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distributed?": [[283, "is-the-data-normally-distributed"]], "Jaccard index": [[227, "jaccard-index"]], "Jaccard-Index versus Accuracy": [[226, null]], "K-means clustering": [[300, "k-means-clustering"], [301, "k-means-clustering"]], "Keep it short and simple": [[25, null]], "Keep it simple": [[112, "keep-it-simple"]], "Keeping parameters unset": [[21, "keeping-parameters-unset"]], "Kernel": [[0, "kernel"]], "Kernels, footsprints and structural elements": [[163, "kernels-footsprints-and-structural-elements"]], "Knowledge": [[30, "knowledge"]], "Kontakt": [[318, "kontakt"]], "Label image": [[0, "label-image"]], "Label image refinement": [[164, null]], "Label images": [[125, null]], "Label intensity statistics": [[192, "label-intensity-statistics"]], "Label neighbor filters": [[207, null]], "Label touch count and touch portion": [[213, null]], "Labeled surface voxels": [[182, "labeled-surface-voxels"]], "Labeling": [[0, "labeling"]], "Labeling in practice": [[125, "labeling-in-practice"]], "Labeling pixels on label borders": [[192, "labeling-pixels-on-label-borders"]], "Laplace operator": [[95, "laplace-operator"]], "Laplacian": [[97, "laplacian"]], "Laplacian of Gaussian": [[95, "laplacian-of-gaussian"], [97, "laplacian-of-gaussian"]], "Laplacian-of-Gaussian (LoG)": [[200, "laplacian-of-gaussian-log"]], "Large Language Vision Models": [[150, null]], "Large language model fine tuning": [[49, null]], "Layer properties": [[88, "layer-properties"]], "Libraries to extract features of all timepoints": [[256, "libraries-to-extract-features-of-all-timepoints"]], "License": [[319, "license"]], "Linear interpolation": [[108, "linear-interpolation"]], "Linear interpolation versus nearest neighbor interpolation": [[108, "linear-interpolation-versus-nearest-neighbor-interpolation"]], "List": [[0, "list"]], "Lists and tuples": [[7, null]], "Load a data set": [[240, "load-a-data-set"]], "Load an image and measure shape of objects in 3D": [[264, null]], "Load 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deviation": [[95, "local-standard-deviation"], [95, "id1"]], "Login": [[19, "login"], [74, "login"]], "Logout": [[19, "logout"], [74, "logout"]], "Lookup tables (a.k.a. color maps)": [[53, "lookup-tables-a-k-a-color-maps"]], "Loops": [[12, null]], "Machine learning": [[0, "machine-learning"]], "Machine learning basics": [[76, null]], "Machine learning for image segmentation": [[144, null]], "Manual annotation": [[180, "manual-annotation"]], "Manual clustering": [[302, "manual-clustering"]], "Manual clustering using thresholds": [[300, "manual-clustering-using-thresholds"]], "Map area of objects in tiles": [[244, null]], "Markdown documentation in Jupyter notebooks": [[3, "markdown-documentation-in-jupyter-notebooks"]], "Material origin": [[319, "material-origin"]], "Math": [[30, "math"]], "Matrix": [[0, "matrix"]], "Mean / minimum / maximum / standard-deviation intensity map": [[311, "mean-minimum-maximum-standard-deviation-intensity-map"]], "Measure distance along a center line": [[188, null]], "Measure distance to a center line": [[190, null]], "Measure overlap between two label images": [[224, null]], "Measure the distance to cells in another label image": [[206, null]], "Measure the mean intensity along lines": [[191, "measure-the-mean-intensity-along-lines"]], "Measurements": [[190, "measurements"], [196, "measurements"], [265, "measurements"], [298, "measurements"]], "Measurements / region properties": [[193, "measurements-region-properties"], [198, "measurements-region-properties"]], "Measurements and feature extraction": [[2, "measurements-and-feature-extraction"]], "Measurements in objects in tiled images": [[248, null]], "Measurements of central tendency": [[284, "measurements-of-central-tendency"]], "Measurements of spread": [[284, "measurements-of-spread"]], "Measurements/ region properties": [[199, "measurements-region-properties"]], "Measuring distances between objects": [[189, null]], "Measuring features in a time-lapse dataset": [[256, null]], "Measuring features on an image and a label