Differentiating Small (≤1 cm) Focal Liver Lesions as Metastases or Cysts by means of Computed Tomography: A Case-Study to Illustrate a Fuzzy Logic-Based Method to Assess the Impact of Diagnostic Confidence on Radiological Diagnosis

Table 3

Set of P(d) and N(d) values attributed to 50 focal liver lesions by reader R1 and reader R2, respectively, with the calculations necessary to evaluate fTPs, fFNs, fFPs, and fTNs based on final diagnosis. Numbers in the brackets represent a fuzzy DC value multiplied (𝑥) by the number of lesions to which it was attributed.

(a) R1 reader

Number of lesions	P(d)	N(d)
	Metastases
25	1	0.0
2	0.8	0.2
2	0.2	0.8
1	0.0	1.0
	Cysts
19	0.0	1.0
1	0.2	0.8

fTPs=(25×1.0)+(2×0.8)+(2×0.2)+(1×0.0)=27  
fFPs=(19×0.0)+(1×0.2)=0.2 
fFNs=(25×0.0)+(2×0.2)+(2×0.8)+(1×1.0)=3 
fTNs=(19×1.0)+(1×0.8)=19.8 

(b) R2 reader

Number of lesions	P(d)	N(d)
	Metastases
28	1	0.0
1	0.2	0.8
1	0.0	1.0
	Cysts
12	0.0	1.0
2	0.1	0.9
3	0.2	0.8
2	0.3	0.7
1	1.0	0.0

fTPs=(28×1.0)+(1×0.2)+(1×0.0)=28.2 
fFPs=(12×0.0)+(2×0.1)+(3×0.2)+(2×0.3)+(1×1.0)=2.4 
fFNs=(28×0.0)+(1×0.8)+(1×1.0)=1.8 
fTNs=(12×1.0)+(2×0.9)+(3×0.8)+(2×0.7)+(1×0.0)=17.6 
fTPs: fuzzy true positives; fFNs: fuzzy false negatives; fFPs: fuzzy false positives; fTNs: fuzzy true negatives.