On generating benchmark datasets for evaluation of segmentation and tracking algorithms in fluorescence microscopy

SVOBODA, David. On generating benchmark datasets for evaluation of segmentation and tracking algorithms in fluorescence microscopy. In SPlab workshop. 2013.

Basic information

• Original name: On generating benchmark datasets for evaluation of segmentation and tracking algorithms in fluorescence microscopy
• Authors: SVOBODA, David (203 Czech Republic, guarantor, belonging to the institution).
• Edition: SPlab workshop, 2013.

Other information

• Original language: English
• Type of outcome: Requested lectures
• Field of Study: 20200 2.2 Electrical engineering, Electronic engineering, Information engineering
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• RIV identification code: RIV/00216224:14330/13:00066770
• Organization unit: Faculty of Informatics
• Keywords in English: simulation; benchmark datasets; image processing; fluorescence microscopy
• Tags: cbia-web

Abstract

In fluorescence microscopy, the proper evaluation of image segmentation and tracking algorithms is still an open problem. As the ground truth for cell image data (and measurements on them) is not available in most experiments, the outputs of different image analysis methods can hardly be verified or compared to each other. We created a toolbox that can generate 3D digital phantoms of specific cellular components along with their corresponding images degraded by specific optics and electronics. The images can represent static scenes (fixed cell) as well as time-lapse sequences (living cells). Such synthetically generated images can serve as a benchmark dataset for measuring the quality of various segmentation and tracking algorithms.

Links

• GBP302/12/G157, research and development project: Name: Dynamika a organizace chromosomů během buněčného cyklu a při diferenciaci v normě a patologii

Investor: Czech Science Foundation