Cargando…
Deep fusion of gray level co-occurrence matrices for lung nodule classification
Lung cancer is a serious threat to human health, with millions dying because of its late diagnosis. The computerized tomography (CT) scan of the chest is an efficient method for early detection and classification of lung nodules. The requirement for high accuracy in analyzing CT scan images is a sig...
Autores principales: | Saihood, Ahmed, Karshenas, Hossein, Nilchi, Ahmad Reza Naghsh |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9521911/ https://www.ncbi.nlm.nih.gov/pubmed/36174073 http://dx.doi.org/10.1371/journal.pone.0274516 |
Ejemplares similares
-
Chaotic Particle Swarm Optimization with Mutation for Classification
por: Assarzadeh, Zahra, et al.
Publicado: (2015) -
Cauchy Based Matched Filter for Retinal Vessels Detection
por: Zolfagharnasab, Hooshiar, et al.
Publicado: (2014) -
Precise two-dimensional D-bar reconstructions of human chest and phantom tank via sinc-convolution algorithm
por: Abbasi, Mahdi, et al.
Publicado: (2012) -
Identification of masses in digital mammogram using gray level co-occurrence matrices
por: Mohd. Khuzi, A, et al.
Publicado: (2009) -
Multi-Perspective Hierarchical Deep-Fusion Learning Framework for Lung Nodule Classification
por: Sekeroglu, Kazim, et al.
Publicado: (2022)