A state-of-the-art survey of artificial neural networks for whole-slide image analysis: from popular convolutional neural networks to potential visual transformers

W Hu, X Li, C Li, R Li, T Jiang, H Sun, X Huang… - Computers in Biology …, 2023 - Elsevier
In recent years, with the advancement of computer-aided diagnosis (CAD) technology and
whole slide image (WSI), histopathological WSI has gradually played a crucial aspect in the …

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

Y **g, 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 …

A state-of-the-art survey of U-Net in microscopic image analysis: from simple usage to structure mortification

J Wu, W Liu, C Li, T Jiang, IM Shariful, Y Yao… - Neural Computing and …, 2024 - Springer
Microscopic image analysis technology helps solve the inadvertences of artificial traditional
methods in disease, wastewater treatment, and environmental change monitoring analysis …

[HTML][HTML] Few-shot learning based histopathological image classification of colorectal cancer

R Li, X Li, H Sun, J Yang, M Rahaman, M Grzegozek… - Intelligent …, 2024 - Elsevier
Background Colorectal cancer is a prevalent and deadly disease worldwide, posing
significant diagnostic challenges. Traditional histopathologic image classification is often …

Exploring feasibility of citric acid infused lignocellulosic waste derived from chestnut and water melon peels for phytofiltration of Eosin yellow dye from water

R Rehman, MS Hussain, A Abidin, AA Ghfar… - International Journal of …, 2024 - Elsevier
The adsorption efficiency of cheap, ecofriendly, and easily available agro-waste, Trapa
natans (Chestnut) and Citrullus lanatus (Watermelon) peels, has been investigated in their …

[HTML][HTML] Optimized detection and segmentation of nuclei in gastric cancer images using stain normalization and blurred artifact removal

O Martos, MZ Hoque, A Keskinarkaus, N Kemi… - … -Research and Practice, 2023 - Elsevier
Histological analysis with microscopy is the gold standard to diagnose and stage cancer,
where slides or whole slide images are analyzed for cell morphological and spatial features …

AATCT-IDS: A benchmark Abdominal Adipose Tissue CT Image Dataset for image denoising, semantic segmentation, and radiomics evaluation

Z Ma, C Li, T Du, L Zhang, D Tang, D Ma… - Computers in Biology …, 2024 - Elsevier
Background and objective: The metabolic syndrome induced by obesity is closely
associated with cardiovascular disease, and the prevalence is increasing globally, year by …

A high-level feature channel attention UNet network for cholangiocarcinoma segmentation from microscopy hyperspectral images

H Gao, M Yang, X Cao, Q Liu, P Xu - Machine Vision and Applications, 2023 - Springer
Pathological diagnosis is the gold standard for the diagnosis of cholangiocarcinoma. The
manual segmentation of pathology sections is time-consuming. Automatic segmentation has …

[HTML][HTML] Computer-aided colorectal cancer diagnosis: AI-driven image segmentation and classification

ÇB Erdaş - PeerJ Computer Science, 2024 - peerj.com
Colorectal cancer is an enormous health concern since it is among the most lethal types of
malignancy. The manual examination has its limitations, including subjectivity and data …

To pretrain or not to pretrain? a case study of domain-specific pretraining for semantic segmentation in histopathology

T Kataria, B Knudsen, S Elhabian - … Image Learning with Limited and Noisy …, 2023 - Springer
Annotating medical imaging datasets is costly, so fine-tuning (or transfer learning) is the
most effective method for digital pathology vision applications such as disease classification …