[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis

M Salvi, UR Acharya, F Molinari… - Computers in Biology and …, 2021 - Elsevier
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …

[HTML][HTML] Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

Y Nan, J Del Ser, S Walsh, C Schönlieb, M Roberts… - Information …, 2022 - Elsevier
Removing the bias and variance of multicentre data has always been a challenge in large
scale digital healthcare studies, which requires the ability to integrate clinical features …

The devil is in the details: Whole slide image acquisition and processing for artifacts detection, color variation, and data augmentation: A review

N Kanwal, F Pérez-Bueno, A Schmidt, K Engan… - Ieee …, 2022 - ieeexplore.ieee.org
Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis
of different types of cancer. The preparation and digitization of histological tissues leads to …

A review: The detection of cancer cells in histopathology based on machine vision

W He, T Liu, Y Han, W Ming, J Du, Y Liu, Y Yang… - Computers in Biology …, 2022 - Elsevier
Abstract Machine vision is being employed in defect detection, size measurement, pattern
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …

[HTML][HTML] Unstained tissue imaging and virtual hematoxylin and eosin staining of histologic whole slide images

S Koivukoski, U Khan, P Ruusuvuori, L Latonen - Laboratory Investigation, 2023 - Elsevier
Tissue structures, phenotypes, and pathology are routinely investigated based on histology.
This includes chemically staining the transparent tissue sections to make them visible to the …

Covalent organic framework based nanoagent for enhanced mild-temperature photothermal therapy

Q Sun, K Tang, L Song, Y Li, W Pan, N Li… - Biomaterials Science, 2021 - pubs.rsc.org
Photothermal therapy effectively ablates tumors by hyperthermia (> 50° C) under laser
irradiation. However, the hyperthermia may inevitably diffuse to the surrounding healthy …

Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization

B Li, A Keikhosravi, AG Loeffler, KW Eliceiri - Medical Image Analysis, 2021 - Elsevier
High-quality whole slide scanners used for animal and human pathology scanning are
expensive and can produce massive datasets, which limits the access to and adoption of …

[HTML][HTML] Bayesian K-SVD for H and E blind color deconvolution. Applications to stain normalization, data augmentation and cancer classification

F Pérez-Bueno, JG Serra, M Vega, J Mateos… - … Medical Imaging and …, 2022 - Elsevier
Stain variation between images is a main issue in the analysis of histological images. These
color variations, produced by different staining protocols and scanners in each laboratory …

DSCA-Net: Double-stage Codec Attention Network for automatic nuclear segmentation

Z Ye, B Hu, H Sui, M Mei, L Mei, R Zhou - Biomedical Signal Processing …, 2024 - Elsevier
The rapid and precise segmentation of cell nuclei from hematoxylin and eosin-stained tissue
images is an essential clinical undertaking with significant implications for various clinical …

A stain color normalization with robust dictionary learning for breast cancer histological images processing

TAA Tosta, AD Freitas, PR de Faria, LA Neves… - … Signal Processing and …, 2023 - Elsevier
Microscopic analyses of tissue samples are crucial for confirming the diagnosis of breast
cancer. The digitization of these samples has led to the development of computational …