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| applyPeaksFilter | Apply the results of a peaks filter. |
| applyPeaksFilter-method | Apply the results of a peaks filter. |
| applyPeaksFilter-msi.dataset-method | Apply the results of a peaks filter. |
| binKmeans | Return a binary mask generated applying k-means clustering on first 10 principal components of peaks intensities. |
| binKmeans-method | Return a binary mask generated applying k-means clustering on first 10 principal components of peaks intensities. |
| binKmeans2 | Return a binary mask generated applying k-means clustering on peaks intensities. A finer segmentation is obtained by using a larger number of clusters than 2. The off-sample clusters are merged looking at the most frequent labels in the image corners. The lookup areas are defined by the kernel size. |
| binKmeans2-method | Return a binary mask generated applying k-means clustering on peaks intensities. A finer segmentation is obtained by using a larger number of clusters than 2. The off-sample clusters are merged looking at the most frequent labels in the image corners. The lookup areas are defined by the kernel size. |
| binOtsu | Binarize MS image using Otsu's thresholding. |
| binOtsu-method | Binarize MS image using Otsu's thresholding. |
| binSupervised | Return a binary mask generated applying a supervised classifier on peaks intensities using manually selected regions corresponding to off-sample and sample-related areas. |
| binSupervised-method | Return a binary mask generated applying a supervised classifier on peaks intensities using manually selected regions corresponding to off-sample and sample-related areas. |
| bladderMALDIRompp2010 | Load the example MALDI-MSI data. |
| closeImage | Apply morphological closing to binary image. |
| closeImage-method | Apply morphological closing to binary image. |
| countPixelsFilter | Filter based on the minimum number of connected pixels in the ROI. |
| createPeaksFilter | Generate a peak filter object. |
| CSRPeaksFilter | Performs the peak selection based on complete spatial randomness test. |
| getIntensityMat | Return the peaks intensity matrix. |
| getIntensityMat-method | Return the peaks intensity matrix. |
| getMZ | Return the m/z vector. |
| getMZ-method | Return the m/z vector. |
| getShapeMSI | Returns the geometrical shape of MSI dataset |
| getShapeMSI-method | Returns the geometrical shape of MSI dataset |
| gini.index | Gini index. |
| globalPeaksFilter | Reference similarity based peak selection. |
| invertImage | Invert the colors of an MS image. |
| invertImage-method | Invert the colors of an MS image. |
| ms.image-class | ms.image-class definition. |
| msi.dataset-class | msi.dataset-class S4 class definition containing the information about the mass spectrometry imaging dataset. |
| msiDataset | Constructor for msi.dataset-class objects. |
| msImage | Constructor for ms.image-class objects. |
| NMI | Normalized mutual information (NMI). |
| normIntensity | Normalize the peaks intensities. |
| normIntensity-method | Normalize the peaks intensities. |
| numDetectedMSI | Generates an msImage representing the number of detected peaks per pixel. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample. |
| numDetectedMSI-method | Generates an msImage representing the number of detected peaks per pixel. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample. |
| ovarianDESIDoria2016 | Load the example DESI-MSI data. |
| PCAImage | Generates an RGB msImage representing the first 3 principal components. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample. |
| PCAImage-method | Generates an RGB msImage representing the first 3 principal components. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample. |
| plot | Visualize an MS image. 'plot' extends the generic function to ms.image-class objects. |
| plot-method | Visualize an MS image. 'plot' extends the generic function to ms.image-class objects. |
| refImageBinaryKmeans | Calculate the binary reference image using k-means clustering. K-Means is run on the first 'npcs' principal components to speed up the calculations. |
| refImageBinaryKmeansMulti | Calculate the binary reference image using k-means clustering with multi-cluster merging. K-means is run on the first 'npcs' principal components to speed up the calculations. |
| refImageBinaryOtsu | Calculate the binary reference image using Otsu's thresholding. |
| refImageBinarySVM | Calculate the binary reference image using linear SVM trained on manually selected pixels. |
| refImageContinuous | 'refImageContinuous' returns the reference image, calculated using the 'refMethod'. This images represents the basic measure for the filters in SPUTNIK. |
| refImageOtsu | Calculate the binary reference image using k-means clustering. K-Means is run on the first 'npcs' principal components to speed up the calculations. |
| removeSmallObjects | Remove binary ROI objects smaller than user-defined number of pixels |
| removeSmallObjects-method | Remove binary ROI objects smaller than user-defined number of pixels |
| scatter.ratio | Pixel scatteredness ratio. |
| smoothImage | Apply Gaussian smoothing to an MS image. |
| smoothImage-method | Apply Gaussian smoothing to an MS image. |
| spatial.chaos | Spatial chaos measure. |
| splitPeaksFilter | Test for the presence of split peaks. |
| SSIM | Structural similarity index (SSIM). |
| totalIonCountMSI | Generates an msImage representing pixels total-ion-counts. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample. |
| totalIonCountMSI-method | Generates an msImage representing pixels total-ion-counts. This image can be used to qualitatively evaluate the spatial heterogeneity of the sample. |
| varTransform | Variance stabilizing transformation. |
| varTransform-method | Variance stabilizing transformation. |