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Towards simplified image analysis workflows

Mongis, Cyril

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Vorschau
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Abstract

Automated fluorescence microscopes enable biologists to acquire large amounts of biological images that contain clues to important scientific discoveries. Because these datasets can contain hundreds of images, computational approaches are required to efficiently analyse these datasets. However, many biologists lack the programming experience and knowledge necessary to design such approaches and therefore rely heavily on software solutions. Unfortunately, freely available software lack efficient dataset browsing capabilities and often suffer from bloated and complicated interfaces, preventing many biologists from easily analysing the data themselves. Here we introduce two pieces of software : PSFj and ImageJFX, that both offer clean, modern and practical interfaces that enable biologists to browse, assess, correct and analyse large image datasets by creating simplified image processing workflows. PSFj estimates the microscope quality, allowing the biologists to assess the reliability of the microscope data, while ImageJFX reduces the time spent on handling complicated datasets as well as increasing raising analysis reproducibility. By reducing the effort and time required to devise computational protocols, simplified image analysis software can truly lower the barriers of knowledge extraction and accelerate scientific discoveries.

Dokumententyp: Dissertation
Erstgutachter: Knop, Prof. Dr. Michael
Sonstige Beteiligte:
Mitarbeit
Name
Thesis advisor
Knop, Michael
Thesis advisor
Wittbrodt, Jochen
Ort der Veröffentlichung: Heidelberg, University
Tag der Prüfung: 25 April 2017
Erstellungsdatum: 17 Aug. 2017 10:15
Erscheinungsjahr: 2017
Institute/Einrichtungen: Fakultät für Biowissenschaften > Dekanat der Fakultät für Biowissenschaften
DDC-Sachgruppe: 004 Informatik
570 Biowissenschaften, Biologie
Normierte Schlagwörter: image, analysis, imagej, life science, image processing
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