R-net: A Deep Convolutional Neural Network for Improving Photoacoustic Image Reconstruction
Python Codes* :
Requires Keras and TensorFlow
Training dataset was prepared by extracting patches from STARE, DRIVE, and CHASE retinal databases.
# Codes for U-net (Reference: Deep Convolutional Neural Network for Inverse Problems in Imaging)
This Python code is used as part of the work presented in:
[Sreedevi Gutta*, Jayasimha Talur*], Sandeep Kumar Kalva, Manojit Pramanik, R. Venkatesh Babu, and Phaneendra K. Yalavarthy, “R-net: A Deep Convolutional Neural Network for Improving Photoacoustic Image Reconstruction". [* equal contribution]
Created on: Aug 30, 2017
Updated on: Dec 18, 2017