0000000000433723
AUTHOR
Heinz-otto Peitgen
Segmentierung von Hepatozellulären Karzinomen mit Fuzzy-Connectedness
Die Segmentierung von hepatozellularen Karzinomen nach Chemoembolisation stellt eine grose Herausforderung an die Bildverarbeitung dar. CT-Aufnahmen sechs Wochen nach dieser Therapie sind die Grundlage fur die angestrebte Volumetrie der Raumforderungen. In diesen Bildern stellen sich die mit Lipiodol und Mitomycin behandelten Tumore als inhomogene, kraftig kontrastierte Herde dar, wahrend gleichzeitig neue Metastasen mit nur geringer Kontrastierung entstanden sein konnen. Ein neuer, auf Basis der Fuzzy-Connectedness beruhender Algorithmus zeigt in einer ersten Studie durch seine Fahigkeit, Grauwertinformationen mit Kriterien zu lokalen Zusammenhangen zu kombinieren, gute Ergebnisse. Verglei…
Partial volume correction for volume estimation of liver metastases and lymph nodes in CT scans using spatial subdivision
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 volum…
3D contour based local manual correction of tumor segmentations in CT scans
Segmentation is an essential task in medical image analysis. For example measuring tumor growth in consecutive CT scans based on the volume of the tumor requires a good segmentation. Since manual segmentation takes too much time in clinical routine automatic segmentation algorithms are typically used. However there are always cases where an automatic segmentation fails to provide an acceptable segmentation for example due to low contrast, noise or structures of the same density lying close to the lesion. These erroneous segmentation masks need to be manually corrected. We present a novel method for fast three-dimensional local manual correction of segmentation masks. The user needs to draw …