An effective way to improve the performance of deep neural networks in most computer vision tasks is quantity labeled data and quality labels. However, analysis processing medical images, high-quality annotation depends on experience professional knowledge experts, which makes it very difficult obtain a large number annotations. Therefore, we propose new semi-supervised framework for image clas...

Medical image classification as an important research topic both in image processing and biomedical engineering. The ridgelet transform has good directional selective ability to locally and sparsely in representing the image compared with the traditional wavelet transform. This paper proposes a novel classification model for medical image, which is using ridgelet transform and dynamic fuzzy the...

Medical image classification as an important research topic both in image processing and biomedical engineering. The ridgelet transform has good directional selective ability to locally and sparsely in representing the image compared with the traditional wavelet transform. This paper proposes a novel classification model for medical image, which is using ridgelet transform and dynamic fuzzy the...

Automatic medical image classification refers to assigning an medical image into a class, among a number of image categories. Due to computational complexity, it is an important task in the content based image retrieval (CBIR). In this paper, we propose a method for classification and retrieval of medical images using multi-feature extraction method. Here, edge and patch based methods are used ...

Medical image processing is the technique used to create images of the human body for medical purposes. Nowadays, medical image processing plays a major role and a challenging solution for the critical stage in the medical line. Several researches have done in this area to enhance the techniques for medical image processing. However, due to some demerits met by some advanced technologies, there...

as the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. this processing comprises two fundamental and critical steps towar...

Image representation is one of the major aspects of automatic classification algorithms. In this paper, different feature extraction techniques have been utilized to represent medical X-ray images. They are categorized into two groups; (i) low-level image representation such as Gray Level Co-occurrence Matrix(GLCM), Canny Edge Operator, Local Binary Pattern(LBP) , pixel value, and (ii) local pa...

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...