Current applications and future impact of machine learning in radiology
Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …
applications in medical imaging. Machine learning has the potential to improve different …
Review of medical image quality assessment
LS Chow, R Paramesran - Biomedical signal processing and control, 2016 - Elsevier
Abstract Image Quality Assessment (IQA) plays an important role in assessing any new
hardware, software, image acquisition techniques, image reconstruction or post-processing …
hardware, software, image acquisition techniques, image reconstruction or post-processing …
Transforming obstetric ultrasound into data science using eye tracking, voice recording, transducer motion and ultrasound video
Ultrasound is the primary modality for obstetric imaging and is highly sonographer
dependent. Long training period, insufficient recruitment and poor retention of sonographers …
dependent. Long training period, insufficient recruitment and poor retention of sonographers …
[HTML][HTML] Applications of artificial intelligence in the radiology roundtrip: process streamlining, workflow optimization, and beyond
K Pierre, AG Haneberg, S Kwak, KR Peters… - Seminars in …, 2023 - Elsevier
There are many impactful applications of artificial intelligence (AI) in the electronic radiology
roundtrip and the patient's journey through the healthcare system that go beyond diagnostic …
roundtrip and the patient's journey through the healthcare system that go beyond diagnostic …
[HTML][HTML] Image quality assessment for machine learning tasks using meta-reinforcement learning
In this paper, we consider image quality assessment (IQA) as a measure of how images are
amenable with respect to a given downstream task, or task amenability. When the task is …
amenable with respect to a given downstream task, or task amenability. When the task is …
A machine-learning framework for automatic reference-free quality assessment in MRI
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large
amount of data is created per examination which needs to be checked for sufficient quality in …
amount of data is created per examination which needs to be checked for sufficient quality in …
Comparative study of the methodologies used for subjective medical image quality assessment
Healthcare professionals have been increasingly viewing medical images and videos in
their routine clinical practice, and this in a wide variety of environments. Both the perception …
their routine clinical practice, and this in a wide variety of environments. Both the perception …
Blind night-time image quality assessment: Subjective and objective approaches
Blind image quality assessment (BIQA) aims to develop quantitative measures to
automatically and accurately estimate the visual quality of an image without any prior …
automatically and accurately estimate the visual quality of an image without any prior …
The relevance sample-feature machine: A sparse Bayesian learning approach to joint feature-sample selection
Y Mohsenzadeh, H Sheikhzadeh… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
This paper introduces a novel sparse Bayesian machine-learning algorithm for embedded
feature selection in classification tasks. Our proposed algorithm, called the relevance …
feature selection in classification tasks. Our proposed algorithm, called the relevance …
CNN as model observer in a liver lesion detection task for x‐ray computed tomography: A phantom study
Purpose The purpose of this study was the evaluation of anthropomorphic model observers
trained with neural networks for the prediction of a human observer's performance. Methods …
trained with neural networks for the prediction of a human observer's performance. Methods …