EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising

Related tags

Deep LearningEDCNN
Overview

EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising

By Tengfei Liang, Yi Jin, Yidong Li, Tao Wang.

This repository is an official implementation of the paper EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising. arXiv IEEEXplore

Notes:

This repository provides model and loss implementation code, which can be easily integrated into the user's project.

Introduction

EDCNN is a new end-to-end Low-Dose CT Denoiser. Designed as the FCN structure, it can effectively realize the low-dose CT image denoising in the way of post-processing. With the noval edge enhancement module, densely connection and compound loss, the model has a good performance in preserving details and suppressing noise in this denoising task. (For more details, please refer to the original paper)


Fig. 1: Overall architecture of the proposed EDCNN model.

Denoised results

For fairness, we choose the REDCNN, WGAN and CPCE for comparison, because of their design of the single model, which is the same as our EDCNN model. All these models adopt the structure of convolutional neural networks.


Fig. 2: Comparison with existing Models on the AAPM-Mayo Dataset.

Citing EDCNN

If you find EDCNN useful in your research, please consider citing:

@INPROCEEDINGS{9320928,
  author={T. {Liang} and Y. {Jin} and Y. {Li} and T. {Wang}},
  booktitle={2020 15th IEEE International Conference on Signal Processing (ICSP)}, 
  title={EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising}, 
  year={2020},
  volume={1},
  number={},
  pages={193-198},
  doi={10.1109/ICSP48669.2020.9320928}
}

License

This repository is released under the Apache 2.0 license. Please see the LICENSE file for more information.

Owner
workingcoder
workingcoder
Repo for EMNLP 2021 paper "Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression"

beyond-preserved-accuracy Repo for EMNLP 2021 paper "Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression" How to implemen

Kevin Canwen Xu 10 Dec 23, 2022
An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

Optimization for AI 176 Jan 07, 2023
LSSY量化交易系统

LSSY量化交易系统 该项目是本人3年来研究量化慢慢积累开发的一套系统,属于早期作品慢慢修改而来,仅供学习研究,回测分析,实盘交易部分未公开

55 Oct 04, 2022
The repo for reproducing Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study

ECIR Reproducibility Paper: Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study This code corresponds to the reproducibility

ielab 3 Mar 31, 2022
TensorFlow implementation of "Variational Inference with Normalizing Flows"

[TensorFlow 2] Variational Inference with Normalizing Flows TensorFlow implementation of "Variational Inference with Normalizing Flows" [1] Concept Co

YeongHyeon Park 7 Jun 08, 2022
PyTorch implementation of Self-supervised Contrastive Regularization for DG (SelfReg)

SelfReg PyTorch official implementation of Self-supervised Contrastive Regularization for Domain Generalization (SelfReg, https://arxiv.org/abs/2104.0

64 Dec 16, 2022
A collection of awesome resources image-to-image translation.

awesome image-to-image translation A collection of resources on image-to-image translation. Contributing If you think I have missed out on something (

876 Dec 28, 2022
Multiple Object Extraction from Aerial Imagery with Convolutional Neural Networks

This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi

Shunta Saito 255 Sep 07, 2022
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras

Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals

Federico Lopez 2 Jan 14, 2022
Java and SHACL code commented in the paper "Towards compliance checking in reified I/O logic via SHACL" submitted to ICAIL 2021

shRIOL The subfolder shRIOL contains Java files to execute the SHACL files on the OWL ontology. To compile the Java files: "javac -cp ./src/;./lib/* -

1 Dec 06, 2022
Python implementation of ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images, AAAI2022.

ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images Binh M. Le & Simon S. Woo, "ADD:

2 Oct 24, 2022
Yolov3 pytorch implementation

YOLOV3 Pytorch实现 在bubbliiing大佬代码的基础上进行了修改,添加了部分注释。 预训练模型 预训练模型来源于bubbliiing。 链接:https://pan.baidu.com/s/1ncREw6Na9ycZptdxiVMApw 提取码:appk 训练自己的数据集 按照VO

4 Aug 27, 2022
Neurolab is a simple and powerful Neural Network Library for Python

Neurolab Neurolab is a simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework

152 Dec 06, 2022
Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

Realtime Unsupervised Depth Estimation from an Image This is the caffe implementation of our paper "Unsupervised CNN for single view depth estimation:

Ravi Garg 227 Nov 28, 2022
Make your own game in a font!

Project structure. Included is a suite of tools to create font games. Tutorial: For a quick tutorial about how to make your own game go here For devel

Michael Mulet 125 Dec 04, 2022
[ICML 2021] A fast algorithm for fitting robust decision trees.

GROOT: Growing Robust Trees Growing Robust Trees (GROOT) is an algorithm that fits binary classification decision trees such that they are robust agai

Cyber Analytics Lab 17 Nov 21, 2022
This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

TransUNet This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Usage

1.4k Jan 04, 2023
SiT: Self-supervised vIsion Transformer

This repository contains the official PyTorch self-supervised pretraining, finetuning, and evaluation codes for SiT (Self-supervised image Transformer).

Sara Ahmed 275 Dec 28, 2022
Customised to detect objects automatically by a given model file(onnx)

LabelImg LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Annotations are saved as XML

Heeone Lee 1 Jun 07, 2022
A LiDAR point cloud cluster for panoptic segmentation

Divide-and-Merge-LiDAR-Panoptic-Cluster A demo video of our method with semantic prior: More information will be coming soon! As a PhD student, I don'

YimingZhao 65 Dec 22, 2022