Outlier-based Autism Detection using Longitudinal Structural MRI

02/21/2022
by   Devika K, et al.
21

Diagnosis of Autism Spectrum Disorder (ASD) using clinical evaluation (cognitive tests) is challenging due to wide variations amongst individuals. Since no effective treatment exists, prompt and reliable ASD diagnosis can enable the effective preparation of treatment regimens. This paper proposes structural Magnetic Resonance Imaging (sMRI)-based ASD diagnosis via an outlier detection approach. To learn Spatio-temporal patterns in structural brain connectivity, a Generative Adversarial Network (GAN) is trained exclusively with sMRI scans of healthy subjects. Given a stack of three adjacent slices as input, the GAN generator reconstructs the next three adjacent slices; the GAN discriminator then identifies ASD sMRI scan reconstructions as outliers. This model is compared against two other baselines – a simpler UNet and a sophisticated Self-Attention GAN. Axial, Coronal, and Sagittal sMRI slices from the multi-site ABIDE II dataset are used for evaluation. Extensive experiments reveal that our ASD detection framework performs comparably with the state-of-the-art with far fewer training data. Furthermore, longitudinal data (two scans per subject over time) achieve 17-28 cross-sectional data (one scan per subject). Among other findings, metrics employed for model training as well as reconstruction loss computation impact detection performance, and the coronal modality is found to best encode structural information for ASD detection.

READ FULL TEXT

page 4

page 8

page 9

page 10

page 14

page 20

research
07/24/2020

MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction

Unsupervised learning can discover various unseen diseases, relying on l...
research
08/09/2022

Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network

Missing scans are inevitable in longitudinal studies due to either subje...
research
09/15/2023

Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs

The cross-modal synthesis between structural magnetic resonance imaging ...
research
09/12/2021

Differential Diagnosis of Frontotemporal Dementia and Alzheimer's Disease using Generative Adversarial Network

Frontotemporal dementia and Alzheimer's disease are two common forms of ...
research
08/04/2021

MRI to PET Cross-Modality Translation using Globally and Locally Aware GAN (GLA-GAN) for Multi-Modal Diagnosis of Alzheimer's Disease

Medical imaging datasets are inherently high dimensional with large vari...
research
06/14/2019

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

Leveraging large-scale healthy datasets, unsupervised learning can disco...
research
02/25/2022

Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglement

Cycle reconstruction regularized adversarial training – e.g., CycleGAN, ...

Please sign up or login with your details

Forgot password? Click here to reset