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AISO: Annotation of Image Segments with Ontologies.

Nikhil Tej Lingutla1, Justin Preece2, Sinisa Todorovic1

  • 1School of Electrical Engineering and Computer Science, Kelley Engineering Center, Oregon State University, Corvallis, OR 97331-2902 USA.

Journal of Biomedical Semantics
|January 14, 2015
PubMed
Summary
This summary is machine-generated.

Researchers can now annotate biological images with ontology terms using the new Annotation of Image Segments with Ontologies (AISO) software. This tool facilitates feature identification and annotation for improved data mining and machine learning applications.

Keywords:
Computer visionImage annotationImage curationImage segmentationMachine learningPlant anatomyPlant ontologySemantic webWeb services

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Area of Science:

  • Biological imaging
  • Bioinformatics
  • Computational biology

Background:

  • Biological collections generate large volumes of digital images from high-throughput screening and genome-phenome experiments.
  • Image annotations often use free text and lack precise feature localization, hindering computational analysis.
  • A tool is needed to delineate image features and annotate them with standardized ontology terms.

Purpose of the Study:

  • To develop a software tool for segmenting and annotating digital images using ontology terms.
  • To enable precise feature identification and annotation for enhanced biological data analysis.

Main Methods:

  • Development of a novel Java-based desktop application named "Annotation of Image Segments with Ontologies" (AISO).
  • The software allows users to delineate image segments and annotate them with controlled vocabulary from ontologies.

Main Results:

  • AISO is a freely available, cross-platform application for image segmentation and ontology-based annotation.
  • The tool facilitates the creation of semantically rich image annotations.

Conclusions:

  • AISO enhances the computational value of annotated biological images.
  • Applications include biological data mining, machine learning, and comparative analyses.