Development of an Image Retrieval Model for Biomedical Image Databases

Abstract

Image processing is the field of signal processing where both the input and output signals are images. Images can be thought of as two-dimensional signals via a matrix representation. Image processing a is very important subject, and finds itself in such fields as photography, satellite imaging, medical imaging, and image compression, to name but a few. In the past, image processing was largely done using analog devices (Cheng et al., 2006). However, as computers became more powerful, processing shifted toward the digital domain. Like one-dimensional digital signal processing, digital image processing overcomes traditional analog "problems" such as noise, distortion during processing, inflexibility of system to change, and difficulty of implementation. Image retrieval, popularly referred to as content-based image retrieval is an emerging technology that allows a user to retrieve relevant images in an effective and efficient manner. Digital imaging has extensive applications in our daily lives and it is being used for several applications. Examples of imaging applications are in museums for archiving important images and manuscripts from art gallery and museum management. Many useful applications of imaging are found in security for tracking an intruder, crime prevention, law enforcement and object recognition in digital forensic. In particular, image retrieval is potentially useful in discovering brain activation patterns, in classifications and in diagnoses by comparing observed patterns with those of known diseases, leading to clinical applications. In biomedicine, content-based image retrieval is critically important in patient digital libraries, clinical diagnosis, clinical trials, searching for 2-D electrophoresis gels, and pathological slides. Most existing content-based image retrieval systems (Flickner et al., 1995; Gupta and Jain, 1997; Ma and Manjunath, 1997; Rubner, 1999 and Wang et al., 1998) are designed for general purpose picture libraries such as photos and graph. The storage, manipulation and analysis of the contents of digital images are essential requirements for the next generation of healthcare information infrastructure. The aim of this infrastructure is to bring timely health information to support communication among healthcare decision makers and communities at large. Among several healthcare services that can be provided with the aid of the emerging grid technology for ubiquitous access, image classification and diagnosis services are important. The ubiquitous access and