کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
530126 869745 2012 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Unsupervised segmentation and classification of cervical cell images
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Unsupervised segmentation and classification of cervical cell images
چکیده انگلیسی

The Pap smear test is a manual screening procedure that is used to detect precancerous changes in cervical cells based on color and shape properties of their nuclei and cytoplasms. Automating this procedure is still an open problem due to the complexities of cell structures. In this paper, we propose an unsupervised approach for the segmentation and classification of cervical cells. The segmentation process involves automatic thresholding to separate the cell regions from the background, a multi-scale hierarchical segmentation algorithm to partition these regions based on homogeneity and circularity, and a binary classifier to finalize the separation of nuclei from cytoplasm within the cell regions. Classification is posed as a grouping problem by ranking the cells based on their feature characteristics modeling abnormality degrees. The proposed procedure constructs a tree using hierarchical clustering, and then arranges the cells in a linear order by using an optimal leaf ordering algorithm that maximizes the similarity of adjacent leaves without any requirement for training examples or parameter adjustment. Performance evaluation using two data sets show the effectiveness of the proposed approach in images having inconsistent staining, poor contrast, and overlapping cells.


► Automating the diagnosis of cancerous cells is an open problem.
► We present a generic parameter-free segmentation algorithm for delineating the cells.
► We describe an unsupervised approach for categorizing the cells via ranking.
► The proposed methodologies are robust to inconsistent staining and poor contrast.
► Experiments show good results on images with overlapping cells.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 45, Issue 12, December 2012, Pages 4151–4168
نویسندگان
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