AIMC Topic: Phantoms, Imaging

Clear Filters Showing 61 to 70 of 786 articles

Noise Reduction in Brain CT: A Comparative Study of Deep Learning and Hybrid Iterative Reconstruction Using Multiple Parameters.

Tomography (Ann Arbor, Mich.) Dec 18, 2024
OBJECTIVES: We evaluated the noise reduction effects of deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) in brain computed tomography (CT).
Humans Brain Adult Male Middle Aged Tomography, X-Ray Computed Female Aged Signal-To-Noise Ratio Phantoms, Imaging Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted
View on PubMed DOI

CT image super-resolution under the guidance of deep gradient information.

Journal of X-ray science and technology Dec 15, 2024
Due to the hardware constraints of Computed Tomography (CT) imaging, acquiring high-resolution (HR) CT images in clinical settings poses a significant challenge. In recent years, convolutional neural networks have shown great potential in CT super-re...
Phantoms, Imaging Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
View on PubMed DOI

Estimation of fatty acid composition in mammary adipose tissue using deep neural network with unsupervised training.

Magnetic resonance in medicine Dec 6, 2024
PURPOSE: To develop a deep learning-based method for robust and rapid estimation of the fatty acid composition (FAC) in mammary adipose tissue.
Breast Fatty Acids Phantoms, Imaging Magnetic Resonance Imaging Unsupervised Machine Learning Adipose Tissue Neural Networks, Computer Female Breast Neoplasms Middle Aged Deep Learning Image Processing, Computer-Assisted Humans
View on PubMed DOI

Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to- Aberration Approach.

IEEE transactions on medical imaging Dec 2, 2024
One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which disturbs the transmitted waves and prevents coherent summation of echo...
Ultrasonography Image Processing, Computer-Assisted Phantoms, Imaging Humans Algorithms Deep Learning
View on PubMed DOI

Three-Dimensional Thermal Tomography with Physics-Informed Neural Networks.

Tomography (Ann Arbor, Mich.) Nov 30, 2024
: Accurate reconstruction of internal temperature fields from surface temperature data is critical for applications such as non-invasive thermal imaging, particularly in scenarios involving small temperature gradients, like those in the human body. :...
Imaging, Three-Dimensional Humans Thermography Neural Networks, Computer Phantoms, Imaging Deep Learning
View on PubMed DOI

Investigating the Use of Traveltime and Reflection Tomography for Deep Learning-Based Sound-Speed Estimation in Ultrasound Computed Tomography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Ultrasound computed tomography (USCT) quantifies acoustic tissue properties such as the speed-of-sound (SOS). Although full-waveform inversion (FWI) is an effective method for accurate SOS reconstruction, it can be computationally challenging for lar...
Ultrasonography Image Processing, Computer-Assisted Breast Phantoms, Imaging Tomography Tomography, X-Ray Computed Humans Female Algorithms Deep Learning
View on PubMed DOI

Brain MR-only workflow in clinical practice: A comparison among generators for quality assurance and patient positioning.

Journal of applied clinical medical physics Nov 25, 2024
BACKGROUND AND PURPOSE: Routine quality control procedures are still required for sCT based on artificial intelligence (AI) to verify the performance of the generators. The aim of this study was to evaluate three generators based on AI or bulk densit...
Humans Radiotherapy Dosage Phantoms, Imaging Radiotherapy, Intensity-Modulated Artificial Intelligence Workflow Brain Neoplasms Patient Positioning Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Quality Assurance, Health Care Magnetic Resonance Imaging
View on PubMed DOI

Automated robotic-assisted patient positioning method and dosimetric impact analysis for boron neutron capture therapy.

Scientific reports Nov 22, 2024
Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in precise targeting is well-recognized, a critical bottleneck remains in the accurate positioning of p...
Radiometry Boron Neutron Capture Therapy Radiotherapy Dosage Patient Positioning Phantoms, Imaging Neoplasms Robotics Humans Radiotherapy Planning, Computer-Assisted Algorithms
View on PubMed DOI

A Physics-Informed Deep Neural Network for Harmonization of CT Images.

IEEE transactions on bio-medical engineering Nov 21, 2024
OBJECTIVE: Computed Tomography (CT) quantification is affected by the variability in image acquisition and rendition. This paper aimed to reduce this variability by harmonizing the images utilizing physics-based deep neural networks (DNNs).
Radiographic Image Interpretation, Computer-Assisted Lung Diseases Phantoms, Imaging Humans Lung Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Tomography, X-Ray Computed
View on PubMed DOI

MMD-Net: Image domain multi-material decomposition network for dual-energy CT imaging.

Medical physics Nov 18, 2024
BACKGROUND: Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms.
Neural Networks, Computer Algorithms Tomography, X-Ray Computed Humans Animals Phantoms, Imaging Swine Image Processing, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals