Cargando…
Automated Detection and Classification of Oral Squamous Cell Carcinoma Using Deep Neural Networks
This work aims to classify normal and carcinogenic cells in the oral cavity using two different approaches with an eye towards achieving high accuracy. The first approach extracts local binary patterns and metrics derived from a histogram from the dataset and is fed to several machine-learning model...
Autores principales: | Ananthakrishnan, Balasundaram, Shaik, Ayesha, Kumar, Soham, Narendran, S. O., Mattu, Khushi, Kavitha, Muthu Subash |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10001077/ https://www.ncbi.nlm.nih.gov/pubmed/36900062 http://dx.doi.org/10.3390/diagnostics13050918 |
Ejemplares similares
-
Automated Bone Marrow Cell Classification for Haematological Disease Diagnosis Using Siamese Neural Network
por: Ananthakrishnan, Balasundaram, et al.
Publicado: (2022) -
A Foreground Prototype-Based One-Shot Segmentation of Brain Tumors
por: Balasundaram, Ananthakrishnan, et al.
Publicado: (2023) -
Deep Neural Network Models for Colon Cancer Screening
por: Kavitha, Muthu Subash, et al.
Publicado: (2022) -
Automated Truck Taxonomy Classification Using Deep Convolutional Neural Networks
por: Almutairi, Abdullah, et al.
Publicado: (2022) -
Deep vector-based convolutional neural network approach for automatic recognition of colonies of induced pluripotent stem cells
por: Kavitha, Muthu Subash, et al.
Publicado: (2017)