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 …
Applications of deep learning to neuro-imaging techniques
Many clinical applications based on deep learning and pertaining to radiology have been
proposed and studied in radiology for classification, risk assessment, segmentation tasks …
proposed and studied in radiology for classification, risk assessment, segmentation tasks …
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 …
Automated reference-free detection of motion artifacts in magnetic resonance images
T Küstner, A Liebgott, L Mauch, P Martirosian… - … Resonance Materials in …, 2018 - Springer
Objectives Our objectives were to provide an automated method for spatially resolved
detection and quantification of motion artifacts in MR images of the head and abdomen as …
detection and quantification of motion artifacts in MR images of the head and abdomen as …
[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 …
[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 …
Regularization strategies in statistical image reconstruction of low‐dose x‐ray CT: A review
Statistical image reconstruction (SIR) methods have shown potential to substantially improve
the image quality of low‐dose x‐ray computed tomography (CT) as compared to the …
the image quality of low‐dose x‐ray computed tomography (CT) as compared to the …
CNN‐Based Medical Ultrasound Image Quality Assessment
S Zhang, Y Wang, J Jiang, J Dong, W Yi, W Hou - Complexity, 2021 - Wiley Online Library
The quality of ultrasound image is a key information in medical related application. It is also
an important index in evaluating the performance of ultrasonic imaging equipment and …
an important index in evaluating the performance of ultrasonic imaging equipment and …
Correlation between human detection accuracy and observer model-based image quality metrics in computed tomography
The purpose of this study was to compare computed tomography (CT) low-contrast
detectability from human readers with observer model-based surrogates of image quality. A …
detectability from human readers with observer model-based surrogates of image quality. A …
Can signal-to-noise ratio perform as a baseline indicator for medical image quality assessment
Natural image quality assessment (NIQA) wins increasing attention, while NIQA models are
rarely used in the medical community. A couple of studies employ the NIQA methodologies …
rarely used in the medical community. A couple of studies employ the NIQA methodologies …