Institute of Science and Technology) ;
  • Park, Chan-Mo (Department of Computer Science Pohang Institute of Science and Technology) ;
  • Park, Hwa-Choon (Department of Computer Science Pohang Institute of Science and Technology) ;
  • Yoon, So-Young (Department of Pathology Ewha Woman's University Hospital) ;
  • Cho, Min-Sun (Department of Pathology Ewha Woman's University Hospital) ;
  • Cho, Soo-Yeon (Department of Pathology Ewha Woman's University Hospital) ;
  • Kim, Sung-Sook (Department of Pathology Ewha Woman's University Hospital)
  • 은성경 (포항공과대학 전자계산학과) ;
  • 박찬모 (포항공과대학 전자계산학과) ;
  • 박화춘 (포항공과대학 전자계산학과) ;
  • 윤소영 (이화여자대학교 의과대학 병리과) ;
  • 조민선 (이화여자대학교 의과대학 병리과) ;
  • 조수연 (이화여자대학교 의과대학 병리과) ;
  • 김성숙 (이화여자대학교 의과대학 병리과)
  • Published : 1994.06.30

Abstract

Cancer of the cervix is the most common malignancy in women in developing countries and the second most common cancer in women throughout the world with approximately 500,000 new cases each year. Prevention of this large number of premature deaths among women is, therefore, a goal worthy of urgent and serious consideration. Due to its high diagnostic disagreement among pathologists and large quantity of specimens, it is necessary to develop an automatic screening system measuring morphologic and densitometric features of the samples. Many research works have been published but most of them used Feulgen stained specimens which are not a usual staining method used in clinics. In this thesis, an automatic cancerous nucleus detection method essential to a screening system with papanicolaou stained specimens called Pap-smear is proposed which employs image processing techniques. It uses edge information to segment objects and morphologic as well as densitometric information to distinguish cancerous nuclei from dirts or normal nuclei. It has produced useful results in our study.

Keywords