AIMC Topic: Tomography, Emission-Computed, Single-Photon
Clear Filters Showing 141 to 150 of 161 articles
Machine learning models for the differential diagnosis of vascular parkinsonism and Parkinson's disease using [(123)I]FP-CIT SPECT.
European journal of nuclear medicine and molecular imaging
Aug 14, 2014
PURPOSE: The study's objective was to develop diagnostic predictive models using data from two commonly used [(123)I]FP-CIT SPECT assessment methods: region-of-interest (ROI) analysis and whole-brain voxel-based analysis.
Differentiating Treatment-Resistant Depression With and Without Parkinsonism in the Elderly From a Psychiatric Perspective by Tc-TRODAT-1 SPECT Imaging.
International journal of geriatric psychiatry
Jun 1, 2025
OBJECTIVES: Late-life depression often overlaps with neurodegenerative diseases leading to diagnostic and treatment challenges for neuropsychiatrists. This study aimed to differentiate elderly treatment-resistant depression (TRD) comorbid with parkin...
Diagnosis, Differential
Radiopharmaceuticals
Humans
Parkinsonian Disorders
Machine Learning
Middle Aged
Female
Case-Control Studies
Aged
Dopamine Plasma Membrane Transport Proteins
Aged, 80 and over
Depressive Disorder, Treatment-Resistant
Male
Corpus Striatum
Organotechnetium Compounds
Tomography, Emission-Computed, Single-Photon
Tropanes
Neural Networks and Chemical Messengers: Insights into Tobacco Addiction.
Brain topography
May 13, 2025
This study investigates changes in resting-state networks (RSNs) associated with tobacco addiction (TA) and whether these changes reflect alterations in neurotransmitter systems. A total of 90 patients with TA and 46 healthy controls (HCs) matched fo...
Classification of Artifacts in Multimodal Fused Images using Transfer Learning with Convolutional Neural Networks.
Current medical imaging
Jan 1, 2024
INTRODUCTION: Multimodal medical image fusion techniques play an important role in clinical diagnosis and treatment planning. The process of combining multimodal images involves several challenges depending on the type of modality, transformation tec...
Multimodal Data-Driven Segmentation of Bone Metastasis Lesions in SPECT Bone Scans Using Deep Learning.
Current medical imaging
Jan 1, 2024
BACKGROUND: Patients with malignant tumors often develop bone metastases. SPECT bone scintigraphy is an effective tool for surveying bone metastases due to its high sensitivity, low-cost equipment, and radiopharmaceutical. However, the low spatial re...
Refining and simplifying decision models-tackling the 'one size fits all' challenge.
Cardiovascular research
Jul 20, 2022
[[SPECT] 5. Application of Artificial Intelligence in Nuclear Medicine for SPECT].
Nihon Hoshasen Gijutsu Gakkai zasshi
Jan 1, 2022
ACTIVITY CONCENTRATION ESTIMATION IN AUTOMATED KIDNEY SEGMENTATION BASED ON CONVOLUTION NEURAL NETWORK METHOD FOR 177LU-SPECT/CT KIDNEY DOSIMETRY.
Radiation protection dosimetry
Oct 12, 2021
For 177Lu-DOTATATE treatments, dosimetry based on manual kidney segmentation from computed tomography (CT) is accurate but time consuming and might be affected by misregistration between CT and SPECT images. This study develops a convolution neural n...
IMPROVEMENTS OF 111IN SPECT IMAGES RECONSTRUCTED WITH SPARSELY ACQUIRED PROJECTIONS BY DEEP LEARNING GENERATED SYNTHETIC PROJECTIONS.
Radiation protection dosimetry
Oct 12, 2021
The aim was to improve single-photon emission computed tomography (SPECT) quality for sparsely acquired 111In projections by adding deep learning generated synthetic intermediate projections (SIPs). Method: The recently constructed deep convolutional...
[Accuracy of Classification of Cerebral Blood Flow Reduction Patterns Using Statistical Analysis Images Generated with Simulated SPECT Datasets via Deep Learning].
Nihon Hoshasen Gijutsu Gakkai zasshi
Jan 1, 2021
PURPOSE: The aim of this study was to evaluate the classification accuracy of specific blood flow reduction patterns in clinical images by deep learning using simulation data.
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