In this work, a bibliographic analysis on artificial neural networks (ANNs) using fractional
calculus (FC) theory has been developed to summarize the main features and applications …

This work presents a literature review of the fractional Fourier transform (FrFT) investigations
and applications in the biomedical field. The FrFT is a time-frequency analysis tool that has …

Detection of Alzheimer's disease (AD) from magnetic resonance images can help
neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain …

In order to detect the cerebral microbleed (CMB) voxels within brain, we used susceptibility
weighted imaging to scan the subjects. Then, we used undersampling to solve the accuracy …

(Aim) Classification of brain images as pathological or healthy case is a key pre-clinical step
for potential patients. Manual classification is irreproducible and unreliable. In this study, we …

AIM: Unilateral sensorineural hearing loss is a brain disease, which causes slight
morphology changes within brain structure. Traditional manual method may ignore this …

In this study, we proposed a smart detection method for abnormal breasts in digital
mammography. Firstly, preprocessing was carried out to deaden noises, enhance images …

Highlights We develop computer-aided diagnosis system for unilateral hearing loss
detection in structural magnetic resonance imaging. Wavelet entropy is introduced to extract …

The enormous information flow in our day today life, initiates the necessitates of the
identifying the valuable data that are to be concentrated. In case of image segmentation and …

Aim: It is beneficial to classify brain images as healthy or pathological automatically,
because 3D brain images can generate so much information which is time consuming and …