Deep Learning Methods for Autism Spectrum Disorder Diagnosis Based on fMRI Images

Abstract

Brain injuries are significant disorders affecting human life. Some of these damages can be completely eliminated by methods such as drug therapy. On the other hand, there is no known permanent treatment for damages caused by diseases such as Alzheimer, Autism spectrum disorder (ASD), Multiple sclerosis and Parkinson. Treatments aimed at slowing the progression of the disease are generally applied in these types of disorders. For this reason, essential to diagnose the disease at an early phase before behavioral disorders occur. In this study, a study is presented to detect ASD through resting-state functional magnetic resonance imaging rs-fMRI. However, fMRI data are highly complex data. Within the study's scope, ASD and healthy individuals were distinguished on 871 samples obtained from the ABIDE I data set. The long short-term memory network (LSTM), convolutional neural network (CNN) , and hybrid models are used together for the classification process. The results obtained are promising for the detection of ASD on fMRI.

A Deep Learning Approach to Classify Autism Spectrum Disorder using MRI Images

“…Bayram, Muhammed Ali, et al [7], 2021, uses RNN and ACC of 74.74% are achieved and SENS is 72.95%. This study presents a promising approach for the early detection of ASD using rs-fMRI data, employing a combination of long short-term memory network (LSTM), CNN, and hybrid models on the dataset.…”

Comparison of different classification methods for autism spectrum diagnosis

“…Since LSTM can learn longterm dependency information, the final accuracy was improved by 9% over previous studies 22 . Furthermore, Bayram et al 23 compared the performance of different networks including LSTM, RNN, and CNN. The experimental results show that the LSTM network structure achieves accuracy slightly lower than that of RNN.…”

Analysis of Brain Imaging Data for the Detection of Early Age Autism Spectrum Disorder Using Transfer Learning Approaches for Internet of Things

“…Recently, data-driven approaches have been used to discover unique clusters of children with shared EF-related issues and brain structure features [5]. Common brain diseases include Alzheimer [6], brain cancer [7], schizophrenia [8,9], Autism [10], and psychiatric disorders [11-13] [8, 9, 14] etc. Autism spectrum disorder (ASD) is a common brain disease which affects many parts of the brain and causes neurological and developmental disability in a child (12-18 months) that can last throughout their life span [10,15].…”

“…Common brain diseases include Alzheimer [6], brain cancer [7], schizophrenia [8,9], Autism [10], and psychiatric disorders [11-13] [8, 9, 14] etc. Autism spectrum disorder (ASD) is a common brain disease which affects many parts of the brain and causes neurological and developmental disability in a child (12-18 months) that can last throughout their life span [10,15]. ASD shows various symptoms including learning disability, behavioural disability, abnormal body posture and facial expressions and poor eye contact etc.…”