On simulating subjective evaluation using combined objective metrics for validation of 3D tumor segmentation.
In this paper, we present a new segmentation evaluation method that can simulate radiologist's subjective assessment of 3D tumor segmentation in CT images. The method uses a new metric defined as a linear combination of a set of commonly used objective metrics. The weighing parameters of the linear combination are determined by maximizing the rank correlation between radiologist's subjective rating and objective measurements. Experimental results on 93 lesions demonstrate that the new composite metric shows better performance in segmentation evaluation than each individual objective metric. Also, segmentation rating using the composite metric compares well with radiologist's subjective evaluation. Our method has the potential to facilitate the development of new tumor segmentation algorithms and assist large scale segmentation evaluation studies.
Deng
Xiang
X
Corporate Technology, Siemens Ltd., China. xiang.deng@siemens.com
Zhu
Lei
L
Sun
Yiyong
Y
Xu
Chenyang
C
Song
Lan
L
Chen
Jiuhong
J
Merges
Reto D
RD
Jolly
Marie-Pierre
MP
Suehling
Michael
M
Xu
Xiaodong
X
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D009369:Neoplasms / Q000000981:diagnostic imaging*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*