Cargando…
Improving breast cancer diagnosis by incorporating raw ultrasound parameters into machine learning
The improved diagnostic accuracy of ultrasound breast examinations remains an important goal. In this study, we propose a biophysical feature-based machine learning method for breast cancer detection to improve the performance beyond a benchmark deep learning algorithm and to furthermore provide a c...
Autores principales: | Baek, Jihye, O’Connell, Avice M, Parker, Kevin J |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOP Publishing
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9855672/ https://www.ncbi.nlm.nih.gov/pubmed/36698865 http://dx.doi.org/10.1088/2632-2153/ac9bcc |
Ejemplares similares
-
Enhancing Breast Ultrasound Segmentation through Fine-tuning and Optimization Techniques: Sharp Attention UNet
por: Khaledyan, Donya, et al.
Publicado: (2023) -
Pilomatrixoma of the Adult Male Breast: A Rare Tumor with Typical Ultrasound Features
por: Hubeny, Charles M., et al.
Publicado: (2011) -
Color Doppler Ultrasound Improves Machine Learning Diagnosis of Breast Cancer
por: Moustafa, Afaf F., et al.
Publicado: (2020) -
Incorporation of a machine learning pathological diagnosis algorithm into the thyroid ultrasound imaging data improves the diagnosis risk of malignant thyroid nodules
por: Li, Wanying, et al.
Publicado: (2022) -
Cone-Beam Breast Computed Tomography: Time for a New Paradigm in Breast Imaging
por: O’Connell, Avice M., et al.
Publicado: (2021)