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Positron-Emission Tomography

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Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.

Deep learning-based time-of-flight (ToF) image enhancement of non-ToF PET scans.

European journal of nuclear medicine and molecular imaging
PURPOSE: To improve the quantitative accuracy and diagnostic confidence of PET images reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image enhancement (DL-ToF).

Deep Learning Based Joint PET Image Reconstruction and Motion Estimation.

IEEE transactions on medical imaging
Respiratory motion is one of the main sources of motion artifacts in positron emission tomography (PET) imaging. The emission image and patient motion can be estimated simultaneously from respiratory gated data through a joint estimation framework. H...

Improved 3D tumour definition and quantification of uptake in simulated lung tumours using deep learning.

Physics in medicine and biology
In clinical positron emission tomography (PET) imaging, quantification of radiotracer uptake in tumours is often performed using semi-quantitative measurements such as the standardised uptake value (SUV). For small objects, the accuracy of SUV estima...

Evaluation Algorithm for the Effectiveness of Stroke Rehabilitation Treatment Using Cross-Modal Deep Learning.

Computational and mathematical methods in medicine
It is important to study the evaluation algorithm for the stroke rehabilitation treatment effect to make accurate evaluation and optimize the stroke disease treatment plan according to the evaluation results. To address the problems of poor restorati...

Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework.

Clinical nuclear medicine
PURPOSE: The generalizability and trustworthiness of deep learning (DL)-based algorithms depend on the size and heterogeneity of training datasets. However, because of patient privacy concerns and ethical and legal issues, sharing medical images betw...

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

Magnetic resonance in medicine
PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan.

The efficacy of F-FDG-PET-based radiomic and deep-learning features using a machine-learning approach to predict the pathological risk subtypes of thymic epithelial tumors.

The British journal of radiology
OBJECTIVE: To examine whether the machine-learning approach using 18-fludeoxyglucose positron emission tomography (F-FDG-PET)-based radiomic and deep-learning features is useful for predicting the pathological risk subtypes of thymic epithelial tumor...

Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement.

European journal of nuclear medicine and molecular imaging
Image processing plays a crucial role in maximising diagnostic quality of positron emission tomography (PET) images. Recently, deep learning methods developed across many fields have shown tremendous potential when applied to medical image enhancemen...

Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Total-body dynamic positron emission tomography/computed tomography (PET/CT) provides much sensitivity for clinical imaging and research, bringing new opportunities and challenges regarding the generation of total-body parametric images. Thi...