AIMC Topic: Pattern Recognition, Automated

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BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species.

BioMed research international
MicroRNAs (miRNAs) are a set of short (21-24 nt) noncoding RNAs that play significant regulatory roles in cells. In the past few years, research on miRNA-related problems has become a hot field of bioinformatics because of miRNAs' essential biologica...

Using Anatomic Intelligence to Localize Mitral Valve Prolapse on Three-Dimensional Echocardiography.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Accurate localization of mitral valve prolapse (MVP) is crucial for surgical planning. Despite improved visualization of the mitral valve by three-dimensional transesophageal echocardiography, image interpretation remains expertise depend...

Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection.

BioMed research international
Automatic liver segmentation not only plays an important role in the analysis of liver disease, but also reduces the cost and humanity's impact in segmentation. In addition, liver segmentation is a very challenging task due to countless anatomical va...

A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor imagery classification is an important topic in brain-computer interface (BCI) research that enables the recognition of a subject's intension to, e.g., implement prosthesis control. The brain dynamics of motor imagery are usually measured by el...

Role of Muscle Synergies in Real-Time Classification of Upper Limb Motions using Extreme Learning Machines.

Journal of neuroengineering and rehabilitation
BACKGROUND: Myoelectric signals offer significant insights in interpreting the motion intention and extent of effort involved in performing a movement, with application in prostheses, orthosis and exoskeletons. Feature extraction plays a vital role, ...

Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network.

BioMed research international
Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI) image which contains the liver tumo...

Unsupervised delineation of stratum corneum using reflectance confocal microscopy and spectral clustering.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Measuring the thickness of the stratum corneum (SC) in vivo is often required in pharmacological, dermatological, and cosmetological studies. Reflectance confocal microscopy (RCM) offers a non-invasive imaging-based approach. However, RCM...

Development of Health Parameter Model for Risk Prediction of CVD Using SVM.

Computational and mathematical methods in medicine
Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared th...

A Feature Selection Approach Based on Interclass and Intraclass Relative Contributions of Terms.

Computational intelligence and neuroscience
Feature selection plays a critical role in text categorization. During feature selecting, high-frequency terms and the interclass and intraclass relative contributions of terms all have significant effects on classification results. So we put forward...

DeepFruits: A Fruit Detection System Using Deep Neural Networks.

Sensors (Basel, Switzerland)
This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it i...