AI applications to medical images: From machine learning to deep learning
Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …
research and healthcare services. This review focuses on challenges points to be clarified …
Artificial intelligence and machine learning for medical imaging: A technology review
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …
of disruptive technical advances and impressive experimental results, notably in the field of …
Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration
Multiomics data including imaging radiomics and various types of molecular biomarkers
have been increasingly investigated for better diagnosis and therapy in the era of precision …
have been increasingly investigated for better diagnosis and therapy in the era of precision …
[HTML][HTML] Quality assurance for AI-based applications in radiation therapy
Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT)
and their integration into modern software-based systems raise new challenges to the …
and their integration into modern software-based systems raise new challenges to the …
HaN‐Seg: The head and neck organ‐at‐risk CT and MR segmentation dataset
Purpose For the cancer in the head and neck (HaN), radiotherapy (RT) represents an
important treatment modality. Segmentation of organs‐at‐risk (OARs) is the starting point of …
important treatment modality. Segmentation of organs‐at‐risk (OARs) is the starting point of …
Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model …
A Barragán-Montero, A Bibal… - Physics in Medicine …, 2022 - iopscience.iop.org
The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …
the performance leap that occurred with new techniques of deep learning, convolutional …
A deep learning approach for automatic detection, segmentation and classification of breast lesions from thermal images
Purpose This study investigates implementation of deep learning (DL) approaches to breast
tumor recognition based on thermal images. We propose to utilize Mask R-CNN technique …
tumor recognition based on thermal images. We propose to utilize Mask R-CNN technique …
[图书][B] Modern diagnostic x-ray sources: technology, manufacturing, reliability
R Behling - 2021 - taylorfrancis.com
Now fully updated, the second edition of Modern Diagnostic X-Ray Sources: Technology,
Manufacturing, Reliability gives an up-to-date summary of X-ray source technology and …
Manufacturing, Reliability gives an up-to-date summary of X-ray source technology and …
Artificial intelligence in thyroid field—a comprehensive review
Simple Summary The incidence of thyroid pathologies has been increasing worldwide.
Historically, the detection of thyroid neoplasms relies on medical imaging analysis …
Historically, the detection of thyroid neoplasms relies on medical imaging analysis …
Quantitative molecular positron emission tomography imaging using advanced deep learning techniques
The widespread availability of high-performance computing and the popularity of artificial
intelligence (AI) with machine learning and deep learning (ML/DL) algorithms at the helm …
intelligence (AI) with machine learning and deep learning (ML/DL) algorithms at the helm …