BioMed Research International / 2018 / Article / Tab 3

Research Article

Tumor Segmentation in Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma: Deep Learning with Convolutional Neural Network

Table 3

Comparison of segmentation performance among our convolutional neural network model and other models. N.A.: not available.

Dice similarity coefficientCorresponding ratioPercent match
StudyAlgorithmMean ± SDRangeMean ± SDRangeMean ± SDRange

Current studyConvolutional neural network0.89±0.050.80-0.950.84±0.060.71-0.920.90±0.040.83-0.96
Zhou at al. [7]Support vector machineN.AN.A0.72±0.060.58~0.850.79±0.070.65-0.91
Huang et al. [14]Hidden Markov random fieldN.AN.A0.720.44-0.910.850.64-1.00
Wang et al. [15]Deep Convolutional Neural NetworksN.A-0.80N.AN.AN.A-0.90

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