کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6920241 | 1447879 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automated analysis and classification of melanocytic tumor on skin whole slide images
ترجمه فارسی عنوان
تجزیه و تحلیل خودکار و طبقه بندی تومور ملانوسیتی بر روی تصاویر کل اسلاید پوست
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کلمات کلیدی
ملانوما، تقسیم بندی هسته، طبقه بندی بیوپسی، اپیدرم و درم،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
This paper presents a computer-aided technique for automated analysis and classification of melanocytic tumor on skin whole slide biopsy images. The proposed technique consists of four main modules. First, skin epidermis and dermis regions are segmented by a multi-resolution framework. Next, epidermis analysis is performed, where a set of epidermis features reflecting nuclear morphologies and spatial distributions is computed. In parallel with epidermis analysis, dermis analysis is also performed, where dermal cell nuclei are segmented and a set of textural and cytological features are computed. Finally, the skin melanocytic image is classified into different categories such as melanoma, nevus or normal tissue by using a multi-class support vector machine (mSVM) with extracted epidermis and dermis features. Experimental results on 66 skin whole slide images indicate that the proposed technique achieves more than 95% classification accuracy, which suggests that the technique has the potential to be used for assisting pathologists on skin biopsy image analysis and classification.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computerized Medical Imaging and Graphics - Volume 66, June 2018, Pages 124-134
Journal: Computerized Medical Imaging and Graphics - Volume 66, June 2018, Pages 124-134
نویسندگان
Hongming Xu, Cheng Lu, Richard Berendt, Naresh Jha, Mrinal Mandal,