Computer-aided diagnosis: A survey with bibliometric analysis
R Takahashi, Y Kajikawa - International journal of medical informatics, 2017 - Elsevier
Computer-aided diagnosis (CAD) has been a promising area of research over the last two
decades. However, CAD is a very complicated subject because it involves a number of …
decades. However, CAD is a very complicated subject because it involves a number of …
Medical Image Classification Based on Deep Features Extracted by Deep Model and Statistic Feature Fusion with Multilayer Perceptron
ZF Lai, HF Deng - Computational intelligence and …, 2018 - Wiley Online Library
Medical image classification is a key technique of Computer‐Aided Diagnosis (CAD)
systems. Traditional methods rely mainly on the shape, color, and/or texture features as well …
systems. Traditional methods rely mainly on the shape, color, and/or texture features as well …
Raspberry Pi assisted face recognition framework for enhanced law-enforcement services in smart cities
Similar to a fingerprint search system, face recognition technology can assist law
enforcement agencies in identifying suspects or finding missing persons. Face recognition …
enforcement agencies in identifying suspects or finding missing persons. Face recognition …
The fractional Fourier transform as a biomedical signal and image processing tool: A review
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 …
and applications in the biomedical field. The FrFT is a time-frequency analysis tool that has …
Brain tumor segmentation and classification by improved binomial thresholding and multi-features selection
A malignant tumor in brain is detected using images from Magnetic Resonance scanners.
Malignancy detection in brain and separation of its tissues from normal brain cells allows to …
Malignancy detection in brain and separation of its tissues from normal brain cells allows to …
[Retracted] Internet of Things with Deep Learning‐Based Face Recognition Approach for Authentication in Control Medical Systems
Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant
role in many applications, including medical and healthcare systems. It can help users in this …
role in many applications, including medical and healthcare systems. It can help users in this …
Polarimetric synthetic aperture radar image segmentation by convolutional neural network using graphical processing units
SH Wang, J Sun, P Phillips, G Zhao… - Journal of Real-Time …, 2018 - Springer
Image segmentation is an important application of polarimetric synthetic aperture radar. This
study aimed to create an 11-layer deep convolutional neural network for this task. The Pauli …
study aimed to create an 11-layer deep convolutional neural network for this task. The Pauli …
Fruit classification by biogeography‐based optimization and feedforward neural network
Accurate fruit classification is difficult to accomplish because of the similarities among the
various categories. In this paper, we proposed a novel fruit‐classification system, with the …
various categories. In this paper, we proposed a novel fruit‐classification system, with the …
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 …
Comparison of machine learning methods for stationary wavelet entropy-based multiple sclerosis detection: decision tree, k-nearest neighbors, and support vector …
In order to detect multiple sclerosis (MS) subjects from healthy controls (HCs) in magnetic
resonance imaging, we developed a new system based on machine learning. The MS …
resonance imaging, we developed a new system based on machine learning. The MS …