دورية أكاديمية
أعرض في EDS

Differential diagnosis of thyroid nodule capsules using random forest guided selection of image features

التفاصيل البيبلوغرافية
العنوان: Differential diagnosis of thyroid nodule capsules using random forest guided selection of image features
المؤلفون: Lucian G. Eftimie, Remus R. Glogojeanu, A. Tejaswee, Pavel Gheorghita, Stefan G. Stanciu, Augustin Chirila, George A. Stanciu, Angshuman Paul, Radu Hristu
المصدر: Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
بيانات النشر: Nature Portfolio, 2022.
سنة النشر: 2022
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: Abstract Microscopic evaluation of tissue sections stained with hematoxylin and eosin is the current gold standard for diagnosing thyroid pathology. Digital pathology is gaining momentum providing the pathologist with additional cues to traditional routes when placing a diagnosis, therefore it is extremely important to develop new image analysis methods that can extract image features with diagnostic potential. In this work, we use histogram and texture analysis to extract features from microscopic images acquired on thin thyroid nodule capsules sections and demonstrate how they enable the differential diagnosis of thyroid nodules. Targeted thyroid nodules are benign (i.e., follicular adenoma) and malignant (i.e., papillary thyroid carcinoma and its sub-type arising within a follicular adenoma). Our results show that the considered image features can enable the quantitative characterization of the collagen capsule surrounding thyroid nodules and provide an accurate classification of the latter’s type using random forest.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-022-25788-w
URL الوصول: https://doaj.org/article/dddfe2e735474e38a6e1293ec6fa039b
رقم الأكسشن: edsdoj.fe2e735474e38a6e1293ec6fa039b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-022-25788-w