User Tools

Site Tools


Sidebar

Top
Profile
Freelancing
Seminar
Courses -2016
Courses 2018-
Textbooks
Documents
Downloads (-2016)
Downloads (2016-)
Weblog
RSS aggregates
Discussions
Archives
日本語


EMBL BioImage Data Analysis

EuBIAS

NEUBIAS

—- Contact
CMCI Alumni
ALMF
EMBL Heidelberg
EMBL Intranet


Popularity Ranking


Timeline of @cmci_

cmci_ avatar

RT @CornellBiotech: Join us for the Fiji (ImageJ) Summer Workshop Aug 10-12 https://t.co/hRVTW6JJyL
About 3 days, 12 hours ago by: Kota Miura (@cmci_)

cmci_ avatar

RT @christlet: Extending the classic full-width at half-maximum (FWHM) method for estimating image resolution on sub-resolutive structures…
About 1 week, 4 days ago by: Kota Miura (@cmci_)

cmci_ avatar

RT @CiminiLab: I've made a Twitter Community for Bioimage Analysis- feel free to join and share widely! I'll fully admit this is an experim…
About 1 week, 6 days ago by: Kota Miura (@cmci_)

cmci_ avatar

RT @kjaMartens: We created a very simple method to get high precision and density in spectrally-resolved single-molecule localization micro…
About 1 month ago by: Kota Miura (@cmci_)

cmci_ avatar

RT @random_walker: There’s a reproducibility crisis brewing in almost every scientific field that has adopted machine learning. On July 28,…
About 1 month ago by: Kota Miura (@cmci_)

cmci_ avatar

@AthaleLab @IISERPune @serbonline @DBTIndia @IFCPAR @OfficialSICI @boschindia Congrats Prof. Chait!
About 1 month, 1 week ago by: Kota Miura (@cmci_)
documents:121019htm

2012 EMBO High-throughput Microscopy Practical Course

Dates: 2012.10.15-20 Place: ATC, EMBL Heidelberg

    1. With Andrea Boni @ Ellenberg Lab
    2. Abstract: The students will learn basics of image analysis of time lapse data. We will first go through preprocessing steps: filtering, noise reduction and background subtraction. We then move on to image thresholding and segmentation techniques, which allow us to objectively define region of interest (ROI) where the temporal dynamics of signal intensity are measured. Automation is an esseitial aspect in highthroughput imaging. In this session, students will be guided to learn how to automate the imaging processing steps that we went through manually. Scripting is necessary for automation. For this reason, a brief introduction to code ImageJ macro will be provided and students will learn to write a short macro that processes raw data and outputs results automatically.
  1. Demo script (written in Jython)
  2. Student ImageJ macro: example
documents/121019htm.txt · Last modified: 2016/05/24 12:46 (external edit)