A Review of Image Analysis and Pattern Classification Techniques for Automatic Pap Smear Screening Process

Pap smears are a very effective screening test for cervical precancerous. However, hundreds of small windows have to be looked under microscope by a trained cytologist for a single slide from each patient. It makes this process very tedious and erroneous. The automatic analysis of Pap smear microscopic images is one of the most interesting fields in biomedical image processing. This paper gives an overview of the state of the art and currently available literature and techniques related to Pap smear microscopic image analysis. Some techniques are used to detect cell components such as nuclei and cell boundaries. Other segmentation techniques are designed to use in single cell or clustered cell images. Many schemes are proposed for cell classification. The common aim of all these techniques is to develop an automated Pap smear analysis system which can help cytotechnician reducing time spent for slide examination in Pap screening process and save lives.

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