AI Medical Compendium Topic

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Tomography, Emission-Computed, Single-Photon

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Development of attenuation correction methods using deep learning in brain-perfusion single-photon emission computed tomography.

Medical physics
PURPOSE: Computed tomography (CT)-based attenuation correction (CTAC) in single-photon emission computed tomography (SPECT) is highly accurate, but it requires hybrid SPECT/CT instruments and additional radiation exposure. To obtain attenuation corre...

A novel deep-learning-based approach for automatic reorientation of 3D cardiac SPECT images.

European journal of nuclear medicine and molecular imaging
PURPOSE: Reconstructed transaxial cardiac SPECT images need to be reoriented into standard short-axis slices for subsequent accurate processing and analysis. We proposed a novel deep-learning-based method for fully automatic reorientation of cardiac ...

The promise of artificial intelligence and deep learning in PET and SPECT imaging.

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)
This review sets out to discuss the foremost applications of artificial intelligence (AI), particularly deep learning (DL) algorithms, in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging. To this end, ...

Attenuation correction using deep learning for brain perfusion SPECT images.

Annals of nuclear medicine
OBJECTIVE: Non-uniform attenuation correction using computed tomography (CT) improves the image quality and quantification of single-photon emission computed tomography (SPECT). However, it is not widely used because it requires a SPECT/CT scanner. T...

Improved motor outcome prediction in Parkinson's disease applying deep learning to DaTscan SPECT images.

Computers in biology and medicine
PURPOSE: Dopamine transporter (DAT) SPECT imaging is routinely used in the diagnosis of Parkinson's disease (PD). Our previous efforts demonstrated the use of DAT SPECT images in a data-driven manner by improving prediction of PD clinical assessment ...

Automatic attenuation map estimation from SPECT data only for brain perfusion scans using convolutional neural networks.

Physics in medicine and biology
In clinical brain SPECT, correction for photon attenuation in the patient is essential to obtain images which provide quantitative information on the regional activity concentration per unit volume (kBq.[Formula: see text]). This correction generally...

Direct Attenuation Correction Using Deep Learning for Cardiac SPECT: A Feasibility Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Dedicated cardiac SPECT scanners with cadmium-zinc-telluride cameras have shown capabilities for shortened scan times or reduced radiation doses, as well as improved image quality. Since most dedicated scanners do not have integrated CT, image quanti...

Modeling complex particles phase space with GAN for Monte Carlo SPECT simulations: a proof of concept.

Physics in medicine and biology
A method is proposed to model by a generative adversarial network the distribution of particles exiting a patient during Monte Carlo simulation of emission tomography imaging devices. The resulting compact neural network is then able to generate part...

Deep learning based automated diagnosis of bone metastases with SPECT thoracic bone images.

Scientific reports
SPECT nuclear medicine imaging is widely used for treating, diagnosing, evaluating and preventing various serious diseases. The automated classification of medical images is becoming increasingly important in developing computer-aided diagnosis syste...