Domain adaptation for medical image analysis: a survey

H Guan, M Liu - IEEE Transactions on Biomedical Engineering, 2021 - ieeexplore.ieee.org
Machine learning techniques used in computer-aided medical image analysis usually suffer
from the domain shift problem caused by different distributions between source/reference …

Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review

MA Ebrahimighahnavieh, S Luo, R Chiong - Computer methods and …, 2020 - Elsevier
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …

Alzheimer disease detection empowered with transfer learning

TM Ghazal, G Issa - Computers, Materials & …, 2022 - research.skylineuniversity.ac.ae
Alzheimer's disease is a severe neuron disease that damages brain cells which leads to
permanent loss of memory also called dementia. Many people die due to this disease every …

Deep learning approach for early detection of Alzheimer's disease

HA Helaly, M Badawy, AY Haikal - Cognitive computation, 2022 - Springer
Alzheimer's disease (AD) is a chronic, irreversible brain disorder, no effective cure for it till
now. However, available medicines can delay its progress. Therefore, the early detection of …

Convolutional neural network based Alzheimer's disease classification from magnetic resonance brain images

R Jain, N Jain, A Aggarwal, DJ Hemanth - Cognitive Systems Research, 2019 - Elsevier
Alzheimer's disease, the most common form of dementia is a neurodegenerative brain order
that has currently no cure for it. Hence, early diagnosis of such disease using computer …

A systematic survey of computer-aided diagnosis in medicine: Past and present developments

J Yanase, E Triantaphyllou - Expert Systems with Applications, 2019 - Elsevier
Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort
expended in the interface of medicine and computer science. As some CAD systems in …

A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

S Rathore, M Habes, MA Iftikhar, A Shacklett… - NeuroImage, 2017 - Elsevier
Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …

Predicting brain-age from multimodal imaging data captures cognitive impairment

F Liem, G Varoquaux, J Kynast, F Beyer, SK Masouleh… - Neuroimage, 2017 - Elsevier
The disparity between the chronological age of an individual and their brain-age measured
based on biological information has the potential to offer clinically relevant biomarkers of …

Why rankings of biomedical image analysis competitions should be interpreted with care

L Maier-Hein, M Eisenmann, A Reinke… - Nature …, 2018 - nature.com
International challenges have become the standard for validation of biomedical image
analysis methods. Given their scientific impact, it is surprising that a critical analysis of …

Alzheimer's disease diagnostics by a deeply supervised adaptable 3D convolutional network

E Hosseini-Asl, G Gimel'farb, A El-Baz - arxiv preprint arxiv:1607.00556, 2016 - arxiv.org
Early diagnosis, playing an important role in preventing progress and treating the
Alzheimer's disease (AD), is based on classification of features extracted from brain images …