[HTML][HTML] Recent advances of deep learning for computational histopathology: principles and applications
Simple Summary The histopathological image is widely considered as the gold standard for
the diagnosis and prognosis of human cancers. Recently, deep learning technology has …
the diagnosis and prognosis of human cancers. Recently, deep learning technology has …
[HTML][HTML] Closing the translation gap: AI applications in digital pathology
Recent advances in artificial intelligence show tremendous promise to improve the
accuracy, reproducibility, and availability of medical diagnostics across a number of medical …
accuracy, reproducibility, and availability of medical diagnostics across a number of medical …
[HTML][HTML] Quality control stress test for deep learning-based diagnostic model in digital pathology
B Schömig-Markiefka, A Pryalukhin, W Hulla… - Modern Pathology, 2021 - Elsevier
Digital pathology provides a possibility for computational analysis of histological slides and
automatization of routine pathological tasks. Histological slides are very heterogeneous …
automatization of routine pathological tasks. Histological slides are very heterogeneous …
[HTML][HTML] Best practice recommendations for the implementation of a digital pathology workflow in the anatomic pathology laboratory by the European Society of Digital …
F Fraggetta, V L'imperio, D Ameisen, R Carvalho… - Diagnostics, 2021 - mdpi.com
The interest in implementing digital pathology (DP) workflows to obtain whole slide image
(WSI) files for diagnostic purposes has increased in the last few years. The increasing …
(WSI) files for diagnostic purposes has increased in the last few years. The increasing …
Acute lymphoblastic leukemia detection based on adaptive unsharpening and deep learning
Computer Aided Diagnosis (CAD) systems are increasingly utilizing image analysis and
Deep Learning (DL) techniques, due to their high accuracy in several medical imaging …
Deep Learning (DL) techniques, due to their high accuracy in several medical imaging …
Autofocusing technologies for whole slide imaging and automated microscopy
Whole slide imaging (WSI) has moved digital pathology closer to diagnostic practice in
recent years. Due to the inherent tissue topography variability, accurate autofocusing …
recent years. Due to the inherent tissue topography variability, accurate autofocusing …
[HTML][HTML] Next-generation pathology using multiplexed immunohistochemistry: mapping tissue architecture at single-cell level
FM Bosisio, Y Van Herck, J Messiaen… - Frontiers in …, 2022 - frontiersin.org
Single-cell omics aim at charting the different types and properties of all cells in the human
body in health and disease. Over the past years, myriads of cellular phenotypes have been …
body in health and disease. Over the past years, myriads of cellular phenotypes have been …
Automatic quality evaluation of whole slide images for the practical use of whole slide imaging scanner
HM Shakhawat, T Nakamura, F Kimura… - ITE Transactions On …, 2020 - jstage.jst.go.jp
A whole slide imaging (WSI) scanner scans pathological-specimens to produce digital
images for monitor-based diagnosis and analysis. However, the image quality is sometimes …
images for monitor-based diagnosis and analysis. However, the image quality is sometimes …
Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies
Inconsistencies in the preparation of histology slides and whole‐slide images (WSIs) may
lead to challenges with subsequent image analysis and machine learning approaches for …
lead to challenges with subsequent image analysis and machine learning approaches for …
Blind image quality assessment for pathological microscopic image under screen and immersion scenarios
The high-quality pathological microscopic images are essential for physicians or
pathologists to make a correct diagnosis. Image quality assessment (IQA) can quantify the …
pathologists to make a correct diagnosis. Image quality assessment (IQA) can quantify the …