Open AccessNEPHROBLASTOMA ANALYSIS IN MRI IMAGES
Author(s) -
Djibril Kaba,
N.J.B. McFarlane,
Feng Dong,
Norbert Graf,
Xujiong Ye
Publication year - 2019
Publication title -
image analysis and stereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 27
eISSN - 1854-5165
pISSN - 1580-3139
DOI - 10.5566/ias.2000
Subject(s) - sørensen–dice coefficient , segmentation , computer science , artificial intelligence , dice , mean squared error , pattern recognition (psychology) , computer vision , image segmentation , mathematics , statistics
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.