AIMC Topic: Atrophy

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Large-Vessel Vasculopathy in Children With Sickle Cell Disease: A Magnetic Resonance Imaging Study of Infarct Topography and Focal Atrophy.

Pediatric neurology
BACKGROUND: Large-vessel vasculopathy (LVV) increases stroke risk in pediatric sickle cell disease beyond the baseline elevated stroke risk in this vulnerable population. The mechanisms underlying this added risk and its unique impact on the developi...

HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

NeuroImage
Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodolo...

The modified tower vertical filler technique for the treatment of post-acne scarring.

The Australasian journal of dermatology
BACKGROUND: Acne scarring remains a difficult problem for patients and physicians. Often it is treated as a two-dimensional disease with lasers and similar devices, whereas it is really a three-dimensional problem. Fillers have been used for many yea...

Boosting diagnosis accuracy of Alzheimer's disease using high dimensional recognition of longitudinal brain atrophy patterns.

Behavioural brain research
OBJECTIVE: Boosting accuracy in automatically discriminating patients with Alzheimer's disease (AD) and normal controls (NC), based on multidimensional classification of longitudinal whole brain atrophy rates and their intermediate counterparts in an...

Redefining diagnostic lesional status in temporal lobe epilepsy with artificial intelligence.

Brain : a journal of neurology
Despite decades of advancements in diagnostic MRI, 30%-50% of temporal lobe epilepsy (TLE) patients remain categorized as 'non-lesional' (i.e. MRI negative) based on visual assessment by human experts. MRI-negative patients face diagnostic uncertaint...

Segmentation with artificial intelligence and automated calculation of the corpus callosum index in multiple sclerosis.

Saudi medical journal
OBJECTIVES: To determine the corpus callosum index (CCI) differences between chronic phase multiple sclerosis (MS) patients and healthy individuals and to evaluate the corpus callosum segmentation in MS patients using artificial intelligence technolo...

Generalizable Deep Learning for the Detection of Incomplete and Complete Retinal Pigment Epithelium and Outer Retinal Atrophy: A MACUSTAR Report.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop a deep learning algorithm for detecting and quantifying incomplete retinal pigment epithelium and outer retinal atrophy (iRORA) and complete retinal pigment epithelium and outer retinal atrophy (cRORA...

Artificial intelligence classifies primary progressive aphasia from connected speech.

Brain : a journal of neurology
Neurodegenerative dementia syndromes, such as primary progressive aphasias (PPA), have traditionally been diagnosed based, in part, on verbal and non-verbal cognitive profiles. Debate continues about whether PPA is best divided into three variants an...

Application of artificial intelligence-based magnetic resonance imaging in diagnosis of cerebral small vessel disease.

CNS neuroscience & therapeutics
Cerebral small vessel disease (CSVD) is an important cause of stroke, cognitive impairment, and other diseases, and its early quantitative evaluation can significantly improve patient prognosis. Magnetic resonance imaging (MRI) is an important method...

Sequence of Morphological Changes Preceding Atrophy in Intermediate AMD Using Deep Learning.

Investigative ophthalmology & visual science
PURPOSE: Investigating the sequence of morphological changes preceding outer plexiform layer (OPL) subsidence, a marker preceding geographic atrophy, in intermediate AMD (iAMD) using high-precision artificial intelligence (AI) quantifications on opti...