Neural Network Method for Detecting Blur in Histological Images

In this paper we consider the problem of detecting blurred regions in high-resolution whole slide histologic images. The proposed method is based on the use of a Fourier neural operator trained on the results of two simultaneously used approaches: blur detection using multiscale analysis of the disc...

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Veröffentlicht in:	Programming and computer software 2024-06, Vol.50 (3), p.224-230
Hauptverfasser:	Nazarenko, G. S., Krylov, A. S.
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Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Computer Science Datasets Deep learning Discrete cosine transform Image resolution Methods Multiscale analysis Neural networks Operating Systems Software Engineering Software Engineering/Programming and Operating Systems
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description	In this paper we consider the problem of detecting blurred regions in high-resolution whole slide histologic images. The proposed method is based on the use of a Fourier neural operator trained on the results of two simultaneously used approaches: blur detection using multiscale analysis of the discrete cosine transform coefficients and estimation of the degree of sharpness of objects edges in the image. The efficiency of the algorithm is confirmed on images from the datasets PATH-DT-MSU [1] and FocusPath [2].
doi_str_mv	10.1134/S0361768824700026
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subjects	Algorithms Artificial Intelligence Computer Science Datasets Deep learning Discrete cosine transform Image resolution Methods Multiscale analysis Neural networks Operating Systems Software Engineering Software Engineering/Programming and Operating Systems
title	Neural Network Method for Detecting Blur in Histological Images
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