Feature encoding plays an important role for medical image classification. Intra-cluster features such as bag of visual words have been widely used for feature encoding, which are based on the statistical information within each clusters of local features and therefore fail to capture the inter-cluster statistics, such as how the visual words co-occur in images. This paper proposes a new method...

In this paper, two Medical image Classification can play an important role in diagnostic and teaching purposes in medicine. For these purposes different imaging modalities are used. There are many classifications created for medical images using both grey-scale and color medical images. One way is to find the texture of the images and have the analysis. Texture classification is an image proces...

Abstratct: In this paper, we present a method for classification of medical images. Wavelet features of different modalities of medical images are extracted. Then mean and standard deviation of extracted wavelet features are computed. We utilize KNearest Neighbor classifier to classify medical imaging modalities as X-ray, MRI and CT. Experiments are conducted on medical database containing 4,50...

Many medical image classification tasks share a common unbalanced data problem. That is images of the target classes, e.g., certain types of diseases, only appear in a very small portion of the entire dataset. Nowadays, large co llections of medical images are readily available. However, it is costly and may not even be feasible for medical experts to manually comb through a huge unlabeled data...

Ray Casting is a direct volume rendering technique for visualizing 3D arrays of sampled data. It has vital applications in medical and biological imaging. Nevertheless, it is inherently open to cluttered classification results. It suffers from overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. In this work, we are proposing an ...

Image mining is one of the predominant researches in computer science field. It is a process of extracting valuable information from a huge amount of dataset. In image mining, there are several techniques are adopted such as image classification, image clustering, regression analysis and association rule mining. In this work, we have concentrated on image classification technique to analyze the...

This paper discusses results and methods used to automatically classify medical images for Content Based Image Retrieval (CBIR) systems. Using a supervised learning approach, we automatically classified over 3,000 medical images according to the four facets of IRMA classification code (that's image modality, body orientation, biological system, and anatomical part). Our best results were obtain...

introduction:in this study, ecg signals have been embedded into medical images to create a novel blind watermarking method. the embedding is done when the original image is compressed using the ezw algorithm. the extraction process is performed at the decompression time of the watermarked image. materials and methods: the multi-resolution watermarking with a secret key algorithm developed in th...