Application of digital pathology‐based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response
In recent years, the application of advanced analytics, especially artificial intelligence (AI), to
digital H&E images, and other histological image types, has begun to radically change how …
digital H&E images, and other histological image types, has begun to radically change how …
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
We address the challenging problem of whole slide image (WSI) classification. WSIs have
very high resolutions and usually lack localized annotations. WSI classification can be cast …
very high resolutions and usually lack localized annotations. WSI classification can be cast …
Artificial intelligence and cellular segmentation in tissue microscopy images
With applications in object detection, image feature extraction, image classification, and
image segmentation, artificial intelligence is facilitating high-throughput analysis of image …
image segmentation, artificial intelligence is facilitating high-throughput analysis of image …
Diagnose like a pathologist: Transformer-enabled hierarchical attention-guided multiple instance learning for whole slide image classification
Multiple Instance Learning (MIL) and transformers are increasingly popular in
histopathology Whole Slide Image (WSI) classification. However, unlike human pathologists …
histopathology Whole Slide Image (WSI) classification. However, unlike human pathologists …
Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis
H Xiang, J Shen, Q Yan, M Xu, X Shi, X Zhu - Medical Image Analysis, 2023 - Elsevier
Recently, convolutional neural networks (CNNs) directly using whole slide images (WSIs) for
tumor diagnosis and analysis have attracted considerable attention, because they only …
tumor diagnosis and analysis have attracted considerable attention, because they only …
Label-efficient deep learning in medical image analysis: Challenges and future directions
Deep learning has seen rapid growth in recent years and achieved state-of-the-art
performance in a wide range of applications. However, training models typically requires …
performance in a wide range of applications. However, training models typically requires …
Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation
The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts
ranging from cancers to chronic inflammations, as evidenced by many studies. Quantifying …
ranging from cancers to chronic inflammations, as evidenced by many studies. Quantifying …
Mueller matrix imaging for collagen scoring in mice model of pregnancy
Preterm birth risk is associated with early softening of the uterine cervix in pregnancy due to
the accelerated remodeling of collagen extracellular matrix. Studies of mice model of …
the accelerated remodeling of collagen extracellular matrix. Studies of mice model of …
Microenvironment-mediated cancer dormancy: Insights from metastability theory
Dormancy is an evolutionarily conserved protective mechanism widely observed in nature. A
pathological example is found during cancer metastasis, where cancer cells disseminate …
pathological example is found during cancer metastasis, where cancer cells disseminate …
Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization
High-quality whole slide scanners used for animal and human pathology scanning are
expensive and can produce massive datasets, which limits the access to and adoption of …
expensive and can produce massive datasets, which limits the access to and adoption of …