DeepAI AI Chat
Log In Sign Up

Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN

by   Wen Yu, et al.
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences

The diagnosis of early stages of Alzheimer's disease (AD) is essential for timely treatment to slow further deterioration. Visualizing the morphological features for the early stages of AD is of great clinical value. In this work, a novel Multidirectional Perception Generative Adversarial Network (MP-GAN) is proposed to visualize the morphological features indicating the severity of AD for patients of different stages. Specifically, by introducing a novel multidirectional mapping mechanism into the model, the proposed MP-GAN can capture the salient global features efficiently. Thus, by utilizing the class-discriminative map from the generator, the proposed model can clearly delineate the subtle lesions via MR image transformations between the source domain and the pre-defined target domain. Besides, by integrating the adversarial loss, classification loss, cycle consistency loss and L1 penalty, a single generator in MP-GAN can learn the class-discriminative maps for multiple-classes. Extensive experimental results on Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset demonstrate that MP-GAN achieves superior performance compared with the existing methods. The lesions visualized by MP-GAN are also consistent with what clinicians observe.


page 1

page 2

page 4

page 7

page 8

page 10

page 11


Tensorizing GAN with High-Order Pooling for Alzheimer's Disease Assessment

It is of great significance to apply deep learning for the early diagnos...

GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis

Leveraging large-scale healthy datasets, unsupervised learning can disco...

CatGAN: Coupled Adversarial Transfer for Domain Generation

This paper introduces a Coupled adversarial transfer GAN (CatGAN), an ef...

DecGAN: Decoupling Generative Adversarial Network detecting abnormal neural circuits for Alzheimer's disease

One of the main reasons for Alzheimer's disease (AD) is the disorder of ...

Interpretation of Disease Evidence for Medical Images Using Adversarial Deformation Fields

The high complexity of deep learning models is associated with the diffi...