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Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data.

NeuroImage
A large number of papers have introduced novel machine learning and feature extraction methods for automatic classification of Alzheimer's disease (AD). However, while the vast majority of these works use the public dataset ADNI for evaluation, they ...

Adaptive template generation for amyloid PET using a deep learning approach.

Human brain mapping
Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anatomical magnetic resonance imaging (MRI) of the same individual is technically challenging. In this st...

Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

Medical image analysis
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen prodromal mild cognitive impairment (MCI) phase where memory loss is the main complaint progressively worsening with behavior issues and poor self-care...

Interpretation criteria for FDG PET/CT in multiple myeloma (IMPeTUs): final results. IMPeTUs (Italian myeloma criteria for PET USe).

European journal of nuclear medicine and molecular imaging
UNLABELLED: ᅟ: FDG PET/CT (F-fluoro-deoxy-glucose positron emission tomography/computed tomography) is a useful tool to image multiple myeloma (MM). However, simple and reproducible reporting criteria are still lacking and there is the need for harmo...

Ga PSMA-11 PET with CT urography protocol in the initial staging and biochemical relapse of prostate cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Ga-labelled prostate specific membrane antigen (PSMA) ligand PET/CT is a promising modality in primary staging (PS) and biochemical relapse (BCR) of prostate cancer (PC). However, pelvic nodes or local recurrences can be difficult to diff...

Zero-Echo-Time and Dixon Deep Pseudo-CT (ZeDD CT): Direct Generation of Pseudo-CT Images for Pelvic PET/MRI Attenuation Correction Using Deep Convolutional Neural Networks with Multiparametric MRI.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone ...

Impact of pixel-based machine-learning techniques on automated frameworks for delineation of gross tumor volume regions for stereotactic body radiation therapy.

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)
The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques, i.e., fuzzy-c-means clustering method (FCM), and the artificial neural network (ANN) and support vector machine (SVM), on an automated framework for ...