title: Active learning framework with iterative clustering for bioimage classification.
abstract: Advances in imaging systems have yielded a flood of images into the research field. A semi-automated facility can reduce the laborious task of classifying this large number of images. Here we report the development of a novel framework, CARTA (Clustering-Aided Rapid Training Agent), applicable to bioimage classification that facilitates annotation and selection of features. CARTA comprises an active learning algorithm combined with a genetic algorithm and self-organizing map. The framework provides an easy and interactive annotation method and accurate classification. The CARTA framework enables classification of subcellular localization, mitotic phases and discrimination of apoptosis in images of plant and human cells with an accuracy level greater than or equal to annotators. CARTA can be applied to classification of magnetic resonance imaging of cancer cells or multicolour time-course images after surgery. Furthermore, CARTA can support development of customized features for classification, high-throughput phenotyping and application of various classification schemes dependent on the user's purpose.
authors.affiliation: Department of Integrated Biosciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Chiba 277-8562, Japan.
authors.forename: Natsumaro
authors.initials: N
authors.lastname: Kutsuna
authors.forename: Takumi
authors.initials: T
authors.lastname: Higaki
authors.forename: Sachihiro
authors.initials: S
authors.lastname: Matsunaga
authors.forename: Tomoshi
authors.initials: T
authors.lastname: Otsuki
authors.forename: Masayuki
authors.initials: M
authors.lastname: Yamaguchi
authors.forename: Hirofumi
authors.initials: H
authors.lastname: Fujii
authors.forename: Seiichiro
authors.initials: S
authors.lastname: Hasezawa
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence / Q000145:classification*; D058948:Cell Tracking / Q000145:classification / Q000295:instrumentation / Q000379:methods*; D002477:Cells / Q000737:chemistry* / Q000145:classification* / Q000166:cytology; D022082:Cellular Structures; D006367:HeLa Cells; D006801:Humans; D010363:Pattern Recognition, Automated / Q000145:classification / Q000379:methods*