AIMC Topic: Phantoms, Imaging

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KBA-PDNet: A primal-dual unrolling network with kernel basis attention for low-dose CT reconstruction.

Journal of X-ray science and technology
Computed tomography (CT) image reconstruction is faced with challenge of balancing image quality and radiation dose. Recent unrolled optimization methods address low-dose CT image quality issues using convolutional neural networks or self-attention m...

Sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization.

Computers in biology and medicine
Cone beam computed tomography (CBCT) is an emerging medical imaging technique to visualize the internal anatomical structures of patients. During a CBCT scan, several projection images of different angles or views are collectively utilized to reconst...

Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques.

Magma (New York, N.Y.)
OBJECTIVE: Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed.

Complex conjugate removal in optical coherence tomography using phase aware generative adversarial network.

Journal of biomedical optics
SIGNIFICANCE: Current methods for complex conjugate removal (CCR) in frequency-domain optical coherence tomography (FD-OCT) often require additional hardware components, which increase system complexity and cost. A software-based solution would provi...

Evaluation of deep learning-based scatter correction on a long-axial field-of-view PET scanner.

European journal of nuclear medicine and molecular imaging
OBJECTIVE: Long-axial field-of-view (LAFOV) positron emission tomography (PET) systems allow higher sensitivity, with an increased number of detected lines of response induced by a larger angle of acceptance. However this extended angle increases the...

Deep learning aided determination of the optimal number of detectors for photoacoustic tomography.

Biomedical physics & engineering express
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology...

High-resolution deep learning reconstruction for coronary CTA: compared efficacy of stenosis evaluation with other methods at in vitro and in vivo studies.

European radiology
OBJECTIVE: To directly compare coronary arterial stenosis evaluations by hybrid-type iterative reconstruction (IR), model-based IR (MBIR), deep learning reconstruction (DLR), and high-resolution deep learning reconstruction (HR-DLR) on coronary compu...

Quantification of tissue stiffness with magnetic resonance elastography and finite difference time domain (FDTD) simulation-based spatiotemporal neural network.

Magnetic resonance imaging
Quantification of tissue stiffness with magnetic resonance elastography (MRE) is an inverse problem that is sensitive to noise. Conventional methods for the purpose include direct inversion (DI) and local frequency estimation (LFE). In this study, we...

DLPVI: Deep learning framework integrating projection, view-by-view backprojection, and image domains for high- and ultra-sparse-view CBCT reconstruction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study proposes a deep learning framework, DLPVI, which integrates projection, view-by-view backprojection (VVBP), and image domains to improve the quality of high-sparse-view and ultra-sparse-view cone-beam computed tomography (CBCT) images. The...

Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging.

NeuroImage
INTRODUCTION: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonance Spectroscopic Imaging (MRSI). Advanced MRSI using non-cartesian comp...