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 …
[HTML][HTML] Systematic review of data-centric approaches in artificial intelligence and machine learning
P Singh - Data Science and Management, 2023 - Elsevier
Artificial intelligence (AI) relies on data and algorithms. State-of-the-art (SOTA) AI smart
algorithms have been developed to improve the performance of AI-oriented structures …
algorithms have been developed to improve the performance of AI-oriented structures …
[PDF][PDF] Generative adversarial network based data augmentation to improve cervical cell classification model
S Yu, S Zhang, B Wang, H Dun, L Xu, X Huang… - Math. Biosci …, 2021 - aimspress.com
The survival rate of cervical cancer can be improved by the early screening. However, the
screening is a heavy task for pathologists. Thus, automatic cervical cell classification model …
screening is a heavy task for pathologists. Thus, automatic cervical cell classification model …
Synchronous medical image augmentation framework for deep learning-based image segmentation
J Chen, N Yang, Y Pan, H Liu, Z Zhang - Computerized Medical Imaging …, 2023 - Elsevier
Various deep learning (DL) models are widely applied in medical image analysis, and their
performance depends on the scale and diversity of available training data. However …
performance depends on the scale and diversity of available training data. However …
A Unified Framework for Generative Data Augmentation: A Comprehensive Survey
Generative data augmentation (GDA) has emerged as a promising technique to alleviate
data scarcity in machine learning applications. This thesis presents a comprehensive survey …
data scarcity in machine learning applications. This thesis presents a comprehensive survey …
A two-stage approach solo_GAN for overlapping cervical cell segmentation based on single-cell identification and boundary generation
Accurate cell segmentation is a pivotal step throughout the cervical cancer treatment
continuum, encompassing early screening, guiding treatment decisions, and assessing long …
continuum, encompassing early screening, guiding treatment decisions, and assessing long …
Generative adversarial networks in cell microscopy for image augmentation. A systematic review
Cell microscopy is the main tool that allows researchers to study microorganisms and plays
a key role in observing and understanding the morphology, interactions, and development of …
a key role in observing and understanding the morphology, interactions, and development of …
A Novel Nucleus Detection on Pap Smear Image Using Mathematical Morphology Approach
N Nahrawi, WA Mustafa, SNAM Kanafiah… - Journal of …, 2021 - Trans Tech Publ
The fourth most common form of cancer among women is cervical cancer with 569,847 new
cases and 311,365 reported deaths worldwide in 2018. Cervical cancer is classified as the …
cases and 311,365 reported deaths worldwide in 2018. Cervical cancer is classified as the …
Data Augmentation Techniques to Detect Cervical Cancer Using Deep Learning: A Systematic Review
BZ Wubineh, A Rusiecki, K Halawa - International Conference on …, 2024 - Springer
Computer-assisted systems have been widely used as tools to support medical experts in
various fields, including the analysis of cervical cytology. However, due to patient privacy …
various fields, including the analysis of cervical cytology. However, due to patient privacy …
Recent trends and analysis of Generative Adversarial Networks in Cervical Cancer Imaging
T Sood - arXiv preprint arXiv:2209.12680, 2022 - arxiv.org
Cervical cancer is one of the most common types of cancer found in females. It contributes to
6-29% of all cancers in women. It is caused by the Human Papilloma Virus (HPV). The 5 …
6-29% of all cancers in women. It is caused by the Human Papilloma Virus (HPV). The 5 …