AI Medical Compendium Journal:
Bio-medical materials and engineering

Showing 31 to 38 of 38 articles

Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

Bio-medical materials and engineering
This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangio...

A novel method of diagnosing premature ventricular contraction based on sparse auto-encoder and softmax regression.

Bio-medical materials and engineering
Premature ventricular contraction (PVC) is one of the most serious arrhythmias. Without early diagnosis and proper treatment, PVC can result in significant complications. In this paper, a novel feature extraction method based on a sparse auto-encoder...

Automatic segmentation in image stacks based on multi-constraint level-set evolution.

Bio-medical materials and engineering
Contour extraction of image stacks is a basic task in medical modeling. The existing level-set methods usually suffer from some problems (e.g. serious errors around sharp features, incorrect split of topology and contour occlusions). This paper propo...

Image manifold revealing for breast lesion segmentation in DCE-MRI.

Bio-medical materials and engineering
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used for breast lesion differentiation. Manual segmentation in DCE-MRI is difficult and open to viewer interpretation. In this paper, an automatic segmentation method based on i...

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

Bio-medical materials and engineering
Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, no...

Nonholonomic mobile system control by combining EEG-based BCI with ANFIS.

Bio-medical materials and engineering
Motor imagery EEG-based BCI has advantages in the assistance of human control of peripheral devices, such as the mobile robot or wheelchair, because the subject is not exposed to any stimulation and suffers no risk of fatigue. However, the intensive ...

A novel approach for arrhythmia diagnosis: Self-adaptive and distribution-free mode.

Bio-medical materials and engineering
Arrhythmia diagnosis is very significant to ensure human health. In this paper, a new model is developed for arrhythmia diagnosis. A salient feature of the algorithm is a synergistic combination of statistical and fuzzy set-based techniques. It is di...