Applied sciences

Bulletin of the Polish Academy of Sciences Technical Sciences

Content

Bulletin of the Polish Academy of Sciences Technical Sciences | 2018 | 66 | No 6 (Special Section on Deep Learning: Theory and Practice)

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Abstract

The pathologists follow a systematic and partially manual process to obtain histological tissue sections from the biological tissue extracted from patients. This process is far from being perfect and can introduce some errors in the quality of the tissue sections (distortions, deformations, folds and tissue breaks). In this paper, we propose a deep learning (DL) method for the detection and segmentation of these damaged regions in whole slide images (WSIs). The proposed technique is based on convolutional neural networks (CNNs) and uses the U-net model to achieve the pixel-wise segmentation of these unwanted regions. The results obtained show that this technique yields satisfactory results and can be applied as a pre-processing step for automatic WSI analysis in order to prevent the use of the damaged areas in the evaluation processes.

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Authors and Affiliations

Z. Swiderska-Chadaj
T. Markiewicz
J. Gallego
G. Bueno
B. Grala
M. Lorent

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NEW PUBLICATION FEES
Articles submitted by December 31st, 2024: existing fee: 1500 PLN (and mandatory over-length charges of 230 PLN per page)
Articles submitted from January 1st, 2025: new fee: 2000 PLN (approx. 500 EUR- depending on the exchange rate) - a flat fee per paper up to 8 pages of the journal format (each additional page will be charged an additional 250 PLN).

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