The complexity of multimedia contents is significantly increasing in the current digital world.
This yields an exigent demand for develo** highly effective retrieval systems to satisfy …

Content-based image retrieval (CBIR) technology has been proposed to benefit not only the
management of increasingly large image collections, but also to aid clinical care, biomedical …

In this paper we propose a new and efficient texture feature extraction method: the
Segmentation-based Fractal Texture Analysis, or SFTA. The extraction algorithm consists in …

Heart disease is a category of various conditions that affect the heart, which includes
multiple diseases that influence its structure and operation. Such conditions may consist of …

Lung cancer is an important global health problem, and it is defined by abnormal growth of
the cells in the tissues of the lung, mostly leading to significant morbidity and mortality. Its …

In this paper, we describe the design and development of a multitiered content-based image
retrieval (CBIR) system for microscopic images utilizing a reference database that contains …

Context-aware mobile computing requires wearable sensors to acquire information about
the user. Continuous sensing rapidly depletes the-wearable system's energy, which is a …

In todays health care, imaging plays an important role throughout the entire clinical process
from diagnostics and treatment planning to surgical procedures and follow up studies. Since …

This paper brings a solution for bridging the gap between the results of state-of-the-art
automatic classification algorithms and high semantic human-defined manually created …

This paper is aimed at develo** and evaluating a content-based retrieval method for
contrast-enhanced liver computed tomographic (CT) images using bag-of-visual-words …