SUMMARY Leishmania is an infectious protozoan parasite related to African and American trypanosomes. All Leishmania species that are pathogenic to humans can cause dermal disease. When one is confronted with cutaneous leishmaniasis, identification of the causative species is relevant in both clinical and epidemiological studies, case management, and control. This review gives an overview of the currently existing and most used assays for species discrimination, with a critical appraisal of the limitations of each technique. The consensus taxonomy for the genus is outlined, including debatable species designations. Finally, a numerical literature analysis is presented that describes which methods are most used in various countries and regions in the world, and for which purposes.

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Abstract-Perfect reconstruction, quality scalability, and region-of-interest coding are basic features needed for the image compression schemes used in telemedicine applications. This paper proposes a new wavelet-based embedded compression technique that efficiently exploits the intraband dependencies and uses a quadtree-based approach to encode the significance maps. The algorithm produces a losslessly compressed embedded data stream, supports quality scalability, and permits regionof-interest coding. Moreover, experimental results obtained on various images show that the proposed algorithm provides competitive lossless/lossy compression results. The proposed technique is well suited for telemedicine applications that require fast interactive handling of large image sets, over networks with limited and/or variable bandwidth.

Lossless image compression with progressive transmission capabilities plays a key role in measurement applications, requiring quantitative analysis and involving large sets of images. This work proposes a wavelet-based compression scheme that is able to operate in the lossless mode. The quantization module implements a new technique for the coding of the wavelet coefficients that is more effective than the classical zerotree coding. The experimental results obtained on a set of multimodal medical images show that the proposed algorithm outperforms the embedded zerotree coder combined with the integer wavelet transform by 0.28 bpp, the set-partitioning coder by 0.1 bpp, and the lossless JPEG coder by 0.6 bpp. The scheme produces a losslessly compressed embedded data stream; hence, it supports progressive refinement of the decompressed images. Therefore, it is a good candidate for telematics applications requiring fast user interaction with the image data, retaining the option of lossless transmission and archiving of the images.

Abstract-While the hierarchical B frames based Scalable Video Coding (SVC) extension of the H.264/AVC standard achieves significantly improved compression over the initial H.264/AVC codec, the SVC video traffic is significantly more variable than H.264/AVC traffic. The higher traffic variability of the SVC encoder can lead to smaller numbers of streams supported with bufferless statistical multiplexing than with the H.264/AVC encoder (and even less streams than with the MPEG-4 Part 2 encoder) for prescribed link capacities and loss constraints. In this paper we examine the implications of video traffic smoothing on the numbers of statistically multiplexed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams, the bandwidth requirements for streaming, and the introduced delay. We identify the levels of smoothing that ensure that more H.264 SVC streams than H.264/AVC streams can be supported. For a basic low-complexity smoothing technique that is readily applicable to both live and prerecorded streams, we identify the levels of smoothing that give (bufferless) statistical multiplexing performance close to an optimal off-line smoothing technique. We thus characterize the trade-offs between increased smoothing delay and increased statistical multiplexing performance for both H.264/AVC, which employs classical B frames, and H.264 SVC, which employs hierarchical B frames. We similarly identify the buffer sizes for the buffered multiplexing of unsmoothed H.264 SVC, H.264/AVC, and MPEG-4 Part 2 streams that give close to optimal performance.

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