Abstract
Alzheimer’s disease (AD) is an irreversible progressive cerebral disease with most of its symptoms appearing after 60 years of age. Alzheimer’s disease has been largely attributed to accumulation of amyloid beta (Aβ), but a complete cure has remained elusive. 18F-Florbetaben amyloid positron emission tomography (PET) has been shown as a more powerful tool for understanding AD-related brain changes than magnetic resonance imaging and computed tomography. In this paper, we propose an accurate classification method for scoring brain amyloid plaque load (BAPL) based on deep convolutional neural networks. A joint discriminative loss function was formulated by adding a discriminative intra-loss function to the conventional (cross-entropy) loss function. The performance of the proposed joint loss function was compared with that of the conventional loss function in three state-of-the-art deep neural network architectures. The intra-loss function significantly improved the BAPL classification performance. In addition, we showed that the mix-up data augmentation method, originally proposed for natural image classification, was also useful for medical image classification.
Highlights
Alzheimer’s disease (AD) is an irreversible progressive cerebral disease with most of its symptoms appearing after 60 years of age
The positron emission tomography (PET) images were reconstructed by UltraHD-PET (TrueX-TOF)
The results suggest that the coronal plane contains more useful information for the classification of brain amyloid-β plaque load (BAPL) scores which are extracted by deep learning
Summary
Alzheimer’s disease (AD) is an irreversible progressive cerebral disease with most of its symptoms appearing after 60 years of age. Alzheimer’s disease currently affects approximately 46.8 million people worldwide and may reach 132 million people in 2050 [1]. A complete cure for AD has remained elusive. Accurate and early diagnosis of AD is essential for treating patients and for developing future treatments. Accumulation of amyloid beta (Aβ) is considered as a diagnostic feature of Alzheimer’s disease. 18F-florbetaben (FBB) amyloid positron emission tomography (PET) is a more powerful tool for understanding AD-related brain changes than magnetic resonance imaging (MRI) and computed tomography (CT) [2,3]
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