Fig 1.
MIP of every patient included in the study ordered by tumor type: a) lung cancer, b) lymphoma, c) melanoma, d) sarcoma.
Fig 2.
Illustrates the workflow for the interactive threshold approach.
Initially, CT and PET image are presented to the user including a mask marking roughly the tumor. The user changes then interactively the threshold until the segmentation is considered as satisfactory.
Fig 3.
Illustrates the workflow of the interactive gradient based segmentation.
Gradient and PET image are presented to the user. Also here, the user changes interactively the threshold until the segmentation is satisfactory on both PET and gradient image.
Fig 4.
Displays an example for the Select-the-best method.
The user chooses the best result out of four segmentations that were acquired automatically.
Fig 5.
Illustrates the variability of the JC values (left) and percentage MATV differences (right) for all images. The amount of user-interaction increases from left to right (for both plots: left: Select-the-best (S), middle-left: Gradient (G); middle-right: Threshold-based (T), right: Manual (M)).
Table 1.
P-values obtained with the Kruskal-Wallis test.
Non-significant results are marked with ‘n.s.‘.
Fig 6.
Illustrates the variability of PPV/SE values for the approaches with increasing user-interaction from left to right.
Fig 7.
Percentage MATV differences and PPV/SE values between segmentations performed by observers and MV segmentation displayed for every observer separately.
The observers are ordered by their level of experience with observer 1 being the most experienced. Observer 4a and 4b are having the same experience level.
Fig 8.
Demonstrates the feature value variability for the approaches (increasing user-interaction from left to right).