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Table 4 Evaluation results for prostate cancer detection: Feature selection based on specificity (results are shown with 95 % confidence interval)

From: Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

Imaging

Number of

Sensitivity

Specificity

Accuracy

AUC

modality

features

    

T2w

10

0.66 [0.50 0.81]

0.47 [0.42 0.53]

0.48 [0.43 0.53]

0.57 [0.48 0.66]

CHB-DWI

10

0.69 [0.52 0.86]

0.82 [0.75 0.88]

0.81 [0.75 0.87]

0.76 [0.68 0.84]

ADC

96

0.73 [0.60 0.85]

0.62 [0.55 0.70]

0.63 [0.56 0.71]

0.70. [0.64 0.76]

CDI

10

0.82 [0.69 0.94]

0.85 [0.80 0.89]

0.84 [0.80 0.88]

0.84 [0.78 0.89]

TFM 1= T2w+ADC

110

0.72 [0.59 0.86]

0.63 [0.55 0.70]

0.64 [0.56 0.71]

0.69 [0.63 0.75]

TFM 2=T2w+ADC

40

0.66 [0.50 0.82]

0.77 [0.71 0.83]

0.77 [0.71 0.82]

0.73 [0.65 0.81]

+CHB-DWI

     

TFM 3=T2w+CDI

20

0.78 [0.65 0.91]

0.86 [0.82 0.90]

0.86 [0.82 0.89]

0.84 [0.78 0.90]

TFM 4=T2w+ADC+CDI

40

0.77 [0.63 0.90]

0.86 [0.82 0.90]

0.85 [0.81 0.89]

0.84 [0.79 0.89]

TFM 5=T2w+ADC

50

0.78 [0.64 0.91]

0.86 [0.82 0.90]

0.85 [0.82 0.89]

0.84 [0.78 0.90]

+CHB-DWI+CDI

     

TFM 6=T2w+ADC

130

0.80 [0.69 0.91]

0.88 [0.85 0.92]

0.88 [0.84 0.91]

0.88 [0.83 0.93]

+CHB-DWI+CDI

     

+ b1 + b2 + b3 + b4