Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

A Shmatko, N Ghaffari Laleh, M Gerstung, JN Kather - Nature cancer, 2022 - nature.com
Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative
information from digital histopathology images. AI is expected to reduce workload for human …

Domain adaptation for medical image analysis: a survey

H Guan, M Liu - IEEE Transactions on Biomedical Engineering, 2021 - ieeexplore.ieee.org
Machine learning techniques used in computer-aided medical image analysis usually suffer
from the domain shift problem caused by different distributions between source/reference …

Deep neural network models for computational histopathology: A survey

CL Srinidhi, O Ciga, AL Martel - Medical image analysis, 2021 - Elsevier
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …

Medical image analysis based on deep learning approach

M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …

Digital pathology and computational image analysis in nephropathology

L Barisoni, KJ Lafata, SM Hewitt… - Nature Reviews …, 2020 - nature.com
The emergence of digital pathology—an image-based environment for the acquisition,
management and interpretation of pathology information supported by computational …

Generative adversarial networks in medical image segmentation: A review

S Xun, D Li, H Zhu, M Chen, J Wang, J Li… - Computers in biology …, 2022 - Elsevier
Abstract Purpose Since Generative Adversarial Network (GAN) was introduced into the field
of deep learning in 2014, it has received extensive attention from academia and industry …

[HTML][HTML] Development and evaluation of deep learning–based segmentation of histologic structures in the kidney cortex with multiple histologic stains

CP Jayapandian, Y Chen, AR Janowczyk, MB Palmer… - Kidney international, 2021 - Elsevier
The application of deep learning for automated segmentation (delineation of boundaries) of
histologic primitives (structures) from whole slide images can facilitate the establishment of …

Deep learning–based segmentation and quantification in experimental kidney histopathology

N Bouteldja, BM Klinkhammer, RD Bülow… - Journal of the …, 2021 - journals.lww.com
Background Nephropathologic analyses provide important outcomes-related data in
experiments with the animal models that are essential for understanding kidney disease …

Unpaired stain transfer using pathology-consistent constrained generative adversarial networks

S Liu, B Zhang, Y Liu, A Han, H Shi… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Pathological examination is the gold standard for the diagnosis of cancer. Common
pathological examinations include hematoxylin-eosin (H&E) staining and …

Generative adversarial networks in digital pathology: a survey on trends and future potential

ME Tschuchnig, GJ Oostingh, M Gadermayr - Patterns, 2020 - cell.com
Image analysis in the field of digital pathology has recently gained increased popularity. The
use of high-quality whole-slide scanners enables the fast acquisition of large amounts of …