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. 2020 Sep 23;2(5):e190146. doi: 10.1148/ryai.2020190146

Figure 4:

Naive expert-trained deep gray Bayesian network overview. Key image signal, spatial pattern, and anatomic subregion features are probabilistically combined with four clinical features to calculate a probability of each diagnostic state. ADC = apparent diffusion coefficient, Dec = decreased, Enhance = enhancement, FLAIR = fluid-attenuated inversion recovery, GRE = gradient-recalled echo, Inc = increased, Restrict = restricted diffusion, Suscept = susceptibility, T1 = T1-weighted, T1-post = T1-weighted postcontrast.

Naive expert-trained deep gray Bayesian network overview. Key image signal, spatial pattern, and anatomic subregion features are probabilistically combined with four clinical features to calculate a probability of each diagnostic state. ADC = apparent diffusion coefficient, Dec = decreased, Enhance = enhancement, FLAIR = fluid-attenuated inversion recovery, GRE = gradient-recalled echo, Inc = increased, Restrict = restricted diffusion, Suscept = susceptibility, T1 = T1-weighted, T1-post = T1-weighted postcontrast.