image": [[256, "measuring-features-on-an-image-and-a-label-image"]], "Measuring features on the whole time-lapse dataset": [[256, "measuring-features-on-the-whole-time-lapse-dataset"]], "Measuring intensity on label borders": [[192, null]], "Measuring size": [[211, "measuring-size"]], "Measuring the distance between nearest neighbour cells": [[232, "measuring-the-distance-between-nearest-neighbour-cells"]], "Measuring the standard deviation intensity along a line": [[191, "measuring-the-standard-deviation-intensity-along-a-line"]], "Median filter": [[99, "median-filter"]], "Memory management": [[80, "memory-management"]], "Merging annotated labels": [[156, null]], "Merging labels": [[157, null]], "Merging labels according to border intensity": [[157, "merging-labels-according-to-border-intensity"]], "Merging labels according to centroid-distances": [[159, null]], "Merging labels according to edge-to-edge-distances": [[160, null]], "Merging 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distance maps": [[312, "nearest-neighbor-distance-maps"]], "Nearest neighbor interpolation": [[108, "nearest-neighbor-interpolation"]], "Neighbor meshes in three dimensions": [[208, null]], "Neighborhood analysis in tissues": [[210, null]], "Neighborhood definitions": [[203, null]], "Neighbors of touching neighbors": [[203, "neighbors-of-touching-neighbors"]], "Noise": [[234, "noise"]], "Noise removal": [[234, "noise-removal"]], "Noise removal filters": [[91, null]], "Normalizing the input image": [[149, "normalizing-the-input-image"]], "Nuclei": [[234, "nuclei"]], "Number of pixels map": [[311, "number-of-pixels-map"]], "Number of touching neighbors and proximal neighbors": [[212, "number-of-touching-neighbors-and-proximal-neighbors"]], "Numeric lists": [[7, "numeric-lists"]], "Numpy arrays": [[52, "numpy-arrays"]], "Numpy slices": [[115, "numpy-slices"]], "Object area maps in tiles": [[244, "object-area-maps-in-tiles"]], "Object classification": [[218, "object-classification"]], "Object classification on OpenCL-compatible GPUs": [[214, null]], "Object classification with APOC and SimpleITK-based features": [[215, null]], "Object classification with scikit-learn": [[220, null]], "Object distance map": [[189, "object-distance-map"]], "Object segmentation on OpenCL-compatible GPUs": [[137, null]], "Opening CZI files": [[63, null]], "Opening LIF files": [[66, null]], "Opening and closing labels": [[164, "opening-and-closing-labels"]], "Opening image data": [[64, null]], "Opening images": [[53, "opening-images"]], "Opposite situation": [[289, "opposite-situation"]], "Optimization basics": [[261, null]], "Optimize segmentation algorithms": [[259, null]], "Optimizing parameters for membrane-image based cell segmentation": [[260, null]], "Orientation map": [[311, "orientation-map"]], "Original image": [[115, "original-image"]], "Other Voronoi-Otsu-Labeling implementations": [[128, "other-voronoi-otsu-labeling-implementations"]], "Other background subtraction techniques": [[92, "other-background-subtraction-techniques"]], "Other filters": [[99, "other-filters"]], "Other kernels": [[93, "other-kernels"]], "Other mesh quality measurements": [[176, "other-mesh-quality-measurements"]], "Other techniques and further reading": [[317, "other-techniques-and-further-reading"]], "Other ways of creating arrays": [[52, "other-ways-of-creating-arrays"]], "Outer Join": [[278, "outer-join"]], "Overlay texts on images": [[310, null]], "Overlay visualization": [[192, "overlay-visualization"]], "Overview descriptive statistics": [[269, "overview-descriptive-statistics"]], "P-values correction for multiple comparisons.": [[283, "p-values-correction-for-multiple-comparisons"]], "PSF averaging": [[103, "psf-averaging"]], "Paired/related samples": [[294, "paired-related-samples"]], "Parallelization": [[20, null]], "Parallelization using joblib.Parallel": [[20, "parallelization-using-joblib-parallel"]], "Parallelization using numba": [[18, null]], "Parameter 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"pixel-classification"]], "Pixel classification and Object Segmentation in