Radiology

Nuclear Medicine

Latest AI and machine learning research in nuclear medicine for healthcare professionals.

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Next generation research applications for hybrid PET/MR and PET/CT imaging using deep learning.

INTRODUCTION: Recently there have been significant advances in the field of machine learning and art...

F-FDG-PET-based radiomics features to distinguish primary central nervous system lymphoma from glioblastoma.

The differential diagnosis of primary central nervous system lymphoma from glioblastoma multiforme (...

Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss.

PURPOSE: Our goal was to use a generative adversarial network (GAN) with feature matching and task-s...

Automated Bone Scan Index as an Imaging Biomarker to Predict Overall Survival in the Zometa European Study/SPCG11.

BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostat...

Higher SNR PET image prediction using a deep learning model and MRI image.

PET images often suffer poor signal-to-noise ratio (SNR). Our objective is to improve the SNR of PET...

Machine-learned target volume delineation of F-FDG PET images after one cycle of induction chemotherapy.

Biological tumour volume (GTV) delineation on F-FDG PET acquired during induction chemotherapy (ICT)...

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-FP-CIT indices.

OBJECTIVES: To provide an automated classification method for degenerative parkinsonian syndromes (P...

Deep learning only by normal brain PET identify unheralded brain anomalies.

BACKGROUND: Recent deep learning models have shown remarkable accuracy for the diagnostic classifica...

Automatic PET cervical tumor segmentation by combining deep learning and anatomic prior.

Cervical tumor segmentation on 3D FDG PET images is a challenging task because of the proximity betw...

Application of Artificial Neural Networks to Identify Alzheimer's Disease Using Cerebral Perfusion SPECT Data.

The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer d...

Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging.

The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomog...

Unsupervised tumor detection in Dynamic PET/CT imaging of the prostate.

Early detection and localization of prostate tumors pose a challenge to the medical community. Sever...

Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain F-FDG PET.

Dedicated brain positron emission tomography (PET) devices can provide higher-resolution images with...

DeepPET: A deep encoder-decoder network for directly solving the PET image reconstruction inverse problem.

The purpose of this research was to implement a deep learning network to overcome two of the major b...

Measurement of Glomerular Filtration Rate using Quantitative SPECT/CT and Deep-learning-based Kidney Segmentation.

Quantitative SPECT/CT is potentially useful for more accurate and reliable measurement of glomerular...

Machine learning polymer models of three-dimensional chromatin organization in human lymphoblastoid cells.

We present machine learning models of human genome three-dimensional structure that combine one dime...

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