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Table 1.

Summary of studies addressing the segmentation of magnetic resonance imaging and computed tomography images.

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Table 1 Expand

Fig 1.

Brain mapping: (a) specific brain regions and (b) different brain structures.

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Fig 2.

Brain exams: (a) computed tomography e (b) magnetic resonance.

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Fig 3.

Flowchart of the proposed methodology.

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Fig 4.

Flowchart of the proposed architecture.

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Table 2.

and σ along the twelve simulations for each NR and for each class c1, c2 and c4.

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Table 3.

Hyperparameters optimized based on the predefined quantity of labels.

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Table 3 Expand

Fig 5.

Windowing filter 40 × 80 [HU].

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Fig 5 Expand

Fig 6.

Segmentation of exams: (a) to (f) CT042 and (g) to (l) CT195.

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Fig 6 Expand

Fig 7.

Segmentation of exams: (a) to (f) CT200, (g) to (l) CT299, and (m) to (r) CT418.

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Table 4.

Comparison of Dc between the proposed method versus Kim, Kanezaki, and Tanaka’s method [38].

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Table 4 Expand

Fig 8.

Segmentation overlap of the CT195 exam: (a) c1, (b) c2, (c) c3, (d) c4, (e) c5 e (f) c6.

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Fig 8 Expand

Table 5.

Comparison of cranial volumetry values between the proposed method versus CTSeg.

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Fig 9.

Cranial volumetry for class c4 in the CT042 exam.

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Fig 10.

Segmentation using the proposed method in exams: (a) CT042 NR = 7, (b) CT042 NR = 8, (c) CT195 NR = 7, (d) CT195 NR = 8, (e) CT200 NR = 7, (f) CT200 NR = 8, (g) CT299 NR = 7, (h) CT299 NR = 8, (i) CT418 NR = 7, and (j) CT418 NR = 8.

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