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 …
A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval
Benefiting from the large-scale archiving of digitized whole-slide images (WSIs), computer-
aided diagnosis has been well developed to assist pathologists in decision-making. Content …
aided diagnosis has been well developed to assist pathologists in decision-making. Content …
AI-guided auto-discovery of low-carbon cost-effective ultra-high performance concrete (UHPC)
This paper presents an AI-guided approach to automatically discover low-carbon cost-
effective ultra-high performance concrete (UHPC). The presented approach automates data …
effective ultra-high performance concrete (UHPC). The presented approach automates data …
A large-scale synthetic pathological dataset for deep learning-enabled segmentation of breast cancer
The success of training computer-vision models heavily relies on the support of large-scale,
real-world images with annotations. Yet such an annotation-ready dataset is difficult to …
real-world images with annotations. Yet such an annotation-ready dataset is difficult to …
A morphology focused diffusion probabilistic model for synthesis of histopathology images
PA Moghadam, S Van Dalen… - Proceedings of the …, 2023 - openaccess.thecvf.com
Visual microscopic study of diseased tissue by pathologists has been the cornerstone for
cancer diagnosis and prognostication for more than a century. Recently, deep learning …
cancer diagnosis and prognostication for more than a century. Recently, deep learning …
A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images
Mitosis counting of biopsies is an important biomarker for breast cancer patients, which
supports disease prognostication and treatment planning. Developing a robust mitotic cell …
supports disease prognostication and treatment planning. Developing a robust mitotic cell …
Attention-based generative adversarial network in medical imaging: A narrative review
J Zhao, X Hou, M Pan, H Zhang - Computers in Biology and Medicine, 2022 - Elsevier
As a popular probabilistic generative model, generative adversarial network (GAN) has
been successfully used not only in natural image processing, but also in medical image …
been successfully used not only in natural image processing, but also in medical image …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
A review: The detection of cancer cells in histopathology based on machine vision
W He, T Liu, Y Han, W Ming, J Du, Y Liu, Y Yang… - Computers in Biology …, 2022 - Elsevier
Abstract Machine vision is being employed in defect detection, size measurement, pattern
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …