AIMC Topic: Positron-Emission Tomography

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Reconstruction of total-body multi parametric images with shortened-duration dynamic [Ga]Ga-PSMA-11 and [Ga]Ga-FAPI-04 PET scans.

Physics in medicine and biology
The lengthy 1 h dynamic positron emission tomography (PET) scans discomfort patients, add motion artifacts, and inflate costs, highlighting the need for tech advancements to reduce scan times. Therefore, we attempted to reconstruct multi-parametric i...

Machine Learning-Driven radiomics on 18 F-FDG PET for glioma diagnosis: a systematic review and meta-analysis.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Machine learning (ML) applied to radiomics has revolutionized neuro-oncological imaging, yet the diagnostic performance of ML models based specifically on ^18F-FDG PET features in glioma remains poorly characterized.

Deep unrolled primal dual network for TOF-PET list-mode image reconstruction.

Physics in medicine and biology
Time-of-flight (TOF) information provides more accurate location data for annihilation photons, thereby enhancing the quality of positron emission tomography (PET) reconstruction images and reducing noise. List-mode reconstruction has a significant a...

FastDIP: An effective approach for accelerating unsupervised low-count PET image reconstruction.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
INTRODUCTION: Unsupervised deep learning methods can improve the image quality of positron emission tomography (PET) images without the need for large-scale datasets. However, these approaches typically require training a distinct network for each pa...

Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer's disease.

Alzheimer's research & therapy
BACKGROUND AND OBJECTIVES: Early and cost-effective identification of amyloid positivity is crucial for Alzheimer's disease (AD) diagnosis. While amyloid PET is the gold standard, plasma biomarkers such as phosphorylated tau 217 (pTau217) provide a p...

AI-driven fusion of multimodal data for Alzheimer's disease biomarker assessment.

Nature communications
Alzheimer's disease (AD) diagnosis hinges on detecting amyloid beta (Aβ) plaques and neurofibrillary tau (τ) tangles, typically assessed using PET imaging. While accurate, these modalities are expensive and not widely accessible, limiting their utili...

IgCONDA-PET: Weakly-supervised PET anomaly detection using implicitly-guided attention-conditional counterfactual diffusion modeling - a multi-center, multi-cancer, and multi-tracer study.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Minimizing the need for pixel-level annotated data to train PET lesion detection and segmentation networks is highly desired and can be transformative, given time and cost constraints associated with expert annotations. Current unsupervised or weakly...

Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging.

Scientific reports
Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. Multi-feature ...

Novel molecular imaging approaches in oncology: towards a more accurate estimation of tumour response.

Current opinion in oncology
PURPOSE OF REVIEW: With novel therapeutics improving cancer survival rates, the need for accurate treatment response assessment has become increasingly crucial. The Response Evaluation Criteria in Solid Tumours remains the standard imaging method for...

A novel neuroimaging based early detection framework for alzheimer disease using deep learning.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly impacts cognitive function, posing a major global health challenge. Despite its rising prevalence, particularly in low and middle-income countries, early diagnosi...