The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists

Table 2 The best settings for training/validation split ratio and epoch in Experiment 1 and 2

Test image set	Training image set	Training/validation split ratio	Epoch
Experiment 1
Axial ADC map	Axial ADC map	9:1	100
Axial T2WI	Axial T2WI	9:1	50
Sagittal T2WI	Sagittal T2WI	8:2	50
Axial CE-T1WI	Axial CE-T1WI	8:2	200
Sagittal CE-T1WI	Sagittal CE-T1WI	8:2	100
Combined axial T2WI + ADC map	Combined axial T2WI + ADC map	9:1	100
Combined axial T2WI + CE-T1WI	Combined axial T2WI + CE-T1WI	9:1	100
Combined sagittal T2WI + CE-T1WI	Combined sagittal T2WI + CE-T1WI	9:1	50
Combined axial T2WI + ADC map + CE-T1WI	Combined axial T2WI + ADC map + CE-T1WI	9:1	200
Experiment 2
Axial ADC map	All axial	8:2	50
Axial ADC map	All	9:1	50
Axial T2WI	All T2WI	8:2	100
Axial T2WI	All axial	9:1	50
Axial T2WI	All	9:1	50
Sagittal T2WI	All T2WI	8:2	200
Sagittal T2WI	All sagittal	8:2	200
Sagittal T2WI	All	8:2	100
Axial CE-T1WI	All CE-T1WI	8:2	50
Axial CE-T1WI	All axial	8:2	100
Axial CE-T1WI	All	8:2	100
Sagittal CE-T1WI	All CE-T1WI	9:1	100
Sagittal CE-T1WI	All sagittal	9:1	50
Sagittal CE-T1WI	All	9:1	100

ADC, Apparent diffusion coefficient; T2WI, T2 weighted image; CE-T1WI, contrast-enhanced T1 weighted image

ISSN: 1471-2342