Comput Methods Programs Biomed - Lung tumor segmentation in PET images using graph cuts.

Tópicos

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Resumo

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill.

Resumo Limpo

aim segment tumor region positron emiss tomographi pet provid accur measur tumor size extens adjac structur possibl visual assess alon henc improv patient manag decis propos segment energi function graph cut techniqu improv lung tumor segment pet segment energi base analysi tumor voxel pet imag combin standard uptak valu suv cost function monoton downhil suv featur monoton downhil featur avoid segment leakag surround tissu similar higher pet tracer uptak tumor suv cost function improv boundari definit also address situat lung tumor heterogen evalu method clinic pet volum patient nonsmal cell lung cancer nsclc method improv segment perform better region grow approach watersh techniqu fuzzycmean regionbas activ contour tumor custom downhil

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