Cargando…
A quantization assisted U-Net study with ICA and deep features fusion for breast cancer identification using ultrasonic data
Breast cancer is one of the leading causes of death in women worldwide—the rapid increase in breast cancer has brought about more accessible diagnosis resources. The ultrasonic breast cancer modality for diagnosis is relatively cost-effective and valuable. Lesion isolation in ultrasonic images is a...
Autores principales: | Meraj, Talha, Alosaimi, Wael, Alouffi, Bader, Rauf, Hafiz Tayyab, Kumar, Swarn Avinash, Damaševičius, Robertas, Alyami, Hashem |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8725669/ https://www.ncbi.nlm.nih.gov/pubmed/35036531 http://dx.doi.org/10.7717/peerj-cs.805 |
Ejemplares similares
-
AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery
por: Almadhor, Ahmad, et al.
Publicado: (2021) -
Dilated Semantic Segmentation for Breast Ultrasonic Lesion Detection Using Parallel Feature Fusion
por: Irfan, Rizwana, et al.
Publicado: (2021) -
Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition
por: Lal, Sheeba, et al.
Publicado: (2021) -
Detection of diabetic retinopathy using a fusion of textural and ridgelet features of retinal images and sequential minimal optimization classifier
por: Ramasamy, Lakshmana Kumar, et al.
Publicado: (2021) -
Hybrid Deep Learning Model for Endoscopic Lesion Detection and Classification Using Endoscopy Videos
por: Ayyaz, M Shahbaz, et al.
Publicado: (2021)