AIMC Topic: Positron-Emission Tomography
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Utilizing Pix2Pix conditional generative adversarial networks to recover missing data in preclinical PET scanner sinogram gaps.
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)
Apr 14, 2025
BACKGROUND: The presence of a gap between adjacent detector blocks in Positron Emission Tomography (PET) scanners introduces a partial loss of projection data, which can degrade the image quality and quantitative accuracy of reconstructed PET images....
Depth-of-interaction encoding techniques for pixelated PET detectors enabled by machine learning methods and fast waveform digitization.
Physics in medicine and biology
Apr 14, 2025
. Pixelated detectors with single-ended readout are routinely used by commercial positron emission tomography scanners owing to their good energy and timing resolution and optimized manufacturing, but they typically do not provide depth-of-interactio...
A strategy for multimodal integration of transcriptomics, proteomics, and radiomics data for the prediction of recurrence in patients with IDH-mutant gliomas.
International journal of cancer
Apr 11, 2025
Isocitrate dehydrogenase-mutant gliomas are lethal brain cancers that impair quality of life in young adults. Although less aggressive than glioblastomas, IDH-mutant gliomas invariably progress to incurable disease with unpredictable recurrence. A be...
IT: An interpretable transformer model for Alzheimer's disease prediction based on PET/MR images.
NeuroImage
Apr 11, 2025
Alzheimer's disease (AD) represents a significant challenge due to its progressive neurodegenerative impact, particularly within an aging global demographic. This underscores the critical need for developing sophisticated diagnostic tools for its ear...
Amyloid-β Deposition Prediction With Large Language Model Driven and Task-Oriented Learning of Brain Functional Networks.
IEEE transactions on medical imaging
Apr 3, 2025
Amyloid- positron emission tomography can reflect the Amyloid- protein deposition in the brain and thus serves as one of the golden standards for Alzheimer's disease (AD) diagnosis. However, its practical cost and high radioactivity hinder its applic...
POUR-Net: A Population-Prior-Aided Over-Under-Representation Network for Low-Count PET Attenuation Map Generation.
IEEE transactions on medical imaging
Apr 3, 2025
Low-dose PET offers a valuable means of minimizing radiation exposure in PET imaging. However, the prevalent practice of employing additional CT scans for generating attenuation maps ( -map) for PET attenuation correction significantly elevates radia...
Structural and metabolic topological alterations associated with butylphthalide treatment in mild cognitive impairment: Data from a randomized, double-blind, placebo-controlled trial.
Psychiatry and clinical neurosciences
Mar 31, 2025
AIMS: Effective intervention for mild cognitive impairment (MCI) is key for preventing dementia. As a neuroprotective agent, butylphthalide has the potential to treat MCI due to Alzheimer disease (AD). However, the pharmacological mechanism of butylp...
Development and validation of a nomogram for predicting bone marrow involvement in lymphoma patients based on F-FDG PET radiomics and clinical factors.
Annals of nuclear medicine
Mar 29, 2025
OBJECTIVE: This study aimed to develop and validate a nomogram combining F-FDG PET radiomics and clinical factors to non-invasively predict bone marrow involvement (BMI) in patients with lymphoma.
Artificial intelligence for tumor [F]FDG-PET imaging: Advancement and future trends-part I.
Seminars in nuclear medicine
Mar 29, 2025
The advent of sophisticated image analysis techniques has facilitated the extraction of increasingly complex data, such as radiomic features, from various imaging modalities, including [F]FDG PET/CT, a well-established cornerstone of oncological imag...
F-FDG PET radiomics score construction by automatic machine learning for treatment response prediction in elderly patients with diffuse large B-cell lymphoma: a multicenter study.
Journal of cancer research and clinical oncology
Mar 28, 2025
PURPOSE: To explore the development and validation of automated machine learning (AutoML) models for F-FDG PET imaging-based radiomics signatures to predict treatment response in elderly patients with diffuse large B-cell lymphoma (DLBCL).
Antineoplastic Combined Chemotherapy Protocols
Vincristine
Lymphoma, Large B-Cell, Diffuse
Machine Learning
Treatment Outcome
Male
Cyclophosphamide
Prognosis
Radiopharmaceuticals
Middle Aged
Fluorodeoxyglucose F18
Retrospective Studies
Positron-Emission Tomography
Prednisone
Female
Humans
Rituximab
Aged
Aged, 80 and over
Radiomics
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