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Iranian Journal of Medical Physics، جلد ۳، شماره ۱، صفحات ۱-۱۰

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عنوان انگلیسی Classification of Endometrial Images for Aiding the Diagnosis of Hyperplasia Using Logarithmic Gabor Wavelet
چکیده انگلیسی مقاله Introduction: The process of discriminating among benign and malignant hyperplasia begun with subjective methods using light microscopy and is now being continued with computerized morphometrical analysis requiring some features. One of the main features called Volume Percentage of Stroma (VPS) is obtained by calculating the percentage of stroma texture. Currently, this feature is calculated by pathologists on a manual basis. The proposed algorithm can automatically calculate VPS with a good precision. This procedure could be the first and an essential step of diagnosing endometrial hyperplasia in the field of pathology. Materials and Methods: In this paper, a method based on logarithmic Gabor wavelets and mathematical morphology is proposed for the segmentation of texture. Attaining maximum joint space-frequency resolution is highly significant in the process of texture segmentation. The ability of logarithmic Gabor filters in the discrimination of texture bands at different scales and orientations has been used to segment stroma texture which is mainly located in the middle frequency bands from glandular elements. In the proposed algorithm, the logarithmic Gabor filter bank applied on the microscopic endometrial images and mathematical morphology is used for denoising. The segmentation method is averaging the weighted and denoised Gabor filter outputs. Results: The images used in this method segment with a good precision and can be used by pathologists to calculate volume percentage of stroma as an aided diagnosis feature. A sensitivity of 95.3, specificity of 95.6, accuracy of 95.4%, PPV of 98.4% and NPV of 88% was achieved in distinguishing between benign and malignant hyperplasia based on VPS. Discussion and Conclusion: The proposed procedure could be the first and an essential step of diagnosing endometrial hyperplasia in pathology.Based on these experiments, the logarithmic Gabor wavelet is one of the most effective methods in texture segmentation that can easily extract the texture information from the middle frequency bands and make it available to the segmentation algorithm.
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نویسندگان مقاله b شریف | b. sharif
m.sc. in biomedical engineering, tehran university of medical sciences, tehran, iran.

سازمان اصلی تایید شده: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)

a احمدیان | a. ahmadian
assistant professor, physics and biomedical engineering dept., tehran university of medical sciences, tehran, iran. research center for science amp;amp; technology in medicine, imam khomeini hospital, tehran, iran

سازمان اصلی تایید شده: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)

محمدعلی عقابیان | m a oghabian
research center for science amp;amp; technology in medicine, imam khomeini hospital, tehran, iran. associate professor, physics and biomedical engineering, tehran university of medical sciences, tehran, iran.

سازمان اصلی تایید شده: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)

n ایزدی مود | n izadi mood
assistant professor, phathology dept., tehran university of medical sciences, tehran, iran

سازمان اصلی تایید شده: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)

m خوبدل | m. khoobdel
assistant professor, military health research center, baqiyatallah university of medical sciences, tehran, iran

سازمان اصلی تایید شده: دانشگاه علوم پزشکی بقیه الله (Baqiyatallah university of medical sciences)


نشانی اینترنتی http://ijmp.mums.ac.ir/article_8126.html
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Original Paper
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