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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Automatic detection of motion blur in intravital video microscopy image sequences via directional statistics of log-Gabor energy maps

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Autor(es):
Ferrari, Ricardo J. [1] ; Villa Pinto, Carlos H. [1] ; Gregorio da Silva, Bruno C. [1] ; Bernardes, Danielle [2] ; Carvalho-Tavares, Juliana [2]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Fed Sao Carlos, Dept Comp Sci, BR-13565905 Sao Carlos, SP - Brazil
[2] Univ Fed Minas Gerais, Dept Physiol & Biophys, Belo Horizonte, MG - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING; v. 53, n. 2, p. 151-163, FEB 2015.
Citações Web of Science: 4
Resumo

Intravital microscopy is an important experimental tool for the study of cellular and molecular mechanisms of the leukocyte-endothelial interactions in the microcirculation of various tissues and in different inflammatory conditions of in vivo specimens. However, due to the limited control over the conditions of the image acquisition, motion blur and artifacts, resulting mainly from the heartbeat and respiratory movements of the in vivo specimen, will very often be present. This problem can significantly undermine the results of either visual or computerized analysis of the acquired video images. Since only a fraction of the total number of images are usually corrupted by severe motion blur, it is necessary to have a procedure to automatically identify such images in the video for either further restoration or removal. This paper proposes a new technique for the detection of motion blur in intravital video microscopy based on directional statistics of local energy maps computed using a bank of 2D log-Gabor filters. Quantitative assessment using both artificially corrupted images and real microscopy data were conducted to test the effectiveness of the proposed method. Results showed an area under the receiver operating characteristic curve (AUC) of 0.95 ( 95 % CI 0.93-0.97) when tested on 329 video images visually ranked by four observers. (AU)

Processo FAPESP: 12/17772-3 - Correção digital de artefatos de movimento em vídeo de microscopia intravital com aplicação na detecção automática de leucócitos
Beneficiário:Carlos Henrique Villa Pinto
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica