title: Mid-level image representations for real-time heart view plane classification of echocardiograms.
abstract: In this paper, we explore mid-level image representations for real-time heart view plane classification of 2D echocardiogram ultrasound images. The proposed representations rely on bags of visual words, successfully used by the computer vision community in visual recognition problems. An important element of the proposed representations is the image sampling with large regions, drastically reducing the execution time of the image characterization procedure. Throughout an extensive set of experiments, we evaluate the proposed approach against different image descriptors for classifying four heart view planes. The results show that our approach is effective and efficient for the target problem, making it suitable for use in real-time setups. The proposed representations are also robust to different image transformations, e.g., downsampling, noise filtering, and different machine learning classifiers, keeping classification accuracy above 90%. Feature extraction can be performed in 30 fps or 60 fps in some cases. This paper also includes an in-depth review of the literature in the area of automatic echocardiogram view classification giving the reader a through comprehension of this field of study.
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil; Advanced Technologies Group, SAMSUNG Research Institute, Av. Cambacica, 1200, Building 1, Campinas, SP 13097-160, Brazil. Electronic address: o.penatti@samsung.com.
authors.forename: Otávio A B
authors.initials: OA
authors.lastname: Penatti
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Rafael de O
authors.initials: Rde O
authors.lastname: Werneck
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Waldir R
authors.initials: WR
authors.lastname: de Almeida
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Bernardo V
authors.initials: BV
authors.lastname: Stein
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Daniel V
authors.initials: DV
authors.lastname: Pazinato
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Pedro R
authors.initials: PR
authors.lastname: Mendes Júnior
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Ricardo da S
authors.initials: Rda S
authors.lastname: Torres
authors.affiliation: RECOD Lab., Institute of Computing (IC), University of Campinas (Unicamp), Av. Albert Einstein, 1251, Campinas, SP 13083-852, Brazil.
authors.forename: Anderson
authors.initials: A
authors.lastname: Rocha
mesh_terms: D000465:Algorithms; D004452:Echocardiography / Q000379:methods*; D006321:Heart / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D000069550:Machine Learning; D015233:Models, Statistical; D009206:Myocardium / Q000473:pathology*; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D015203:Reproducibility of Results
keywords: Echocardiography; Feature extraction; Image classification; Pattern analysis; Real-time systems