AIMC Topic: Radioisotopes

Clear Filters Showing 11 to 20 of 22 articles

Tritium: Its relevance, sources and impacts on non-human biota.

The Science of the total environment
Tritium (H) is a radioactive isotope of hydrogen that is abundantly released from nuclear industries. It is extremely mobile in the environment and in all biological systems, representing an increasing concern for the health of both humans and non-hu...

Comparison of machine learning approaches for radioisotope identification using NaI(TI) gamma-ray spectrum.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
This research aims at comparing the performance of different machine learning algorithms used for NaI(TI) gamma-ray detector based radioisotope identification. Six machine learning algorithms were implemented, including support vector machine (SVM), ...

A new radionuclide identification method for low-count energy spectra with multiple radionuclides.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Radionuclide identification is to recognize the radionuclides in the environment by analyzing the energy spectrum. Rapid and accurate identification is important for nuclear security. Current radionuclide identification methods based on traditional p...

Radiation Protection and Occupational Exposure on Ga-PSMA-11-Based Cerenkov Luminescence Imaging Procedures in Robot-Assisted Prostatectomy.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Cerenkov luminescence imaging (CLI) was successfully implemented in the intraoperative context as a form of radioguided cancer surgery, showing promise in the detection of surgical margins during robot-assisted radical prostatectomy. The present stud...

Deep-Learning Generation of Synthetic Intermediate Projections Improves Lu SPECT Images Reconstructed with Sparsely Acquired Projections.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
The aims of this study were to decrease the Lu-SPECT acquisition time by reducing the number of projections and to circumvent image degradation by adding deep-learning-generated synthesized projections. We constructed a deep convolutional U-net-shap...

A deep learning approach to radiation dose estimation.

Physics in medicine and biology
Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather crude in daily clinical practice. Most importantly, individual tissue density distributions as well as local variations of the concentration of the ra...

Glucose-holmium for radiotherapy: Characterization and in vitro assays.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
BACKGROUND: The existence of saccharide-holmium complexes, containing mono or polysaccharide molecules, is an attractive hypothesis toward a radiation therapy (RT) with beta-emitters targeting high glucose metabolic human sites. To exam such hypothes...

Personalized Models for Injected Activity Levels in SPECT Myocardial Perfusion Imaging.

IEEE transactions on medical imaging
We propose a patient-specific ("personalized") approach for tailoring the injected activities to individual patients in order to achieve dose reduction in SPECT-myocardial perfusion imaging (MPI). First, we develop a strategy to determine the minimum...