Code Pull requests Actions Projects Security Insights Additional navigation options master 1Branch 0Tags Code This branch is up to date withfeevos/resuneta:master. README License This repository contains source code for some of the models used in the manuscript of the (ResUNet-a) paper. ResUNe...
Directory Structure Complete models live in themodelsdirectory, specifically models d6 and d7 (conditioned multitasking). These are built from modules that are alive inresuneta/nndirectory. The Tanimoto loss function (with complement) is defined in fileresuneta/nn/loss/loss.pyInference demo (.ip...
Files master datasets-rgb images README.md dataset.py loss.py main.py model.py padding.py paper1.png predicted.py requirements.txt test-1.tif test-2.tif test-3.tif test-4.tif train.py utils.py
@misc{keras-unet-collection, author = {Sha, Yingkai}, title = {Keras-unet-collection}, year = {2021}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/yingkaisha/keras-unet-collection}}, doi = {10.5281/zenodo.5449801} }...
synthesis work with LRes-ResUnet and GAN (wgan-gp) in pytorch framework, which is a simple extension of our paperMedical Image Synthesis with Deep Convolutional Adversarial Networks. You are also welcome to visit our Tensorflow version through this link:https://github.com/ginobilinie/medSynthesis...
You are also welcome to visit our Tensorflow version through this link: https://github.com/ginobilinie/medSynthesis How to run the pytorch code The main entrance for the code is runCTRecon.py or runCTRecon3d.py (currently, the 2d/2.5d version is fine to run, and the discriminator for ...