Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Pesquisa Veterinária Brasileira

Lucas B. Moraes²  Fernando S. Osório¹  Felipe O. Salle²  Guilherme F. Souza²  Hamilton L.s. Moraes²  Luiz C.b. Fallavena¹  Luciana R. Santos¹  Carlos T.p. Salle² 

[1] ,Universidade Federal do Rio Grande do Sul Departamento de Medicina Animal Porto Alegre RS ,Brazil

关键词: Digital image analysis;    Gumboro;    bursa of Fabricius;    artificial neuronal network;    Análise digital de imagem;    Gumboro;    bursa de Fabricius;    rede neural artificial;   

DOI  :  10.1590/S0100-736X2010000400010

来源: SciELO

【 摘 要 】

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

【 授权许可】

CC BY-NC   
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