Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)
Objective There has been a large amount of research in the field of artificial intelligence (AI)
as applied to clinical radiology. However, these studies vary in design and quality and …
as applied to clinical radiology. However, these studies vary in design and quality and …
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 …
Realistic morphology-preserving generative modelling of the brain
PD Tudosiu, WHL Pinaya… - Nature Machine …, 2024 - nature.com
Medical imaging research is often limited by data scarcity and availability. Governance,
privacy concerns and the cost of acquisition all restrict access to medical imaging data …
privacy concerns and the cost of acquisition all restrict access to medical imaging data …
[HTML][HTML] Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging
Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …
cancer based on imaging data continue to pose significant challenges. These include inter …
Tumor-attentive segmentation-guided gan for synthesizing breast contrast-enhanced mri without contrast agents
Objective: Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a
sensitive imaging technique critical for breast cancer diagnosis. However, the administration …
sensitive imaging technique critical for breast cancer diagnosis. However, the administration …
High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
Computer-aided detection systems based on deep learning have shown good performance
in breast cancer detection. However, high-density breasts show poorer detection …
in breast cancer detection. However, high-density breasts show poorer detection …
medigan: a Python library of pretrained generative models for medical image synthesis
R Osuala, G Skorupko, N Lazrak… - Journal of Medical …, 2023 - spiedigitallibrary.org
Purpose Deep learning has shown great promise as the backbone of clinical decision
support systems. Synthetic data generated by generative models can enhance the …
support systems. Synthetic data generated by generative models can enhance the …
Cybersecurity in Healthcare
Abstract Embarking on a Medical Artificial Intelligence (AI) or Big Data project includes the
integration of a myriad of medical devices, wireless technologies, data warehouses, and …
integration of a myriad of medical devices, wireless technologies, data warehouses, and …
[PDF][PDF] A review of generative adversarial networks in cancer imaging: New applications, new solutions
Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include high …
cancer based on imaging data continue to pose significant challenges. These include high …
The creation of breast lesion models for mammographic virtual clinical trials: a topical review
A Van Camp, K Houbrechts, L Cockmartin… - Progress in …, 2023 - iopscience.iop.org
Simulated breast lesion models, including microcalcification clusters and masses, have
been used in several studies. Realistic lesion models are required for virtual clinical trials to …
been used in several studies. Realistic lesion models are required for virtual clinical trials to …