کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1588665 1515127 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic recognition of fundamental tissues on histology images of the human cardiovascular system
ترجمه فارسی عنوان
شناخت اتوماتیک بافت های بنیادی بر روی تصاویر بافت شناسی دستگاه قلب و عروق انسان
کلمات کلیدی
بافت های پایه، تصاویر بافت شناسی پردازش تصاویر، طبقه بندی اتوماتیک، شناخت اتوماتیک،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد دانش مواد (عمومی)
چکیده انگلیسی
Cardiovascular disease is the leading cause of death worldwide. Therefore, techniques for improving diagnosis and treatment in this field have become key areas for research. In particular, approaches for tissue image processing may support education system and medical practice. In this paper, an approach to automatic recognition and classification of fundamental tissues, using morphological information is presented. Taking a 40× or 10× histological image as input, three clusters are created with the k-means algorithm using a structural tensor and the red and the green channels. Loose connective tissue, light regions and cell nuclei are recognised on 40× images. Then, the cell nuclei's features - shape and spatial projection - and light regions are used to recognise and classify epithelial cells and tissue into flat, cubic and cylindrical. In a similar way, light regions, loose connective and muscle tissues are recognised on 10× images. Finally, the tissue's function and composition are used to refine muscle tissue recognition. Experimental validation is then carried out by histologist following expert criteria, along with manually annotated images that are used as a ground-truth. The results revealed that the proposed approach classified the fundamental tissues in a similar way to the conventional method employed by histologists. The proposed automatic recognition approach provides for epithelial tissues a sensitivity of 0.79 for cubic, 0.85 for cylindrical and 0.91 for flat. Furthermore, the experts gave our method an average score of 4.85 out of 5 in the recognition of loose connective tissue and 4.82 out of 5 for muscle tissue recognition.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Micron - Volume 89, October 2016, Pages 1-8
نویسندگان
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