Cargando…
Efficient breast cancer mammograms diagnosis using three deep neural networks and term variance
Breast cancer (BC) is spreading more and more every day. Therefore, a patient's life can be saved by its early discovery. Mammography is frequently used to diagnose BC. The classification of mammography region of interest (ROI) patches (i.e., normal, malignant, or benign) is the most crucial ph...
Autores principales: | Elkorany, Ahmed S., Elsharkawy, Zeinab F. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932150/ https://www.ncbi.nlm.nih.gov/pubmed/36792720 http://dx.doi.org/10.1038/s41598-023-29875-4 |
Ejemplares similares
-
COVIDetection-Net: A tailored COVID-19 detection from chest radiography images using deep learning
por: Elkorany, Ahmed S., et al.
Publicado: (2021) -
Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms
por: Cai, Hongmin, et al.
Publicado: (2019) -
Improved breast lesion detection in mammogram images using a deep neural network
por: Zhou, Wen, et al.
Publicado: (2023) -
New convolutional neural network model for screening and diagnosis of mammograms
por: Zhang, Chen, et al.
Publicado: (2020) -
Breast Cancer Mammograms Classification Using Deep Neural Network and Entropy-Controlled Whale Optimization Algorithm
por: Zahoor, Saliha, et al.
Publicado: (2022)