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Atrophy

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Alteration of the corpus callosum in patients with Alzheimer's disease: Deep learning-based assessment.

PloS one
BACKGROUND: Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysi...

Subtyping of mild cognitive impairment using a deep learning model based on brain atrophy patterns.

Cell reports. Medicine
Trajectories of cognitive decline vary considerably among individuals with mild cognitive impairment (MCI). To address this heterogeneity, subtyping approaches have been developed, with the objective of identifying more homogeneous subgroups. To date...

Peripapillary Atrophy Segmentation and Classification Methodologies for Glaucoma Image Detection: A Review.

Current medical imaging
Information-based image processing and computer vision methods are utilized in several healthcare organizations to diagnose diseases. The irregularities in the visual system are identified over fundus images with a fundus camera. Among ophthalmology ...

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learnin...

A deep learning method to assist with chronic atrophic gastritis diagnosis using white light images.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Chronic atrophic gastritis is a common preneoplastic condition of the stomach with a low detection rate during endoscopy.

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes.

Alzheimer's research & therapy
IMPORTANCE: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context.

Multi-modality MRI for Alzheimer's disease detection using deep learning.

Physical and engineering sciences in medicine
Diffusion tensor imaging (DTI) is a new technology in magnetic resonance imaging, which allows us to observe the insightful structure of the human body in vivo and non-invasively. It identifies the microstructure of white matter (WM) connectivity by ...

Voxel-based morphometry and a deep learning model for the diagnosis of early Alzheimer's disease based on cerebral gray matter changes.

Cerebral cortex (New York, N.Y. : 1991)
This study aimed to analyse cerebral grey matter changes in mild cognitive impairment (MCI) using voxel-based morphometry and to diagnose early Alzheimer's disease using deep learning methods based on convolutional neural networks (CNNs) evaluating t...