AIMC Topic: Image Processing, Computer-Assisted

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Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier.

Journal of medical systems
In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of ...

A Feature Learning and Object Recognition Framework for Underwater Fish Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Live fish recognition is one of the most crucial elements of fisheries survey applications where the vast amount of data is rapidly acquired. Different from general scenarios, challenges to underwater image recognition are posted by poor image qualit...

Merge Fuzzy Visual Servoing and GPS-Based Planning to Obtain a Proper Navigation Behavior for a Small Crop-Inspection Robot.

Sensors (Basel, Switzerland)
The concept of precision agriculture, which proposes farming management adapted to crop variability, has emerged in recent years. To effectively implement precision agriculture, data must be gathered from the field in an automated manner at minimal c...

A Novel Sparse Dictionary Learning Separation (SDLS) Model With Adaptive Dictionary Mutual Incoherence Constraint for fMRI Data Analysis.

IEEE transactions on bio-medical engineering
OBJECTIVE: Many studies have shown that the independence assumption in the widely-used ICAs is not adaptive enough for brain functional networks (BFN) detection due to the complex brain hemodynamics, functional integration, artifacts embedded in func...

A multi-layer network approach to MEG connectivity analysis.

NeuroImage
Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of the electrophysiolo...

Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

Journal of biomolecular screening
Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning ...

Data mining framework for identification of myocardial infarction stages in ultrasound: A hybrid feature extraction paradigm (PART 2).

Computers in biology and medicine
Early expansion of infarcted zone after Acute Myocardial Infarction (AMI) has serious short and long-term consequences and contributes to increased mortality. Thus, identification of moderate and severe phases of AMI before leading to other catastrop...

Automated single cell isolation from suspension with computer vision.

Scientific reports
Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently...

HEp-2 Cell Image Classification With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Efficient Human Epithelial-2 cell image classification can facilitate the diagnosis of many autoimmune diseases. This paper proposes an automatic framework for this classification task, by utilizing the deep convolutional neural networks (CNNs) which...