Cargando…
Fuzzy-C-Means Clustering Based Segmentation and CNN-Classification for Accurate Segmentation of Lung Nodules
OBJECTIVE: Accurate segmentation of abnormal and healthy lungs is very crucial for a steadfast computer-aided disease diagnostics. METHODS: For this purpose a stack of chest CT scans are processed. In this paper, novel methods are proposed for segmentation of the multimodal grayscale lung CT scan. I...
Autores principales: | K, Jalal Deen, R, Ganesan, A, Merline |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
West Asia Organization for Cancer Prevention
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648392/ https://www.ncbi.nlm.nih.gov/pubmed/28749127 http://dx.doi.org/10.22034/APJCP.2017.18.7.1869 |
Ejemplares similares
-
Accurate Identification of Tomograms of Lung Nodules Using CNN: Influence of the Optimizer, Preprocessing and Segmentation
por: Loeza Mejía, Cecilia Irene, et al.
Publicado: (2020) -
An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm
por: Chowdhary, Chiranji Lal, et al.
Publicado: (2020) -
The Comparison of Clustering Algorithms K-Means and Fuzzy C-Means for Segmentation Retinal Blood Vessels
por: Wiharto, Wiharto, et al.
Publicado: (2020) -
Efficient Fuzzy C-Means Architecture for Image Segmentation
por: Li, Hui-Ya, et al.
Publicado: (2011) -
Performance evaluation of spatial fuzzy C-means clustering algorithm on GPU for image segmentation
por: Ali, Noureddine Ait, et al.
Publicado: (2022)