Edge enhancement nucleus and cytoplast contour detector of cervical smear images.
This paper presents an edge enhancement nucleus and cytoplast contour (EENCC) detector to enable cutting the nucleus and cytoplast from a cervical smear cell image. To clean up noises from an image, this paper proposes a trim-meaning filter that can effectively remove impulse and Gaussian noises but still preserves the sharpness of object boundaries. In addition, a bigroup enhancer is proposed to make a clear-cut separation of the pixels lying in-between two objects. A mean vector difference enhancer is presented to suppress the gradients of noises and also to brighten the gradients of object contours. What is more, a relative-distance-error measure is put forward to evaluate the segmentation error between the extracted and target object contours. The experimental results show that all the aforementioned techniques proposed have performed impressively. Other than for cervical smear images, these proposed techniques can also be utilized in object segmentation of other images.
Yang-Mao
Shys-Fan
SF
Department of Computer Science and Engineering, National Chung Hsing University, Taichung, Taiwan, ROC. wool@cs.nchu.edu.tw
Chan
Yung-Kuan
YK
Chu
Yen-Ping
YP
D000465:Algorithms; D001185:Artificial Intelligence; D002467:Cell Nucleus / Q000473:pathology*; D003593:Cytoplasm / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014407:Tumor Cells, Cultured; D002583:Uterine Cervical Neoplasms / Q000473:pathology*; D014626:Vaginal Smears / Q000379:methods*