Please use this identifier to cite or link to this item:
Title: Liver tumour segmentation using contrast-enhanced multi-detector CT data: Performance benchmarking of three semiautomated methods
Authors: Zhou, J.-Y.
Wong, D.W.K.
Ding, F.
Venkatesh, S.K.
Tian, Q.
Qi, Y.-Y.
Xiong, W.
Liu, J.J.
Leow, W.-K. 
Keywords: Computed tomography (CT)
Image segmentation
Liver tumour
Performance benchmarking
Tumour volumetry
Issue Date: 2010
Citation: Zhou, J.-Y., Wong, D.W.K., Ding, F., Venkatesh, S.K., Tian, Q., Qi, Y.-Y., Xiong, W., Liu, J.J., Leow, W.-K. (2010). Liver tumour segmentation using contrast-enhanced multi-detector CT data: Performance benchmarking of three semiautomated methods. European Radiology 20 (7) : 1738-1748. ScholarBank@NUS Repository.
Abstract: Objective: Automatic tumour segmentation and volumetry is useful in cancer staging and treatment outcome assessment. This paper presents a performance benchmarking study on liver tumour segmentation for three semiautomatic algorithms: 2D region growing with knowledge-based constraints (A1), 2D voxel classification with propagational learning (A2) and Bayesian rule-based 3D region growing (A3). Methods: CT data from 30 patients were studied, and 47 liver tumours were isolated and manually segmented by experts to obtain the reference standard. Four datasets with ten tumours were used for algorithm training and the remaining 37 tumours for testing. Three evaluation metrics, relative absolute volume difference (RAVD), volumetric overlap error (VOE) and average symmetric surface distance (ASSD), were computed based on computerised and reference segmentations. Results: A1, A2 and A3 obtained mean/median RAVD scores of 17.93/10.53%, 17.92/9.61% and 34.74/28.75%, mean/median VOEs of 30.47/26.79%, 25.70/22.64% and 39.95/38.54%, and mean/median ASSDs of 2.05/1.41 mm, 1.57/1.15 mm and 4.12/3.41 mm, respectively. For each metric, we obtained significantly lower values of A1 and A2 than A3 (P<0.01), suggesting that A1 and A2 outperformed A3. Conclusions: Compared with the reference standard, the overall performance of A1 and A2 is promising. Further development and validation is necessary before reliable tumour segmentation and volumetry can be widely used clinically. © European Society of Radiology 2009.
Source Title: European Radiology
ISSN: 09387994
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Mar 8, 2018


checked on Dec 26, 2018

Page view(s)

checked on Sep 22, 2020

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.