AIMC Journal:
Medical physics
Showing 701 to 710 of 759 articles
AI in medical physics: guidelines for publication.
Medical physics
Sep 1, 2021
The Abstract is intended to provide a concise summary of the study and its scientific findings. For AI/ML applications in medical physics, a problem statement and rationale for utilizing these algorithms are necessary while highlighting the novelty o...
Artificial intelligence-based clinical decision support in modern medical physics: Selection, acceptance, commissioning, and quality assurance.
Medical physics
Jun 1, 2020
BACKGROUND: Recent advances in machine and deep learning based on an increased availability of clinical data have fueled renewed interest in computerized clinical decision support systems (CDSSs). CDSSs have shown great potential to improve healthcar...
Computer-aided diagnosis in the era of deep learning.
Medical physics
Jun 1, 2020
Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then be used to...
Introduction to machine and deep learning for medical physicists.
Medical physics
Jun 1, 2020
Recent years have witnessed tremendous growth in the application of machine learning (ML) and deep learning (DL) techniques in medical physics. Embracing the current big data era, medical physicists equipped with these state-of-the-art tools should b...
Machine learning for radiation outcome modeling and prediction.
Medical physics
Jun 1, 2020
AIMS: This review paper intends to summarize the application of machine learning to radiotherapy outcome modeling based on structured and un-structured radiation oncology datasets.
Machine learning techniques for biomedical image segmentation: An overview of technical aspects and introduction to state-of-art applications.
Medical physics
Jun 1, 2020
In recent years, significant progress has been made in developing more accurate and efficient machine learning algorithms for segmentation of medical and natural images. In this review article, we highlight the imperative role of machine learning alg...
Machine and deep learning methods for radiomics.
Medical physics
Jun 1, 2020
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has enabled t...
Genomics models in radiotherapy: From mechanistic to machine learning.
Medical physics
Jun 1, 2020
Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles...
One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection.
Medical physics
Dec 1, 2019
PURPOSE: Computed tomography for the reconstruction of region of interest (ROI) has advantages in reducing the x-ray dose and the use of a small detector. However, standard analytic reconstruction methods such as filtered back projection (FBP) suffer...
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