Generative adversarial networks in medical image augmentation: a review
Object With the development of deep learning, the number of training samples for medical
image-based diagnosis and treatment models is increasing. Generative Adversarial …
image-based diagnosis and treatment models is increasing. Generative Adversarial …
Generative adversarial networks in digital histopathology: current applications, limitations, ethical considerations, and future directions
Generative adversarial networks (GANs) have gained significant attention in the field of
image synthesis, particularly in computer vision. GANs consist of a generative model and a …
image synthesis, particularly in computer vision. GANs consist of a generative model and a …
Synthesis of diagnostic quality cancer pathology images by generative adversarial networks
Deep learning‐based computer vision methods have recently made remarkable
breakthroughs in the analysis and classification of cancer pathology images. However, there …
breakthroughs in the analysis and classification of cancer pathology images. However, there …
Selective synthetic augmentation with HistoGAN for improved histopathology image classification
Histopathological analysis is the present gold standard for precancerous lesion diagnosis.
The goal of automated histopathological classification from digital images requires …
The goal of automated histopathological classification from digital images requires …
[HTML][HTML] Generative adversarial networks in digital pathology and histopathological image processing: a review
Digital pathology is gaining prominence among the researchers with developments in
advanced imaging modalities and new technologies. Generative adversarial networks …
advanced imaging modalities and new technologies. Generative adversarial networks …
Exploring data mining and machine learning in gynecologic oncology
F Idlahcen, A Idri, E Goceri - Artificial Intelligence Review, 2024 - Springer
Gynecologic (GYN) malignancies are gaining new and much-needed attention, perpetually
fueling literature. Intra-/inter-tumor heterogeneity and “frightened” global distribution by race …
fueling literature. Intra-/inter-tumor heterogeneity and “frightened” global distribution by race …
Dual-path network with synergistic grouping loss and evidence driven risk stratification for whole slide cervical image analysis
Cervical cancer has been one of the most lethal cancers threatening women's health.
Nevertheless, the incidence of cervical cancer can be effectively minimized with preventive …
Nevertheless, the incidence of cervical cancer can be effectively minimized with preventive …
Opportunities and challenges of synthetic data generation in oncology
Widespread interest in artificial intelligence (AI) in health care has focused mainly on
deductive systems that analyze available real-world data to discover patterns not otherwise …
deductive systems that analyze available real-world data to discover patterns not otherwise …
Deepfake histologic images for enhancing digital pathology
A pathologist's optical microscopic examination of thinly cut, stained tissue on glass slides
prepared from a formalin-fixed paraffin-embedded tissue blocks is the gold standard for …
prepared from a formalin-fixed paraffin-embedded tissue blocks is the gold standard for …
Synthetic augmentation with large-scale unconditional pre-training
Deep learning based medical image recognition systems often require a substantial amount
of training data with expert annotations, which can be expensive and time-consuming to …
of training data with expert annotations, which can be expensive and time-consuming to …