Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/235410
Type: Artigo de periódico
Title: Mid-level Image Representations For Real-time Heart View Plane Classification Of Echocardiograms.
Author: Penatti, Otávio A B
Werneck, Rafael de O
de Almeida, Waldir R
Stein, Bernardo V
Pazinato, Daniel V
Mendes Júnior, Pedro R
Torres, Ricardo da S
Rocha, Anderson
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.
Subject: Echocardiography
Feature Extraction
Image Classification
Pattern Analysis
Real-time Systems
Citation: Computers In Biology And Medicine. v. 66, p. 66-81, 2015-Nov.
Rights: embargo
Identifier DOI: 10.1016/j.compbiomed.2015.08.004
Address: http://www.ncbi.nlm.nih.gov/pubmed/26386547
Date Issue: 2015
Appears in Collections:Unicamp - Artigos e Outros Documentos

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