Abstract
Language | English |
---|---|
Pages | 173-183 |
Number of pages | 11 |
Journal | Image Analysis and Stereology |
Volume | 38 |
Issue number | 2 |
DOIs | |
Publication status | Published - 31 Jul 2019 |
Fingerprint
Keywords
- continuous max-flow
- graph segmentation
- kernel induced space
- MRI image
- nephroblastoma
- Wilms tumour
Cite this
}
Nephroblastoma analysis in MRI images. / Kaba, Djibril; McFarlane, Nigel; Dong, Feng; Graf, Norbert; Ye, Xujiong.
Vol. 38, No. 2, 31.07.2019, p. 173-183.Research output: Contribution to journal › Article
TY - JOUR
T1 - Nephroblastoma analysis in MRI images
AU - Kaba, Djibril
AU - McFarlane, Nigel
AU - Dong, Feng
AU - Graf, Norbert
AU - Ye, Xujiong
PY - 2019/7/31
Y1 - 2019/7/31
N2 - The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of nephroblastoma in MRI scans. The segmentation is performed by adapting and a 2D free hand drawing tool to select a region of interest in the scan slices. Results from 24 patients show a mean root-mean-square error of 0.0481±0.0309, an average Dice coefficient of 0.9060±0.0549 and an average accuracy of 99.59% ±0.0039. Thus the proposed method demonstrated an effective agreement with manual annotations.
AB - The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of nephroblastoma in MRI scans. The segmentation is performed by adapting and a 2D free hand drawing tool to select a region of interest in the scan slices. Results from 24 patients show a mean root-mean-square error of 0.0481±0.0309, an average Dice coefficient of 0.9060±0.0549 and an average accuracy of 99.59% ±0.0039. Thus the proposed method demonstrated an effective agreement with manual annotations.
KW - continuous max-flow
KW - graph segmentation
KW - kernel induced space
KW - MRI image
KW - nephroblastoma
KW - Wilms tumour
U2 - 10.5566/ias.2000
DO - 10.5566/ias.2000
M3 - Article
VL - 38
SP - 173
EP - 183
IS - 2
ER -