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A hand-held mosaicked multispectral imaging device for early stage pressure ulcer detection.

机译:一种用于早期压疮检测的手持式镶嵌多光谱成像设备。

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The use of a custom filter mosaic overlaying a CMOS/CCD sensor represents a novel idea to multispectral imaging. The innovation provides simple, miniaturized, low cost instrumentation that has many potential biological applications which require a hand-held detector. This makes it extremely adaptable and can serve as an integrated component to distributed diagnosis and home healthcare (D2H2). A mosaicked sensor is a monolithic array of many sensors, arranged in a geometric pattern with each sensor covered by an optical filter sensitive to a specified wavelength. In this way, only one spectral component is sensed at each pixel and the other spectral components must be estimated from neighbors. Although with great potential, one challenge faced by this device, however, is the reconstruction of the high-resolution full-spectral image from the low-resolution input. Due to the physical limitations in fabrication and the usage of the multispectral filter mosaic, two types of degradations exist, including filter misalignment and the missing spectral components, that must be corrected using intelligent algorithms to take full advantage of the hardware capability of the device. In this paper, we first describe a custom geometric correction method to restore the image from the misalignment distortion. We then present a binary tree-based generic demosaicking algorithm to efficiently estimate the missing special components and reconstruct a high-resolution full-spectral image. We choose early detection of pressure ulcer as a targeting area as early stage pressure ulcers and other subcutaneous lesions are nearly invisible in clinical settings, particularly so for dark pigmented skin. We show how the geometric correction and demosaicking algorithms successfully reconstruct a full-spectral image from which apparent contrast enhancement between damaged skin and the normal skin is observed.
机译:自定义滤镜马赛克覆盖CMOS / CCD传感器的使用代表了多光谱成像的新想法。本发明提供了一种简单,小型化,低成本的仪器,该仪器具有许多潜在的生物学应用,需要手持探测器。这使其具有极强的适应性,可以用作分布式诊断和家庭医疗保健(D2H2)的集成组件。镶嵌传感器是许多传感器的整体阵列,以几何图案排列,每个传感器均由对特定波长敏感的光学滤光片覆盖。以这种方式,在每个像素处仅感测一个光谱分量,并且必须从邻居估计其他光谱分量。尽管具有很大的潜力,但是该设备面临的一个挑战是从低分辨率输入中重建高分辨率全光谱图像。由于制造和使用多光谱滤镜镶嵌的物理限制,存在两种类型的降级,包括滤镜失准和丢失的光谱成分,必须使用智能算法对其进行校正,以充分利用设备的硬件功能。在本文中,我们首先描述一种自定义几何校正方法,以从未对准失真中恢复图像。然后,我们提出了一种基于二叉树的通用去马赛克算法,以有效地估计缺失的特殊成分并重建高分​​辨率的全光谱图像。我们选择早期发现压疮作为目标区域,因为在临床环境中早期压疮和其他皮下病变几乎看不见,尤其是深色皮肤。我们展示了几何校正和去马赛克算法如何成功重建全光谱图像,从中可以观察到受损皮肤和正常皮肤之间明显的对比度增强。

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