Computational analysis of histological images from hematoxylin and eosin-stained oral epithelial dysplasia tissue sections

Oral epithelial dysplasia is a precancerous lesion that presents alterations in the shape and size of cell nuclei and can be graded as mild, moderate and severe. The conventional process for diagnosis of this lesion is complex, time-consuming and subject to errors. The use of digital systems in hist...

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Veröffentlicht in:	Expert systems with applications 2022-05, Vol.193, p.116456, Article 116456
Hauptverfasser:	Silva, Adriano Barbosa, Martins, Alessandro Santana, Tosta, Thaína Aparecida Azevedo, Neves, Leandro Alves, Servato, João Paulo Silva, de Araújo, Marcelo Sivieri, de Faria, Paulo Rogério, do Nascimento, Marcelo Zanchetta
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial neural networks Classification Convolutional neural network Digital systems Dysplasia Feature extraction Histological image Image segmentation Lesions Machine learning Methodology Morphology Nuclei (cytology) Object recognition Oral cavity Polynomial classifier Polynomials
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