AIMC Topic: Phantoms, Imaging

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Robust CNN multi-nested-LSTM framework with compound loss for patch-based multi-push ultrasound shear wave imaging and segmentation.

Physics in medicine and biology
Ultrasound shear wave imaging enables noninvasive, quantitative assessment of tissue pathology with mechanical elasticity measurements. However, shear wave elastography (SWE) reconstructions are challenged by noise sensitivity, inefficient multi-push...

Polychromatic neural CBCT reconstruction through density-attenuation modeling.

Physics in medicine and biology
Monochromatic cone beam computed tomography reconstruction algorithms are still most prominent in practice. Since the x-ray detectors of today's machines are mostly energy integrating detectors and thus not able to resolve photon energy levels, recon...

seg2med: a bridge from artificial anatomy to multimodal medical images.

Physics in medicine and biology
. We present seg2med (segmentation-to-medical images), a modular framework for anatomy-driven multimodal medical image synthesis. The system integrates three components to enable high-fidelity, cross-modality generation of computed tomography (CT) an...

Model-based spatiotemporal synthetic data generation framework and deep-learning reconstruction for real-time MRI oxygen extraction fraction mapping.

Physics in medicine and biology
Synthetic data has emerged as a highly efficient solution to address the scarcity of training data in deep learning-based quantitative magnetic resonance imaging (qMRI) reconstruction. However, current applications of synthetic data predominantly foc...

FBFormer: interventional ultra-sparse CT reconstruction with image prior using feature back-projection and transformer.

Physics in medicine and biology
. CT-guided interventional procedures hold a significant position in clinical practice. However, due to the high number of scans and prolonged procedure times, patients are exposed to considerable radiation doses. This study aims to utilize intraoper...

Metaheuristic-optimized generative adversarial network for enhanced sparse-view low-dose CT reconstruction.

Biomedical physics & engineering express
Sparse-view low-dose computed tomography (LDCT) imaging poses difficulties in preserving image quality while reducing radiation exposure. Recent research has focused extensively on artificial intelligence (AI) to reduce artifacts in LDCT. This paper ...

Experimental approach for optimizing dose regimen of 68Ga-DOTATATE PET/CT for neuroendocrine tumor (NET) imaging in current high sensitivity scanners: Phantom and Patient Study.

Nuklearmedizin. Nuclear medicine
This study aimed to determine the optimized scan time and injected activity regimen for clinical Ga DOTATATE PET/CT in neuroendocrine tumor imaging through an experimental approach without using machine learning techniques.A NEMA PET body phantom was...

Visual language model-assisted spectral CT reconstruction by diffusion and low-rank priors from limited-angle measurements.

Physics in medicine and biology
Spectral computed tomography (CT) is a critical tool in clinical practice, offering capabilities in multi-energy spectrum imaging and material identification. The limited-angle (LA) scanning strategy has attracted attention for its advantages in fast...

Fast machine learning image reconstruction of radially undersampled k-space data for low-latency real-time MRI.

PloS one
Fast data acquisition and fast image reconstruction are essential to enable low-latency real-time magnetic resonance (MR) imaging applications with high temporal resolution such as interstitial percutaneous needle interventions or MR-guided radiother...

Joint frequency-image domain network for image restoration in magnetic particle imaging.

Physics in medicine and biology
Magnetic particle imaging (MPI) is a promising medical imaging technique that has been widely applied in preclinical stages. However, when expanding to human body scanning, cases often arise where superparamagnetic iron oxide nanoparticles (SPIOs) ar...