Interactive Volumetry Of Liver Ablation Zones
| Autor: | Harald Busse, Tuomas Alhonnoro, Michael Moche, Mark Dokter, Dieter Schmalstieg, Xiaojun Chen, Philipp Brandmaier, Bernhard Kainz, Alexander Hann, Michael Hofmann, Steffen Strocka, Mika Pollari, Jan Egger, Matthias Gawlitza, Daniel Seider, Philip Voglreiter |
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| Přispěvatelé: | Department of Neuroscience and Biomedical Engineering, Aalto-yliopisto, Aalto University |
| Rok vydání: | 2015 |
| Předmět: |
FOS: Computer and information sciences
Support Vector Machine Percutaneous Computer science Radiofrequency ablation Computer Vision and Pattern Recognition (cs.CV) medicine.medical_treatment Computer Science - Computer Vision and Pattern Recognition Computer Science - Human-Computer Interaction law.invention Computer Science - Graphics law HEPATOCELLULAR-CARCINOMA Computer vision Contouring IMAGE SEGMENTATION Multidisciplinary Liver Neoplasms Ablation CANCER Multidisciplinary Sciences Treatment Outcome Hepatocellular carcinoma Catheter Ablation Science & Technology - Other Topics SHAPE Tomography Metric (unit) Algorithms Carcinoma Hepatocellular CT-SCANS TUMOR SEGMENTATION FOS: Physical sciences Catheter ablation Article Human-Computer Interaction (cs.HC) medicine Humans RADIOFREQUENCY ABLATION Retrospective Studies Science & Technology business.industry Open surgery Cancer Image segmentation Gold standard (test) Image Enhancement medicine.disease Physics - Medical Physics Graphics (cs.GR) METASTASES Tomography x ray computed Medical Physics (physics.med-ph) Artificial intelligence Tomography X-Ray Computed business |
| Zdroj: | Scientific Reports |
| ISSN: | 2045-2322 |
| DOI: | 10.1038/srep15373 |
| Popis: | Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm's results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow. Comment: 18 pages, 15 figures, 8 tables, 57 references |
| Databáze: | OpenAIRE |
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