AIMC Topic: Phantoms, Imaging
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Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.
Scientific reports
Aug 6, 2025
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...
ComptoNet: a Compton-map guided deep learning framework for multi-scatter estimation in multi-source stationary CT.
Physics in medicine and biology
Jul 16, 2025
Multi-source stationary computed tomography (MSS-CT) offers significant advantages in medical and industrial applications due to its gantryless scan architecture and capability of simultaneous multi-source emission. However, the lack of anti-scatter ...
In-silico CT simulations of deep learning generated heterogeneous phantoms.
Biomedical physics & engineering express
Jul 10, 2025
Current virtual imaging phantoms primarily emphasize geometric accuracy of anatomical structures. However, to enhance realism, it is also important to incorporate intra-organ detail. Because biological tissues are heterogeneous in composition, virtua...
Limited-angle SPECT image reconstruction using deep image prior.
Physics in medicine and biology
Jul 9, 2025
. In single-photon emission computed tomography (SPECT) image reconstruction, limited-angle conditions lead to a loss of frequency components, which distort the reconstructed tomographic image along directions corresponding to the non-collected proje...
Inconsistency of AI in intracranial aneurysm detection with varying dose and image reconstruction.
Scientific reports
Jun 6, 2025
Scanner-related changes in data quality are common in medical imaging, yet monitoring their impact on diagnostic AI performance remains challenging. In this study, we performed standardized consistency testing of an FDA-cleared and CE-marked AI for t...
Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications.
Scientific reports
Jun 4, 2025
Recent research advances have resulted in an experimental benchtop X-ray fluorescence computed tomography (XFCT) system that likely meets the imaging dose/scan time constraints for benchtop XFCT imaging of live mice injected with gold nanoparticles (...
Direct parametric reconstruction in dynamic PET using deep image prior and a novel parameter magnification strategy.
Computers in biology and medicine
Jun 2, 2025
BACKGROUND/PURPOSE: Multiple parametric imaging in positron emission tomography (PET) is challenging due to the noisy dynamic data and the complex mapping to kinetic parameters. Although methods like direct parametric reconstruction have been propose...
Speckle pattern analysis with deep learning for low-cost stroke detection: a phantom-based feasibility study.
Journal of biomedical optics
May 7, 2025
SIGNIFICANCE: Stroke is a leading cause of disability worldwide, necessitating rapid and accurate diagnosis to limit irreversible brain damage. However, many advanced imaging modalities (computerized tomography, magnetic resonance imaging) remain ina...
BentRay-NeRF: Bent-Ray Neural Radiance Fields for Robust Speed-of-Sound Imaging in Ultrasound Computed Tomography.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
May 7, 2025
Ultrasound computed tomography (USCT) is a promising technique for breast cancer detection because of its quantitative imaging capability of the speed of sound (SOS) of soft tissues and the fact that malignant breast lesions often have a higher SOS c...
XCAT 3.0: A comprehensive library of personalized digital twins derived from CT scans.
Medical image analysis
May 3, 2025
Virtual Imaging Trials (VIT) offer a cost-effective and scalable approach for evaluating medical imaging technologies. Computational phantoms, which mimic real patient anatomy and physiology, play a central role in VITs. However, the current librarie...
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