Telemedicine has been developed to allow practitioners to remotely connect with patients and with other medical staff. We propose a new system (hardware and software), named DICODERM (COllaborative DIagnosis of DERMatosis), which makes it possible to monitor the evolution of scars after the excision of a tumorous dermatosis (like melanoma). The hardware part of this system is composed of a new optical innovative probe with which two types of images can be acquired simultaneously: anatomic with a white light image and functional with a fluorescence image (using autofluorescence from the protoporphyrin within the cancer cell). The software part is composed of two components: the image stitching component, and the collaborative/adaptive layer component. Our system creates a panoramic view of these scars obtained by stitching a sequence of small images. We conducted experiments for different image stitching algorithms to define the best solution. We also deployed a second component: a collaborative system layer which allows to remotely share images of scars and to adapt these images. We also made the system adaptive to communicate across different client platforms. We conducted experiments to compare the exchange of images with or without adaptation: these tests showed the efficiency of our layer.

Abstract. The progressive needs of video streaming for different applications in varied domains have created a new set of heterogeneous environments especially in Virtual Collaborative Environments. In order to get the best performance of such environments, video streaming has to be adapted to the different parameters that characterize these environments, namely: bandwidth, CPU, GPU, screen resolution, etc. In this paper, we define a new Web Service, named Wava (Web Service for Automatic Video Data Flows Adaptation). Wava allows multimedia platforms and collaborative application servers to adjust the adaptation at two levels: at the static level during initialization and at the dynamic level according to the variation of the environment.

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Telemedicine, the application of telecommunication in the medicine field, has been developed to meet major problems encountered in connecting doctors to collaborate with patients and other medical staff. Having a robust and efficient telemedical system has always been a challenge. The system needs to make the members in different locations capable of sharing medical data efficiently and without errors. In this work, we present a telemedical system that overcomes these challenges. We deploy a collaborative system and adapt data to store, visualize, modify and transfer fluorescence images in real time. We also make the system adaptive to communicate across different client platforms. We conduct experiments comparing our method with traditional collaborative system, and all results confirm our system is over others in terms of efficiency and robustness.

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