[HTML][HTML] An aggregation of aggregation methods in computational pathology
Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide
images (WSIs) often process a large number of tiles (sub-images) and require aggregating …
images (WSIs) often process a large number of tiles (sub-images) and require aggregating …
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 …
the third most common malignancy and the fourth leading cause of cancer death worldwide …
Human-AI collaboration: the effect of AI delegation on human task performance and task satisfaction
Recent work has proposed artificial intelligence (AI) models that can learn to decide whether
to make a prediction for an instance of a task or to delegate it to a human by considering …
to make a prediction for an instance of a task or to delegate it to a human by considering …
EBHI-Seg: A novel enteroscope biopsy histopathological hematoxylin and eosin image dataset for image segmentation tasks
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 …
common cancer in men, and the third most common cancer in women worldwide. Timely …
[HTML][HTML] Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer
N Zamanitajeddin, M Jahanifar, M Bilal… - Medical Image …, 2024 - Elsevier
Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …
pathways, genetic subtypes, and mutations associated with CRC is crucial for precision …
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
Abstract Background and Objective: Early detection of colon adenomatous polyps is critically
important because correct detection of it significantly reduces the potential of developing …
important because correct detection of it significantly reduces the potential of developing …
A novel Heteromorphous convolutional neural network for automated assessment of tumors in colon and lung histopathology images
The automated assessment of tumors in medical image analysis encounters challenges due
to the resemblance of colon and lung tumors to non-mitotic nuclei and their heteromorphic …
to the resemblance of colon and lung tumors to non-mitotic nuclei and their heteromorphic …
EBHI: A new Enteroscope Biopsy Histopathological H&E Image Dataset for image classification evaluation
Background and purpose: Colorectal cancer has become the third most common cancer
worldwide, accounting for approximately 10% of cancer patients. Early detection of the …
worldwide, accounting for approximately 10% of cancer patients. Early detection of the …
[HTML][HTML] Artificial intelligence-based triage of large bowel biopsies can improve workflow
FG Mayall, MD Goodhead, L de Mendonça… - Journal of Pathology …, 2023 - Elsevier
Background Large bowel biopsies are one of the commonest types of biopsy specimen. We
describe a service evaluation study to test the feasibility of using artificial intelligence (AI) to …
describe a service evaluation study to test the feasibility of using artificial intelligence (AI) to …
[HTML][HTML] An effective colorectal polyp classification for histopathological images based on supervised contrastive learning
Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this
context, accurately distinguishing between adenomatous polyp subtypes, especially tubular …
context, accurately distinguishing between adenomatous polyp subtypes, especially tubular …