Publications by authors named "Mugui Xie"

Background: Static nailfold capillary parameters are important parameters that reflect the health of the human body. Disease onset or progression is often accompanied by changes in the physiological parameters of the nailfold. Hence, the physiological parameters of the nailfold are closely related to the study of disease, with their automated and high-precision measurements playing a crucial role in these studies.

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Nail fold capillaroscopy is an important means of monitoring human health. Panoramic nail fold images improve the efficiency and accuracy of examinations. However, the acquisition of panoramic nail fold images is seldom studied and the problem manifests of few matching feature points when image stitching is used for such images.

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Changes in the structure and function of nailfold capillaries may be indicators of numerous diseases. Noninvasive diagnostic tools are commonly used for the extraction of morphological information from segmented nailfold capillaries to study physiological and pathological changes therein. However, current segmentation methods for nailfold capillaries cannot accurately separate capillaries from the background, resulting in issues such as unclear segmentation boundaries.

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Nailfold capillary density is an essential physiological parameter for analyzing nailfold health; however, clinical images of the nailfold are taken in many situations, and most clinicians subjectively analyze nailfold images. Therefore, based on the improved "you only look once v5" (YOLOv5) algorithm, this study proposes an automated method for measuring nailfold capillary density. The improved technique can effectively and rapidly detect distal capillaries by incorporating methods or structures such as 9mosaic, spatial pyramid pooling cross-stage partial construction, bilinear interpolation, and efficient intersection over union.

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