A BaSiC Tool for Background and Shading Correction of Optical Microscopy Images

Related tags

Deep LearningBaSiC
Overview

BaSiC

Matlab code accompanying

A BaSiC Tool for Background and Shading Correction of Optical Microscopy Images

by Tingying Peng, Kurt Thorn, Timm Schroeder, Lichao Wang, Fabian J Theis, Carsten Marr*, Nassir Navab*, Nature Communication 8:14836 (2017). doi: 10.1038/ncomms14836.

BaSiC is licensed under

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License

It is free for academic use and please contact us for any commercial use.

Usage

BaSiC corrects both spatial uneven illumination of microscopy images and temporal background bleaching for time-lapse movies.

Demo

Download demo data examples from Dropbox and run matlab files under example folder.

ImageJ/Fiji Plugin

BaSiC is also available as a ImageJ/Fiji Plugin.

Installation instruction

Note: If you do not have Fiji installed on your computer, you can download it from Fiji website.

Install via Fiji Updater

  1. Start Fiji and run the updater ("Help->Update Fiji")
  2. Select the "Manage Update Sites" button at the bottom-left of the updater window
  3. Scroll the list of available update sites to find "BaSiC" (Note: If you cannot find "BaSiC" in the list, select "Add Update Sites", Change the name field from default "New" to "BaSiC", set the URL field to http://sites.imagej.net/BaSiC/)
  4. Check the box at the left of "BaSiC"
  5. Select "Close"
  6. Select "Apply Changes"
  7. Restart Fiji. BaSiC should appear in the Plugins menu.

From now on, running the Fiji updater will also check for BaSiC updates, and install them if they are available.

Install manually

Please download BaSiC Plugin from this repository.

  1. Copy “BaSiC_.jar” to the “$FIJIROOT/plugins” folder of your Fiji/ImageJ installation.
  2. Copy all dependent jar files in the "Dependent" folder to your Fiji/ImageJ "$FIJIROOT/jars" directory.

Troubleshooting

If you get the error message

"java.lang.NoSuchMethodError: edu.emory.mathcs.utils.ConcurrencyUtils.submit"

make sure that in your Fiji/ImageJ "$FIJIROOT/jars" directory, there is only one version of each jar from the "Dependent" folder. Particularly, delete jtransforms-2.4.jar and replace it with our jtransform.jar.

Issues

If you have any issues concerning BaSiC, please report them in the Issues section of this GitHub repository and we will try to find a solution.

PyBaSiC

Planed and in progress

Owner
Marr Lab
Marr Lab
Boston House Prediction Valuation Tool

Boston-House-Prediction-Valuation-Tool From Below Anlaysis The Valuation Tool is Designed Correlation Matrix Regrssion Analysis Between Target Vs Pred

0 Sep 09, 2022
Advancing mathematics by guiding human intuition with AI

Advancing mathematics by guiding human intuition with AI This repo contains two colab notebooks which accompany the paper, available online at https:/

DeepMind 315 Dec 26, 2022
A simple implementation of Kalman filter in Multi Object Tracking

kalman Filter in Multi-object Tracking A simple implementation of Kalman filter in Multi Object Tracking 本实现是在https://github.com/liuchangji/kalman-fil

124 Dec 29, 2022
A list of awesome PyTorch scholarship articles, guides, blogs, courses and other resources.

Awesome PyTorch Scholarship Resources A collection of awesome PyTorch and Python learning resources. Contributions are always welcome! Course Informat

Arnas Gečas 302 Dec 03, 2022
Multispectral Object Detection with Yolov5

Multispectral-Object-Detection Intro Official Code for Cross-Modality Fusion Transformer for Multispectral Object Detection. Multispectral Object Dete

Richard Fang 121 Jan 01, 2023
This project is used for the paper Differentiable Programming of Isometric Tensor Network

This project is used for the paper "Differentiable Programming of Isometric Tensor Network". (arXiv:2110.03898)

Chenhua Geng 15 Dec 13, 2022
Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency

Contrastive Learning of Image Representations with Cross-Video Cycle-Consistency This is a official implementation of the CycleContrast introduced in

13 Nov 14, 2022
A higher performance pytorch implementation of DeepLab V3 Plus(DeepLab v3+)

A Higher Performance Pytorch Implementation of DeepLab V3 Plus Introduction This repo is an (re-)implementation of Encoder-Decoder with Atrous Separab

linhua 326 Nov 22, 2022
The ARCA23K baseline system

ARCA23K Baseline System This is the source code for the baseline system associated with the ARCA23K dataset. Details about ARCA23K and the baseline sy

4 Jul 02, 2022
Tweesent-back - Tweesent backend uses fastAPI as the web framework

TweeSent Backend Tweesent backend. This repo uses fastAPI as the web framework.

0 Mar 26, 2022
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)

StarGAN v2 - Official PyTorch Implementation StarGAN v2: Diverse Image Synthesis for Multiple Domains Yunjey Choi*, Youngjung Uh*, Jaejun Yoo*, Jung-W

Clova AI Research 3.1k Jan 09, 2023
Social Network Ads Prediction

Social network advertising, also social media targeting, is a group of terms that are used to describe forms of online advertising that focus on social networking services.

Khazar 2 Jan 28, 2022
[CoRL 21'] TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo

TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo Lukas Koestler1*    Nan Yang1,2*,†    Niclas Zeller2,3    Daniel Cremers1

TUM Computer Vision Group 744 Jan 04, 2023
Official PyTorch implementation of the ICRA 2021 paper: Adversarial Differentiable Data Augmentation for Autonomous Systems.

Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen

Manli 3 Oct 15, 2022
CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021

CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/

Xavier Bresson 165 Oct 25, 2022
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners This repository is built upon BEiT, thanks very much! Now, we on

Zhiliang Peng 2.3k Jan 04, 2023
Machine-in-the-Loop Rewriting for Creative Image Captioning

Machine-in-the-Loop Rewriting for Creative Image Captioning Data Annotated sources of data used in the paper: Data Source URL Mohammed et al. Link Gor

Vishakh P 6 Jul 24, 2022
a baseline to practice

ccks2021_track3_baseline a baseline to practice 路径可能会有问题,自己改改 torch==1.7.1 pyhton==3.7.1 transformers==4.7.0 cuda==11.0 this is a baseline, you can fi

45 Nov 23, 2022
Supervised Contrastive Learning for Product Matching

Contrastive Product Matching This repository contains the code and data download links to reproduce the experiments of the paper "Supervised Contrasti

Web-based Systems Group @ University of Mannheim 18 Dec 10, 2022
Interactive Image Segmentation via Backpropagating Refinement Scheme

Won-Dong Jang and Chang-Su Kim, Interactive Image Segmentation via Backpropagating Refinement Scheme, CVPR 2019

Won-Dong Jang 85 Sep 15, 2022