[HTML][HTML] Stain normalization methods for histopathology image analysis: A comprehensive review and experimental comparison

MZ Hoque, A Keskinarkaus, P Nyberg, T Seppänen - Information Fusion, 2024 - Elsevier
The advent of whole slide imaging has brought advanced computer-aided diagnosis via
medical imaging and artificial intelligence technologies in digital pathology. The …

Artificial intelligence-driven diagnosis of pancreatic cancer

BS Hameed, UM Krishnan - Cancers, 2022 - mdpi.com
Simple Summary Pancreatic cancer poses a grave threat to mankind, due to its poor
prognosis and aggressive nature. An accurate diagnosis is critical for implementing a …

BreaST-Net: Multi-class classification of breast cancer from histopathological images using ensemble of swin transformers

S Tummala, J Kim, S Kadry - Mathematics, 2022 - mdpi.com
Breast cancer (BC) is one of the deadly forms of cancer, causing mortality worldwide in the
female population. The standard imaging procedures for screening BC involve …

Current developments of artificial intelligence in digital pathology and its future clinical applications in gastrointestinal cancers

ANN Wong, Z He, KL Leung, CCK To, CY Wong… - Cancers, 2022 - mdpi.com
Simple Summary The rapid development of technology has enabled numerous applications
of artificial intelligence (AI), especially in medical science. Histopathological assessment of …

A comprehensive survey of intestine histopathological image analysis using machine vision approaches

Y Jing, C Li, T Du, T Jiang, H Sun, J Yang, L Shi… - Computers in Biology …, 2023 - Elsevier
Colorectal Cancer (CRC) is currently one of the most common and deadly cancers. CRC is
the third most common malignancy and the fourth leading cause of cancer death worldwide …

[HTML][HTML] The role of unpaired image-to-image translation for stain color normalization in colorectal cancer histology classification

N Altini, TM Marvulli, FA Zito, M Caputo… - Computer Methods and …, 2023 - Elsevier
Background Histological assessment of colorectal cancer (CRC) tissue is a crucial and
demanding task for pathologists. Unfortunately, manual annotation by trained specialists is a …

EBHI-Seg: A novel enteroscope biopsy histopathological hematoxylin and eosin image dataset for image segmentation tasks

L Shi, X Li, W Hu, H Chen, J Chen, Z Fan, M Gao… - Frontiers in …, 2023 - frontiersin.org
Background and purpose Colorectal cancer is a common fatal malignancy, the fourth most
common cancer in men, and the third most common cancer in women worldwide. Timely …

A comprehensive review of the deep learning-based tumor analysis approaches in histopathological images: segmentation, classification and multi-learning tasks

H Abdel-Nabi, M Ali, A Awajan, M Daoud, R Alazrai… - Cluster …, 2023 - Springer
Medical Imaging has become a vital technique that has been embraced in the diagnosis and
treatment process of cancer. Histopathological slides, which microscopically examine the …

Clinical applications of graph neural networks in computational histopathology: A review

X Meng, T Zou - Computers in Biology and Medicine, 2023 - Elsevier
Pathological examination is the optimal approach for diagnosing cancer, and with the
advancement of digital imaging technologies, it has spurred the emergence of …

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 …