[HTML][HTML] Detection of breast cancer on digital histopathology images: Present status and future possibilities
MA Aswathy, M Jagannath - Informatics in Medicine Unlocked, 2017 - Elsevier
Breast cancer is a very common type of cancer in women around the world and more so in
India. It affects not only women but also men. In India, we have a very disturbing trend of …
India. It affects not only women but also men. In India, we have a very disturbing trend of …
Explainable AI (xAI) for anatomic pathology
Pathologists are adopting whole slide images (WSIs) for diagnosis, thanks to recent FDA
approval of WSI systems as class II medical devices. In response to new market forces and …
approval of WSI systems as class II medical devices. In response to new market forces and …
Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features
Background Histopathology image analysis is a gold standard for cancer recognition and
diagnosis. Automatic analysis of histopathology images can help pathologists diagnose …
diagnosis. Automatic analysis of histopathology images can help pathologists diagnose …
Gland instance segmentation using deep multichannel neural networks
Objective: A new image instance segmentation method is proposed to segment individual
glands (instances) in colon histology images. This process is challenging since the glands …
glands (instances) in colon histology images. This process is challenging since the glands …
Deep convolutional activation features for large scale brain tumor histopathology image classification and segmentation
We propose a simple, efficient and effective method using deep convolutional activation
features (CNNs) to achieve stat-of-the-art classification and segmentation for the MICCAI …
features (CNNs) to achieve stat-of-the-art classification and segmentation for the MICCAI …
Histopathological image classification using discriminative feature-oriented dictionary learning
In histopathological image analysis, feature extraction for classification is a challenging task
due to the diversity of histology features suitable for each problem as well as presence of …
due to the diversity of histology features suitable for each problem as well as presence of …
[PDF][PDF] Histopathological image analysis using image processing techniques: An overview
AD Belsare, MM Mushrif - Signal & Image Processing, 2012 - researchgate.net
This paper reviews computer assisted histopathology image analysis for cancer detection
and classification. Histopathology refers to the examination of invasive or less invasive …
and classification. Histopathology refers to the examination of invasive or less invasive …
Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization
Segmentation of histopathology sections is a necessary preprocessing step for digital
pathology. Due to the large variability of biological tissue, machine learning techniques have …
pathology. Due to the large variability of biological tissue, machine learning techniques have …
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 …
Multiplex immunofluorescence and the digital image analysis workflow for evaluation of the tumor immune environment in translational research
A robust understanding of the tumor immune environment has important implications for
cancer diagnosis, prognosis, research, and immunotherapy. Traditionally …
cancer diagnosis, prognosis, research, and immunotherapy. Traditionally …