ArticleScientific reports2022
Differential diagnosis of thyroid nodule capsules using random forest guided selection of image features.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Polarization-Interference Jones Matrix Sensors of Layer-by-Layer Scanning of Polycrystalline Dehydrated Blood Films. Fundamental and Applied Aspects.Sensors (Basel, Switzerland) · 2025Article
- Widefield polarization-resolved second harmonic generation imaging of entire thyroid nodule sections for the detection of capsular invasion.Biomedical optics express · 2024Article
- Imaging of colorectal adenomas with pseudoinvasion and malignant polyps using two-photon excitation microscopy.Frontiers in oncology · 2024Article
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9 authors.
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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.
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