AIMC Topic: Wavelet Analysis
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A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction.
Medical physics
Oct 1, 2017
PURPOSE: Due to the potential risk of inducing cancer, radiation exposure by X-ray CT devices should be reduced for routine patient scanning. However, in low-dose X-ray CT, severe artifacts typically occur due to photon starvation, beam hardening, an...
Detection of Dendritic Spines Using Wavelet Packet Entropy and Fuzzy Support Vector Machine.
CNS & neurological disorders drug targets
Jan 1, 2017
The morphology of dendritic spines is highly correlated with the neuron function. Therefore, it is of positive influence for the research of the dendritic spines. However, it is tried to manually label the spine types for statistical analysis. In thi...
Stationary Wavelet Transform and AdaBoost with SVM Based Pathological Brain Detection in MRI Scanning.
CNS & neurological disorders drug targets
Jan 1, 2017
This paper presents an automatic classification system for segregating pathological brain from normal brains in magnetic resonance imaging scanning. The proposed system employs contrast limited adaptive histogram equalization scheme to enhance the di...
A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.
CNS & neurological disorders drug targets
Jan 1, 2017
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 tedious for manual analysis. Among various 3D brain imaging techniques, magn...
[A Classification Algorithm for Epileptic Electroencephalogram Based on Wavelet Multiscale Analysis and Extreme Learning Machine].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Dec 1, 2016
The automatic classification of epileptic electroencephalogram(EEG)is significant in the diagnosis and therapy of epilepsy.A classification algorithm for epileptic EEG based on wavelet multiscale analysis and extreme learning machine(ELM)is proposed ...
Preliminary research on abnormal brain detection by wavelet-energy and quantum- behaved PSO.
Technology and health care : official journal of the European Society for Engineering and Medicine
Apr 29, 2016
It is important to detect abnormal brains accurately and early. The wavelet-energy (WE) was a successful feature descriptor that achieved excellent performance in various applications; hence, we proposed a WE based new approach for automated abnormal...
[The Identification of the Origin of Chinese Wolfberry Based on Infrared Spectral Technology and the Artificial Neural Network].
Guang pu xue yu guang pu fen xi = Guang pu
Mar 1, 2016
The Fourier Transform Infrared Spectroscopy (FTIR) is established to find the geographic origins of Chinese wolfberry quickly. In the paper, the 45 samples of Chinese wolfberry from different places of Qinghai Province are to be surveyed by FTIR. The...
[Recognition of Low Arousal Level Electroencephalogram in the Vigilance Based on Wavelet Packet Rhythm and Support Vector Machine].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Feb 1, 2016
Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of monitoring work, low arousal level needs to be recognized and awakened. We proposed a recognition metho...
A new automated quantification algorithm for the detection and evaluation of focal liver lesions with contrast-enhanced ultrasound.
Medical physics
Jul 1, 2015
PURPOSE: Detect and classify focal liver lesions (FLLs) from contrast-enhanced ultrasound (CEUS) imaging by means of an automated quantification algorithm.
Physical activities recognition from ambulatory ECG signals using neuro-fuzzy classifiers and support vector machines.
Journal of medical engineering & technology
Feb 1, 2015
The use of wearable recorders for long-term monitoring of physiological parameters has increased in the last few years. The ambulatory electrocardiogram (A-ECG) signals of five healthy subjects with four body movements or physical activities (PA)-lef...
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