12 March 2010 Partial volume correction for volume estimation of liver metastases and lymph nodes in CT scans using spatial subdivision
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Abstract
In oncological therapy monitoring, the estimation of tumor growth from consecutive CT scans is an important aspect in deciding whether the given treatment is adequate for the patient. This can be done by measuring and comparing the volume of a lesion in the scans based on a segmentation. However, simply counting the voxels within the segmentation mask can lead to significant differences in the volume, if the lesion has been segmented slightly differently by various readers or in different scans, due to the limited spatial resolution of CT and due to partial volume effects. We present a novel algorithm for measuring the volume of liver metastases and lymph nodes which considers partial volume effects at the surface of a lesion. Our algorithm is based on a spatial subdivision of the segmentation. We have evaluated the algorithm on a phantom and a multi-reader study. Our evaluations have shown that our algorithm allows determining the volume more accurately even for larger slice thicknesses. Moreover, it reduces inter-observer variability of volume measurements significantly. The calculation of the volume takes 2 seconds for 503 voxels on a single 2.66GHz Intel Core2 CPU.
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Frank Heckel, Frank Heckel, Volker Dicken, Volker Dicken, Tilman Bostel, Tilman Bostel, Michael Fabel, Michael Fabel, Andreas Kiessling, Andreas Kiessling, Heinz-Otto Peitgen, Heinz-Otto Peitgen, } "Partial volume correction for volume estimation of liver metastases and lymph nodes in CT scans using spatial subdivision", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76230T (12 March 2010); doi: 10.1117/12.844200; https://doi.org/10.1117/12.844200
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