Conception et realisation d'un systeme de communication : en environnement multiprocesseurs, entre elements independants

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

An application of the wavelet theory to early breast cancer

International audienceMammography is one of the principal kinds of the medical images which is considered as the most efficient for the detection of breast cancer at its first step. Microcalcifications and Clustered microcalcifications are known to be the first sign of a development of an eventual cancer. They appear as small and bright regions with irregular shape in the breast. Their diversity in their shape, their orientation, their size and localisation in a dense mammogram are the cause of the major difficulty for their classification. The aim of our scheme is the development of a method for the detection and classification of all type of microcalcifications. The wavelet transform and its multiresolution analysis is well known as a powerful tool for non-stationary signal analysis. In fact its discrete version is closely related to filter banks. In this paper a technique using two different discrete wavelet transforms is used to provide a method for enhancing and controlling the detection of all types of small scale objects, microcalcifications, and separating them from large background structures. Hence, the detection and the enhancement of the microcalcifications is assured for each different type by using appropriate wavelet coefficients. Some numerical experiments are given

Enhanced identification of different types of microcalcifications using the wavelet transform method

International audienceMicrocalcifications and Clustered microcalcifications are known to be the first sign of a development of an eventual cancer. They appear as small and bright region with irregular shape in the breast. Their diversity in their shape, their directionality, their size and localisation in a dense mammogram confirm the major difficulty of their detection. The aim of our scheme is the de¬velopment of a method for the detection of all type of microcalcifications. The wavelet transform has recently emerged as a powerful tool for non-stationary signal analysis, its discrete version is closely related to filter banks. Also, multiresolution signal analysis has been used in image processing. This paper uses the relationship between these two techniques to provide a method of enhancing all type of microcalcifications. The digital mammograms are first processed by the wavelet transform with its multiresolution analysis. The enhancement of the microcalcifications is assured for each different type by using for an appropriate wavelet coefficients

How to Enable Delay Tolerant Network Solutions for Internet of Things: From Taxonomy to Open Challenges

Internet of Things (IoT) is witnessing an increasing range of application domains (industry 4.0, eHealth, smart city, etc.). Meanwhile, IoT is still facing communication challenges because of limited capabilities in computing, storage and energy constraints of smart objects. The use of Delay Tolerant Network (DTN) as basis for communication in IoT is promising but needs more development. In this paper, we present a literature review and a classification of DTN routing protocols. Furthermore, we survey a number of DTN solutions for IoT and propose a new taxonomy to motivate the importance of enabling DTN for IoT applications. The novelty of this classification is the focus on X-DTN category, which combines Delay Tolerant schemes with new technologies (e.g., Fog Computing). We also point out some open issues for potential Delay Tolerant IoT schemes