3 July 1998 Assessing the differences of reactive hyperemic flow due to the contribution of forearm composition using automated tissue segmentation from MR scans and venous occlusion strain gauge plethysmograph
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Abstract
A novel, fully automatic, multi-step segmentation method has been developed to distinguish different tissues in human limbs. As input data conventional transverse T1-weighted MR scans were used providing a good contrast between tissues of interest and background. Hence, a scalar (monospectral) histogram approach employing statistical distribution models of gray values has been chosen. The identification of the tissues becomes possible by alternating different levels of histogram-based thresholding techniques and sequences of morphologic operations in conjunction with a-priori anatomic knowledge. By using morphologic operations and generic definitions of the anatomic structures found in the limbs, specific parts of the histogram can be identified which otherwise impede the automatic histogram interpretation. To correct partial volume effects, which may corrupt the different modes of the histogram, gradient thresholding was established. The proposed method was validated on both phantoms and ten healthy volunteers. Using this method, a study was performed to investigate whether there is a contribution in reactive hyperemic flow induced by differences in forearm composition.
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Roland Bammer, Thomas Wascher, Markus Pedevilla, Paul Wach, Franz Ebner, Rudolf Stollberger, "Assessing the differences of reactive hyperemic flow due to the contribution of forearm composition using automated tissue segmentation from MR scans and venous occlusion strain gauge plethysmograph", Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); doi: 10.1117/12.312556; https://doi.org/10.1117/12.312556
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