AIMC Topic: Positron-Emission Tomography

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Technological advancements in cancer diagnostics: Improvements and limitations.

Cancer reports (Hoboken, N.J.)
BACKGROUND: Cancer is characterized by the rampant proliferation, growth, and infiltration of malignantly transformed cancer cells past their normal boundaries into adjacent tissues. It is the leading cause of death worldwide, responsible for approxi...

Resolution estimation in different monolithic PET detectors using neural networks.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: We use neural networks to evaluate and compare the spatial resolution of two different simulated monolithic PET detector elements. The effects of mixing events with single photoeffect interactions and multiple Compton scatterings are also st...

Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.

Biomedical engineering online
BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta...

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantitative PET imaging, which remain challenging in PET-only and PET/MRI systems. These can be effectively tackled via deep learning (DL) methods. However, t...

Position estimation using neural networks in semi-monolithic PET detectors.

Physics in medicine and biology
. The goal of this work is to experimentally compare the 3D spatial and energy resolution of a semi-monolithic detector suitable for total-body positron emission tomography (TB-PET) scanners using different surface crystal treatments and silicon phot...

Deep learning-based dynamic PET parametric K image generation from lung static PET.

European radiology
OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric K provides better quantification and improve speci...

Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.

Physical and engineering sciences in medicine
The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modality of brain imaging to detect multiple stages of dementia, including Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI)...

NAVIGATOR: an Italian regional imaging biobank to promote precision medicine for oncologic patients.

European radiology experimental
NAVIGATOR is an Italian regional project boosting precision medicine in oncology with the aim of making it more predictive, preventive, and personalised by advancing translational research based on quantitative imaging and integrative omics analyses....

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

BioMed research international
PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian cancer patients. We use the feature map formed by wavelet transform and the parameters obtained by i...