کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10351488 | 864471 | 2013 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images
ترجمه فارسی عنوان
تشخیص کامپیوتری از سرطان پستان بر اساس تصاویر میکروسکوپ بیوپسی خوب سوزن
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کلمات کلیدی
تشخیص کامپیوتری، سرطان پستان، فراگیری ماشین، تقسیم بندی تصویر،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Prompt and widely available diagnostics of breast cancer is crucial for the prognosis of patients. One of the diagnostic methods is the analysis of cytological material from the breast. This examination requires extensive knowledge and experience of the cytologist. Computer-aided diagnosis can speed up the diagnostic process and allow for large-scale screening. One of the largest challenges in the automatic analysis of cytological images is the segmentation of nuclei. In this study, four different clustering algorithms are tested and compared in the task of fast nuclei segmentation. K-means, fuzzy C-means, competitive learning neural networks and Gaussian mixture models were incorporated for clustering in the color space along with adaptive thresholding in grayscale. These methods were applied in a medical decision support system for breast cancer diagnosis, where the cases were classified as either benign or malignant. In the segmented nuclei, 42 morphological, topological and texture features were extracted. Then, these features were used in a classification procedure with three different classifiers. The system was tested for classification accuracy by means of microscopic images of fine needle breast biopsies. In cooperation with the Regional Hospital in Zielona Góra, 500 real case medical images from 50 patients were collected. The acquired classification accuracy was approximately 96-100%, which is very promising and shows that the presented method ensures accurate and objective data acquisition that could be used to facilitate breast cancer diagnosis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 43, Issue 10, 1 October 2013, Pages 1563-1572
Journal: Computers in Biology and Medicine - Volume 43, Issue 10, 1 October 2013, Pages 1563-1572
نویسندگان
Marek Kowal, PaweÅ Filipczuk, Andrzej Obuchowicz, Józef Korbicz, Roman Monczak,