Automated method and system for the segmentation of medical...

Details Automated method and system for the segmentation of medical... Automated method and system for the segmentation of medical...

G - Physics

06

T

G06T 5/40 (2006.01) A61B 6/03 (2006.01) G06T 5/00 (2006.01)

Patent

CA 2177477

A method for the automated segmentation of medical images (figures 5, 11, 12 and 20), including generating image data (figure 19) from radiographic images of the breast (figure 5). The method is applicable to breast mammograms including the extraction of the skinline as well as correction for non-uniform exposure conditions, hand radiographs (figure 11), and chest radiographs (figure 12). Techniques for the segmentation include noise filtering (152 of figure 15), local gray value range determination (153), modified global histogram analysis (154), region growing and determination of object contour (155). The method also is applicable to skin detection and analysis of skin thickening in medical images, where image segmentation (164), local optimization of external skinline (166), creation of a gradient image, identification of the internal skinline (167) and then skin thickness determination are carried out.

Procédé de segmentation automatisée d'images médicales (figures 5, 11, 12 and 20) consistant à générer des données d'image (19) à partir d'images radiographiques de la poitrine (figure). Ce procédé s'applique également aux mammographies de la poitrine comprenant l'extraction de la barrière cutanée ainsi que la correction des conditions d'exposition non uniforme, aux radiographies des mains (figure 11) et du thorax (figure 12). Les techniques de segmentation utilisées intègrent le filtrage du bruit (152, figure 15), la détermination locale de la gamme des valeurs de gris (153), l'analyse de tout l'histogramme modifié (154), la croissance localisée et la détermination des contours de l'objet (155). Ce procédé peut également s'appliquer pour effectuer la détection cutanée et l'analyse de l'épaississement de la peau dans des images médicales, pour lesquelles on effectue une segmentation des images (164), l'optimisation locale de la barrière cutanée externe (166), la création d'une image à gradient, l'identification de la barrière cutanée interne (167) puis la détermination de l'épaisseur de la peau.

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