Mean (and median) macro F₁-scores of the segmentation methods for the IF and LIVE image data.

<p>Mean (and median) macro F₁-scores of the segmentation methods for the IF and LIVE image data.</p

Comparison of 3D segmentation output with and without the local entropy filter.

<p>(a)-(b) 3D segmentation output using the ‘intOtsu’ method on the original intensity images. (c)-(d) 3D segmentation output using the ‘entOtsu’ method, which includes using the local entropy filter. The blue arrow indicates where a tumour organoid and CAF structure appears to be segmented more accurately by the ‘entOtsu’ method. The magenta arrow indicates where the ‘entOtsu’ method appears to have segmented a different CAF structure less accurately.</p

Pairwise comparisons of the F₁-scores for the IF and LIVE image data.

<p>The dotted lines correspond to equal F₁-score and the p-values correspond to Wilcoxon signed-rank tests that there is no difference between the paired F₁-scores. Note that for the IF image data, the p-values are all equal because the MRF F₁-score is always higher (all points are below the dotted line). For the comparison with the ‘intOstu’ method for the LIVE image data, the MRF F₁-score is also always higher but the p-value is lower here because there are more data points.</p

Example 3D segmentation output.

<p>(a) Maximum intensity projection of a representative 3D stack. (b)-(d) Different viewpoints on the corresponding 3D segmentation output using our MRF based method. The blue arrow indicates where the CAFs appear to be inside the tumour organoid in the maximum intensity projection but can be seen to be outside in the 3D segmentation output. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143798#pone.0143798.s001" target="_blank">S1 Video</a> for a video of the 3D segmentation output.</p

Utility of the local entropy filter.

<p>(a) Maximum intensity projection of an example 3D stack. (b) The corresponding local entropy filtered image. The blue arrow indicates where a weakly fluorescent tumour organoid and CAF structure is more clearly distinguished in the local entropy filtered image.</p

Overview of our 3D segmentation method.

<p>Confocal microscopy is used to image 3D co-culture models resulting in a 3D stack of images. Our 3D segmentation method is applied to the 3D stack of images resulting in 3D segmentation output.</p

Schematic diagram of the construction of the densities for each label.

<p>The three labels are: ‘In focus’ tumour cells with a mixture of ‘out of focus’ CAFs and ‘background’ in the other dimension (red), ‘in focus’ CAFs with a mixture of ‘out of focus’ tumour cells and ‘background’ in the other dimension (green) and a mixture of ‘out of focus’ and ‘background’ in both dimensions (dashed).</p

Maximum intensity projections, manual segmentations and the output for all segmentation methods on the IF image data.

<p>Maximum intensity projections, manual segmentations and the output for all segmentation methods on the IF image data.</p

Conditional independence graph of a 6-neighbour conditional MRF with highlighted edges of the vertex corresponding to <i>X</i>_<i>i</i>.

<p>Conditional independence graph of a 6-neighbour conditional MRF with highlighted edges of the vertex corresponding to <i>X</i>_<i>i</i>.</p

Exemplary screen based on the PC-3 spontaneous invasive transformation model.

<p>PC-3 spheroids were treated with 19 compounds mainly targeting integrity, function and organization of the actin cytoskeleton. 172–424 multicellular structures for each treatment were analysed with AMIDA program. (A) A morphometric heatmap showing standardized differences in medians between the treatments and the control for 15 morphological parameters and all 19 compound treatments. Morphological responses clustered into three functional groups. Increasing cytotoxicity, measured by the AreaRatioR parameter – based on presence of dead cells stained with ethidium homodimer - is indicated by the red gradient arrow. (B) Correlation map (nonparametric Spearman) indicating the similarity (positive correlation, red) or dissimilarity (negative correlation, blue) for 21 of AMIDAs morphometric parameters. (C) Bonferroni-corrected and Mann-Whitney U-test filtered morphometric heatmap (threshold p>0.05) focusing on four selected, most informative parameters (AppIndex, AreaRatioR, Roundness, Area). The graph highlights compounds causing mainly growth-inhibition and cytotoxicity (group II), and those that enhance spheroid symmetry and reduce number of invasive protrusions (group I). (D) The image panel shows representative, segmented PC-3 spheroids for groups I and II, compared to DMSO and paclitaxel controls, after six days of drug treatment.</p