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Radiopharmaceuticals

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Deep learning-based whole-body PSMA PET/CT attenuation correction utilizing Pix-2-Pix GAN.

Oncotarget
PURPOSE: Sequential PET/CT studies oncology patients can undergo during their treatment follow-up course is limited by radiation dosage. We propose an artificial intelligence (AI) tool to produce attenuation-corrected PET (AC-PET) images from non-att...

PSMA-positive prostatic volume prediction with deep learning based on T2-weighted MRI.

La Radiologia medica
PURPOSE: High PSMA expression might be correlated with structural characteristics such as growth patterns on histopathology, not recognized by the human eye on MRI images. Deep structural image analysis might be able to detect such differences and th...

DDFC: deep learning approach for deep feature extraction and classification of brain tumors using magnetic resonance imaging in E-healthcare system.

Scientific reports
This research explores the use of gated recurrent units (GRUs) for automated brain tumor detection using MRI data. The GRU model captures sequential patterns and considers spatial information within individual MRI images and the temporal evolution of...

Predicting T-Cell Lymphoma in Children From F-FDG PET-CT Imaging With Multiple Machine Learning Models.

Journal of imaging informatics in medicine
This study aimed to examine the feasibility of utilizing radiomics models derived from F-FDG PET/CT imaging to screen for T-cell lymphoma in children with lymphoma. All patients had undergone F-FDG PET/CT scans. Lesions were extracted from PET/CT and...

Early prediction of distant metastasis in patients with uterine cervical cancer treated with definitive chemoradiotherapy by deep learning using pretreatment [ 18 F]fluorodeoxyglucose positron emission tomography/computed tomography.

Nuclear medicine communications
OBJECTIVES: A deep learning (DL) model using image data from pretreatment [ 18 F]fluorodeoxyglucose ([ 18 F] FDG)-PET or computed tomography (CT) augmented with a novel imaging augmentation approach was developed for the early prediction of distant m...

Evidence of Age Estimation Procedures in Forensic Dentistry: Results from an Umbrella Review.

Medicina (Kaunas, Lithuania)
: Age estimation is an important tool when dealing with human remains or undocumented minors. Although the skull, the skeleton or the hand-wrist are used in age estimation as maturity indicators, they often present a lack of good conditions for a cor...

Deep learning for [F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis.

The Lancet. Digital health
BACKGROUND: The rising global cancer burden has led to an increasing demand for imaging tests such as [F]fluorodeoxyglucose ([F]FDG)-PET-CT. To aid imaging specialists in dealing with high scan volumes, we aimed to train a deep learning artificial in...

Classification of brain tumours from MRI images using deep learning-enabled hybrid optimization algorithm.

Network (Bristol, England)
Brain tumours are produced by the uncontrolled, and unusual tissue growth of brain. Because of the wide range of brain tumour locations, potential shapes, and image intensities, segmentation of the brain tumour by magnetic resonance imaging (MRI) is ...

On the Use of Artificial Intelligence for Dosimetry of Radiopharmaceutical Therapies.

Nuklearmedizin. Nuclear medicine
Routine clinical dosimetry along with radiopharmaceutical therapies is key for future treatment personalization. However, dosimetry is considered complex and time-consuming with various challenges amongst the required steps within the dosimetry workf...