Skin Anatomy and Physiology

DOI: 10.1007/978-1-84882-513-0_13 In book: Plastic and Reconstructive Surgery, pp.161-171


If plastic surgeons are to provide state-of-the-art care in the techniques of skin rejuvenation and minimally invasive treatments
for aging, a thorough understanding of skin, anatomy, and physiology is required. With the changing population demographics,
the plastic surgeon must also be knowledgeable about ethnic variations in skin anatomy and physiology. The changes that occur
with aging skin, inherent developmental disorders, and development of skin cancers are complex. This chapter provides a practical
guide to the understanding of skin and its application to clinical conditions.

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    • "Since the poor quality segmentation like in Fig. 2(f) includes a large number of false positive regions, the segmented epidermis mask has an abnormally large thickness. The epidermis varies in thickness in different regions of body but should be within a limited range [9]. The epidermis of skin images used in this work has a thickness of roughly ranged between 0.05mm and 0.4mm. "
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    ABSTRACT: Segmentation of epidermis areas is an important step towards automatic analysis of skin histopathological images. This paper presents a robust technique for epidermis segmentation in whole slide skin histopathological images. The proposed technique first performs a coarse epidermis segmentation using global thresholding and shape analysis. The epidermis thickness is then estimated by a series of line segments perpendicular to the main axis of the initially segmented epidermis mask. If the segmented epidermis mask has a thickness greater than a predefined threshold, the segmentation is suspected to be inaccurate. A second pass of fine segmentation using k-means algorithm is then carried out over these coarsely segmented result to enhance the performance. Experimental results on 64 different skin histopathological images show that the proposed technique provides a superior performance compared to the existing techniques.
    EMBC2015; 08/2015
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    ABSTRACT: Using continuous wave, 94-GHz millimeter-wave interferometry, a signal representing chest wall motion can be obtained that contains both the heart rate and respiration patterns of a human subject. These components have to be separated from each other in the received signal. Our method was to use the quadrature and in-phase components of the signal, after removing the mean of each, to find the phase, unwrap it, and convert it to a displacement measurement. Using this, the power spectrum was examined for peaks, which corresponded to the heart rate and respiration rate. The displacement waveform of the chest was also analyzed for discrete heartbeats using a novel wavelet decomposition technique.
    IEEE transactions on bio-medical engineering 02/2011; 58(6):1671-7. DOI:10.1109/TBME.2011.2111371 · 2.35 Impact Factor