Efficient B-mode Ultrasound Image Reconstruction Using CNN

Efficient B-mode Ultrasound Image Reconstruction from Sub-sampled RF Data using Deep Learning
593 descargas
Actualizado 26 Nov 2018

Paper
Yoon, Yeo Hun, Shujaat Khan, Jaeyoung Huh, and Jong Chul Ye. "Efficient B-mode Ultrasound Image Reconstruction from Sub-sampled RF Data using Deep Learning." IEEE transactions on medical imaging (2018).
Implementation
MatConvNet (matconvnet-1.0-beta24)
Please run the matconvnet-1.0-beta24/matlab/vl_compilenn.m file to compile matconvnet.
There is instruction on "http://www.vlfeat.org/matconvnet/mfiles/vl_compilenn/"
Please run the installation setup (install.m) and run some training examples.
Trained network
Trained network for 'SC2xRX4 (down-sampling) CNN' is uploaded.
Test data
Test data file is placed in 'data\cnn_sparse_view_init_multi_normal_dsr2_input64' folder.
The dimension of data are as follows -- Test_data = 64x384x1x2304 (channel x scanline x frame x depth)
To perform a test using proposed algorithm

-> Use 'DNN4x1_TestVal' as input data

-> Run 'MAIN_RECONSTRUCTION.m

-> You will get the reconstructed RF data in the 'data\cnn_sparse_view_init_multi_normal_dsr2_input64' directory.

-> Using standard delay-and-sum (DAS) beam-forming code construct a B-mode image. For our experiments we used a DAS beam-forming code provided by (Alpinion Co., Korea). A similar code can be downloaded from ('http://www.ultrasoundtoolbox.com/').

Citar como

Yoon, Yeo Hun, et al. “Efficient B-Mode Ultrasound Image Reconstruction from Sub-Sampled RF Data Using Deep Learning.” IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers (IEEE), 2018, pp. 1–1, doi:10.1109/tmi.2018.2864821.

Ver más estilos
Compatibilidad con la versión de MATLAB
Se creó con R2018b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

No se pueden descargar versiones que utilicen la rama predeterminada de GitHub

Versión Publicado Notas de la versión
1.0.1

- citation information update

1.0.0

Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o notificar algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.