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