Cargando…
Breast Ultrasound Image Synthesis using Deep Convolutional Generative Adversarial Networks
Deep convolutional generative adversarial networks (DCGANs) are newly developed tools for generating synthesized images. To determine the clinical utility of synthesized images, we generated breast ultrasound images and assessed their quality and clinical value. After retrospectively collecting 528...
Autores principales: | Fujioka, Tomoyuki, Mori, Mio, Kubota, Kazunori, Kikuchi, Yuka, Katsuta, Leona, Adachi, Mio, Oda, Goshi, Nakagawa, Tsuyoshi, Kitazume, Yoshio, Tateishi, Ukihide |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6963542/ https://www.ncbi.nlm.nih.gov/pubmed/31698748 http://dx.doi.org/10.3390/diagnostics9040176 |
Ejemplares similares
-
Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging
por: Fujioka, Tomoyuki, et al.
Publicado: (2020) -
The Utility of Deep Learning in Breast Ultrasonic Imaging: A Review
por: Fujioka, Tomoyuki, et al.
Publicado: (2020) -
Virtual Navigator Real-Time Ultrasound Fusion Imaging with Positron Emission Tomography/Computed Tomography for Preoperative Breast Cancer
por: Mori, Mio, et al.
Publicado: (2021) -
Investigating the Image Quality and Utility of Synthetic MRI in the
Breast
por: Fujioka, Tomoyuki, et al.
Publicado: (2021) -
Detection and Diagnosis of Breast Cancer Using Artificial Intelligence Based Assessment of Maximum Intensity Projection Dynamic Contrast-Enhanced Magnetic Resonance Images
por: Adachi, Mio, et al.
Publicado: (2020)