퍼지 논리와 유전 알고리듬을 이용한 갑상선 암세포의 인식 = Recognition of Thyroid Gland Cancer Cells using Fuzzy Logic and Genetic Algorithms

다국어 초록 (Multilingual Abstract)

This paper proposes the new method based on fuzzy logic which recognizes between normal, and abnormal(two types of abnormal : follicular neoplastic, and papillary neoplastic) of thyroid gland cells from pre-obtained 16 feature parameters of image data. This paper applies the genetic algorithms to obtain the dominant feature parameters which have a great influence on discrimination between normal and abnormal cells. This paper shows the effectiveness of proposed method to 240 thyroid gland cells(60 normal cells, 120 follicular neoplastic cells and 60 papillary neoplastic cells) and new dominant feature parameters obtained by genetic algorithms. As a consequence of using the proposed method, average recognition rate of 88.75 % was obtained.