B. Solaiman

Computer-assisted diagnosis system in digestive endoscopy

The purpose of this paper is to present an intelligent atlas of indexed endoscopic lesions that could be used in computer-assisted diagnosis as reference data. The development of such a system requires a mix of medical and engineering skills for analyzing and reproducing the cognitive processes that underlie the medical decision-making process. The analysis of both endoscopists experience and endoscopic terminologies developed by professional associations shows that diagnostic reasoning in digestive endoscopy uses a scene-object approach. The objects correspond to the endoscopic findings and the medical context of examination and the scene to the endoscopic diagnosis. According to expert assessment, the classes of endoscopic findings and diagnoses, their primitive characteristics (or indices), and their relationships have been listed. Each class describes an endoscopic finding or diagnosis in an intensive way. The retrieval method is based on a similarity metric that estimates the membership value of the case under investigation and the prototype of the class. A simulation test with randomized objects demonstrates a good classification of endoscopic findings. The correct class is the unique response in 68% of the tested objects, the first of multiple responses in 28%. Four descriptors are shown to be of major importance in the classification algorithm: anatomic location, shape, color, and relief. At the present time, the application database contains approximately 150 endoscopic images and is accessible via Internet. Experiments are in progress with endoscopists for the validation of the system and for the understanding of the similarity between images. The next step will integrate the system in a learning tool for junior endoscopists.

Medical image compression using region-of-interest vector quantization

In this paper, we propose a region based image compression approach for medical applications. We use a vector quantization scheme, combined with regions-of-interest. The image to be compressed is first segmented into regions and a separate codebook is used for each specified region. Codeword size and number of codewords by codebooks may be different according to the diagnostic importance of the corresponding image region. This permits to create appropriate codebooks with representative codewords, and to obtain good reconstruction quality in relevant zones, while reinforcing compression in less important regions. The proposed approach is tested on ultrasound esophagus images and is shown to be very promising.

Information fusion concepts: from information elements definition to the application of fusion approaches

The aim of this paper is to give a homogeneous and a simple framework in order to present information fusion concepts. The main concept presented here concerns the definition of the information element concept. This concept is then illustrated through the general scheme of pattern recognition systems. Different types of information imperfection are then illustrated. Finally, information fusion concepts and fusion architecture are illustrated.

Esophageal wall detection using endosonographic imaging systems

An endosonographic imaging system permitting esophageal neoplasm evaluation is presented. Several 2D processing methods applied on these images are presented. The architecture of a new imaging system including the existing one is shown. This new system permits 3D studies and consequently improves the interpretation stage.

Dempster-Shafer theory for multi-satellite remotely sensed observations

This study suggests a slight variation of the Dempster- Shafer theory using observation qualification in multi- sensor contexts. The uncertainty is placed on the rules instead of on sources. Thus, sensors specialization is taken into account. By this approach, the masses are not directly attributed on the frame of discernment elements, but on the rules themselves that become the sources of knowledge, in the context of Dempster combining rule. It proposes then an approach for observation qualification in a multi-sensor context, as well as it suggests a new path for the delicate task of mass attribution.

Improving spatial vector quantization for image compression by use of a quadtree scheme. Application to echoendoscopic image compression

Image coding using vector quantization is an interesting approach for image compression. Among the different existing algorithms, Kohonens self-organizing feature maps (SOFMs) are well suited for designing the codebooks because of their specific properties. Moreover, the use of this method for compression gives, in the same process, basic information on the image content, but to preserve the diagnostic accuracy in echoendoscopic images, it is necessary to take small codewords, generally not greater than subimages of 3 by 3 pixels, which limits the compression rate. We propose to improve the compression rate by using four codebooks, with codewords of different size. Image analysis for coding uses a quadtree scheme. Results are compared with those obtained using the standard JPEG image compression algorithm.

Telemedicine in developing countries; Case of Tunisia

Telemedicine and more largely e-health should be considered as one of the strategic components in the national health care system since this assists the delivery of equitable health-care and the accessibility of specific skills. Through telemedicine patients can get access to medical expertise that may not be able at the patients site. Advanced technology such as informatics, medical imaging, robotics, voice activated machines, and remote controls have changed the hospital and operating room to accessible zones in all parts of the world and distance has become meaningless in modern times. Telemedicine networks contribute to the improvement of the medical care quality and to the cost effective use of medical resources. It have a strong impact in developing countries since it allows remote parts to get access to medical care and create local knowledge. The Tunisian experience in Telemedicine is significant and has begun on 90 by scientific meetings with local and international links between researchers. Numerous projects and significant networks have been established in order to set up links and connections between Tunisian hospitals and medical centers in one hand and between Tunisian and foreign hospitals in other hand. This article presents the advantages of Telemedicine and its necessity in developing countries. The Tunisian experience is then detailed and discussed.

Space-Time Adaptive Processing analysis for the moving target on the sea surface indication purpose

Space-time adaptive processing (STAP) can improve target detectability in a presence of a ground clutter for airborne radar. Ground clutter echo has a wide spectrum as a result of the radar platform (airplane or satellite) motion. To reject clutter echo and preserve target echo, STAP employs antenna array. Simultaneous filtering in both spatial (angle) and frequency domain can improve performance. In this paper we propose a new application of STAP. Assuming an antenna array standing on a sea shore, the objective is to detect targets on the sea surface. Unfortunately sea clutter has different statistical properties compared to airborne clutter. As a consequence, basic STAP algorithm is not optimal in any sense. Future research will face the problem of evaluating performance of STAP applied to sea clutter. We hope to develop a new algorithm that can perform better in the presence of sea clutter.

A new image watermarking scheme for medical image archiving

The exchange of databases between hospitals requires efficient transmission and storage to reduce the cost of health care. This exchange involves a large amount of vital patient information such as patient details, history and measured physiological signals, documents and medical images. This paper presents a technique of interleaving patient information such as text documents and physiological signals with medical images for efficient storage and secure transmission. Our embedding and extracting schemes for digital watermarking of medical images with hidden patient information is proposed as a way to effectively reduce memory requirements, provide protection of information and reduce time and cost of transmission. We present this new method with more details

Enabling technology for telemedicine and telehealth

Telemedicine is a growing field and has to face various challenges like its integration to the medical practice and to the health care system, its economic implication and its social impact. This paper will focus on the technological aspects of telemedicine that will be first reviewed. Three main dimensions will be shown to structure the technological space of telemedicine: network, information processing and knowledge engineering. These three components will be briefly discussed. In a second part we will develop three specific issues addressing challenging image and knowledge engineering problems (multimedia medical image management, multimedia medical knowledge bases constitution and management, and case-based reasoning in diagnostic imaging and medical data mining).