Comprehensive review on twin support vector machines
Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly
emerging efficient machine learning techniques which offer promising solutions for …
emerging efficient machine learning techniques which offer promising solutions for …
Automated detection of Alzheimer's disease using brain MRI images–a study with various feature extraction techniques
UR Acharya, SL Fernandes, JE WeiKoh… - Journal of medical …, 2019 - Springer
The aim of this work is to develop a Computer-Aided-Brain-Diagnosis (CABD) system that
can determine if a brain scan shows signs of Alzheimer's disease. The method utilizes …
can determine if a brain scan shows signs of Alzheimer's disease. The method utilizes …
Convolutional neural networks for multi-class brain disease detection using MRI images
The brain disorders may cause loss of some critical functions such as thinking, speech, and
movement. So, the early detection of brain diseases may help to get the timely best …
movement. So, the early detection of brain diseases may help to get the timely best …
Color image encryption using non-dominated sorting genetic algorithm with local chaotic search based 5D chaotic map
The secure key generation is the predominant requirement of an image encryption. Chaotic
maps are often considered by the researchers for secure key generation. However, chaotic …
maps are often considered by the researchers for secure key generation. However, chaotic …
An efficient approach for the detection of brain tumor using fuzzy logic and U-NET CNN classification
Clinical diagnosis has increased marvelous significance in current day healthcare systems.
This article proposes a brain tumor detection method using edge detection based fuzzy logic …
This article proposes a brain tumor detection method using edge detection based fuzzy logic …
Self-supervised multi-modal hybrid fusion network for brain tumor segmentation
Accurate medical image segmentation of brain tumors is necessary for the diagnosing,
monitoring, and treating disease. In recent years, with the gradual emergence of multi …
monitoring, and treating disease. In recent years, with the gradual emergence of multi …
Application of multiresolution analysis for automated detection of brain abnormality using MR images: A comparative study
Neurological disorders are abnormalities related to the human nervous system, and
comprise electrical, biochemical, or structural changes in the spinal cord, brain, or central …
comprise electrical, biochemical, or structural changes in the spinal cord, brain, or central …
Multiple sclerosis detection based on biorthogonal wavelet transform, RBF kernel principal component analysis, and logistic regression
To detect multiple sclerosis (MS) diseases early, we proposed a novel method on the
hardware of magnetic resonance imaging, and on the software of three successful methods …
hardware of magnetic resonance imaging, and on the software of three successful methods …
Brain pathology identification using computer aided diagnostic tool: A systematic review
Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-
of-life by reducing human errors in diagnosis. CAD can expedite decision-making on …
of-life by reducing human errors in diagnosis. CAD can expedite decision-making on …
Diagnosis of Alzheimer's Disease Using Dual‐Tree Complex Wavelet Transform, PCA, and Feed‐Forward Neural Network
Background. Error‐free diagnosis of Alzheimer's disease (AD) from healthy control (HC)
patients at an early stage of the disease is a major concern, because information about the …
patients at an early stage of the disease is a major concern, because information about the …