Visualization and Analysis of Whole Slide Histological Images

In this paper we consider the problem of detecting blurred regions in high-resolution full-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].

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Visualization and Analysis of Whole Slide Histological Images

Cited by 4 publications

References 13 publications

Neural Network Method for Detecting Blur in Histological Images

Neural Network Method for Detecting Blur in Histological Images

Joint Super-resolution and Tissue Patch Classification for Whole Slide Histological Images

Neural Network Method for Detecting Blur in Histological Images

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