BIOIMAGE INFORMATICS: A REVIEW ON THE ADVANCEMENT OF ITS TECHNIQUES

Abstract

In recent years, the rapid accumulation of complex molecular and cellular microscopic images has created significant challenges for the image-computing community. Increasing attention has therefore been directed toward the development of novel image-processing, data-mining, database, and visualization techniques for extracting, comparing, searching, and managing biological information from these data-intensive resources. This emerging area of bioinformatics is known as bioimage informatics. This article reviews the advancement of bioimage informatics from several perspectives, including its applications, key techniques, available tools, databases, and other resources. Applications such as high-throughput and high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The major techniques supporting these applications include bioimage feature identification and extraction, image segmentation, tracking, registration, annotation, image mining, data management, and visualization. The article also provides an overview of representative bioimage databases, image-analysis tools, and other resources used in biological image analysis.