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Fig 1.

Network representation of the whole data-set before clustering superimposed to the mean registered image.

The nodes are located in the center of gravity of the tumors and bigger nodes have bigger network centrality (i.e. they are strongly connected to many other nodes). The edges colors and strength represent the distance between nodes (from red and thick (short distance) to blue and thin). For visibility reasons, arcs corresponding to a distance greater than 35 are not displayed.

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Fig 1 Expand

Fig 2.

Examples of cluster probability maps describing the spatial repartition of tumors in the cluster.

The maps are superimposed to the mean registered image.

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Fig 2 Expand

Fig 3.

Cluster validity indices with respect to the value of α (a, b, c, d) and the number of clusters (e).

Dunn index (a), Davies Bouldin index (b), Silhouette index (c) and combined indices (d, e).

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Fig 3 Expand

Fig 4.

Visualization of the complete clustered graph superimposed to the mean registered image.

The numbers correspond to the number of nodes in each cluster.

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Fig 4 Expand

Table 1.

Anatomical location of the different clusters.

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Table 1 Expand

Fig 5.

Positions of the cluster centers on the MNI atlas.

The clusters are organized in numerical order (from cluster 1 to 11).

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Fig 5 Expand

Fig 6.

Examples of graph matching results.

(a) Complete match, (b, c) Partial match. Positive matches correspond to blue edges and mismatched samples to red edges. The nodes’ locations correspond to the coordinates of the cluster centres of each clustering. The green nodes have been translated along the x axis for visualisation purposes.

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Fig 6 Expand

Table 2.

Mean and median (in parentheses) values of the different scores and methods for tumor segmentation.

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Table 2 Expand

Fig 7.

Boxplots of the Dice score (a), True Positive rate (b), False positive rate (c), and MAD score (d) between the automatic and manual tumor segmentation for the three different methods.

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Fig 7 Expand

Fig 8.

Visual Segmentation results.

(a) boosting score, (b) Boosting classification (thresholding), (c) Pairwise MRF, (d) MRF with spatial prior.

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Fig 8 Expand

Table 3.

Mean and median ages at the time of the first symptoms for each cluster.

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Table 3 Expand

Table 4.

Mean and median ages at the time of MRI diagnosis for each cluster.

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Table 4 Expand

Fig 9.

Patient’s age at the time of the first symptoms (a) and MRI diagnosis (b) for each cluster.

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Fig 9 Expand