AIMC Topic: Phantoms, Imaging

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Improving detection accuracy of heterogeneity in biological tissues through the combination of modulation-demodulation frame accumulation techniques and enhanced vgg16.

PloS one
Light source has obvious absorption and scattering effects during the transmission process of biological tissues, making it difficult to identify heterogeneities in multi-spectral images. This paper achieves a gradual improvement in the classificatio...

Phantom studies in medical imaging (PSMI): a guide with recommendations and checklist.

European radiology experimental
Phantom studies are essential in medical imaging, offering a controlled and reproducible framework for evaluating imaging technologies across all modalities. Phantoms, whether physical (synthetic, biological, or mixed) or computational, simulate huma...

Modular magnetic microrobot system for robust endoluminal navigation and high-radial force stent delivery in complex ductal anatomy.

Science advances
Endoluminal stent implantation is a common intervention strategy for treating obstructive lesions, but conventional delivery systems struggle to reach deep, tortuous ducts. To overcome this limitation, we present a magnetically controlled microrobot ...

Fast water/fatand PDFF mapping via multiple overlapping-echo detachment acquisition and deep learning reconstruction.

Physics in medicine and biology
Rapid and accurate quantitative assessment of muscle tissue characteristics is valuable for the diagnosis and monitoring of neuromuscular diseases (NMDs). Quantitative magnetic resonance imaging (MRI) enables non-invasive assessment of muscle patholo...

Precise path planning for robot-assisted craniotomy: a CT-driven virtual center method.

Biomedical physics & engineering express
. Craniotomy is a critical prerequisite for numerous neuro-surgeries, including intracranial tumor resection and cerebral hemorrhage decompression. However, conventional manual craniotomy methods are often time-consuming, labor-intensive, and associa...

Improved pharmacokinetic parameter estimation from DCE-MRI via spatial-temporal information-driven unsupervised learning.

Physics in medicine and biology
Pharmacokinetic (PK) parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provide quantitative characterization of tissue perfusion and permeability. However, existing deep learning methods for PK parameter estimatio...

Insertion of hepatic lesions into clinical photon-counting-detector CT projection data.

Physics in medicine and biology
To facilitate task-driven image quality assessment of lesion detectability in clinical photon-counting-detector CT (PCD-CT), it is desired to have patient image data with known pathology and precise annotation. Standard patient case collection and re...

PixelPrint 4D : A 3D Printing Method of Fabricating Patient-Specific Deformable CT Phantoms for Respiratory Motion Applications.

Investigative radiology
OBJECTIVES: Respiratory motion poses a significant challenge for clinical workflows in diagnostic imaging and radiation therapy. Many technologies such as motion artifact reduction and tumor tracking have been developed to compensate for its effect. ...

3D electroacoustic tomography image enhancement using deep learning with the SAM-Med3D encoder.

Physics in medicine and biology
To overcome the limitations of electroacoustic tomography (EAT) in clinical settings-particularly the artifacts and distortions caused by limited-angle data acquisition-and enable accurate, efficient visualization of electric field distributions for ...

Disentangled deep learning method for interior tomographic reconstruction of low-dose x-ray CT.

Physics in medicine and biology
. Low-dose interior tomography integrates low-dose CT (LDCT) with region-of-interest (ROI) imaging which finds wide application in radiation dose reduction and high-resolution imaging. However, the combined effects of noise and data truncation pose g...