Napari": [[142, "pixel-classification-and-object-segmentation-in-napari"]], "Pixel classification in multi-channel images": [[143, null]], "Pixel classification on OpenCL-compatible GPUs": [[138, null]], "Pixel classification using Scikit-learn": [[145, null]], "Pixel count map": [[311, "pixel-count-map"]], "Playing with dimensions": [[57, "playing-with-dimensions"]], "Plotting": [[2, "plotting"], [298, "plotting"], [302, "plotting"], [309, null]], "Plotting Distributions with Seaborn": [[306, null]], "Plotting clustering results": [[298, "plotting-clustering-results"]], "Plotting joint and marginal distributions": [[305, "plotting-joint-and-marginal-distributions"]], "Plotting many distributions at once": [[305, "plotting-many-distributions-at-once"]], "Plotting the p-value depending on a given normal distribution": [[293, null]], "Plotting with Matplotlib": [[307, null]], "Post-processing binary images using 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"recap-descriptive-statistics"]], "References": [[221, "references"], [222, "references"]], "Regional properties": [[211, "regional-properties"]], "Regional properties of label": [[211, null]], "Regionalization": [[0, "regionalization"]], "Regression": [[0, "regression"]], "Related works": [[319, "related-works"]], "Remote files": [[75, null]], "Remove labels on image edges": [[167, null]], "Removing layers": [[88, "removing-layers"]], "Renaming columns": [[278, "renaming-columns"]], "Reproducibility": [[48, "reproducibility"]], "Resave scikit-image example data": [[267, null]], "Restructuring data": [[30, "restructuring-data"]], "Result visualization": [[147, "result-visualization"], [149, "result-visualization"]], "Retrieving a file": [[19, "retrieving-a-file"], [74, "retrieving-a-file"]], "Reverting sequential labeling": [[170, "reverting-sequential-labeling"]], "Richardson-Lucy-Deconvolution on OpenCL-compatible GPUs": [[107, null]], "Rigid transform": [[108, "rigid-transform"]], "Rotation": [[108, "rotation"]], "Roundness map": [[311, "roundness-map"]], "Saving 3D images": [[62, "saving-3d-images"]], "Saving 4D images": [[62, "saving-4d-images"]], "Saving and loading surfaces": [[178, null]], "Saving as zarr": [[69, "saving-as-zarr"]], "Saving data frames": [[271, "saving-data-frames"]], "Saving surfaces to disk": [[178, "saving-surfaces-to-disk"]], "Scaling": [[77, null], [108, "scaling"], [117, null], [300, "scaling"]], "Scaling coordinate lists": [[118, null]], "Scaling with the voxel size": [[117, "scaling-with-the-voxel-size"]], "Scatter plot": [[186, "scatter-plot"]], "Scatter plots": [[282, "scatter-plots"]], "Scatter plots with seaborn": [[308, "scatter-plots-with-seaborn"]], "Scatter plots with subplots": [[308, "scatter-plots-with-subplots"]], "Scenario: Comparing different implementations of the same thresholding algorithm": [[230, null]], "Scikit-image rescale() with anti-aliasing": [[115, "scikit-image-rescale-with-anti-aliasing"]], "Scikit-image rescale() without anti-aliasing": [[115, "scikit-image-rescale-without-anti-aliasing"]], "See also": [[60, "see-also"], [106, "see-also"], [229, "see-also"], [230, "see-also"]], "Seeded watershed": [[134, "seeded-watershed"]], "Seeded watershed for membrane-based cell segmentation": [[134, null]], "Seeded watershed using automatic seed detection": [[134, "seeded-watershed-using-automatic-seed-detection"]], "Segmentation": [[130, "segmentation"]], "Segmentation algorithms to compare": [[285, "segmentation-algorithms-to-compare"]], "Segmentation from a loaded segmenter": [[137, "segmentation-from-a-loaded-segmenter"]], "Segmentation post-processing": [[165, null]], "Segmenting nuclei": [[221, "segmenting-nuclei"], [222, "segmenting-nuclei"], [223, "segmenting-nuclei"]], "Select From": [[281, "select-from"]], "Select labels based on their size": [[169, null]], "Select labels using machine learning": [[168, null]], "Selecting columns": [[274, "selecting-columns"], [278, "selecting-columns"]], "Selecting features": [[146, null]], "Selecting labels above a given intensity threshold": [[222, "selecting-labels-above-a-given-intensity-threshold"]], "Selecting ranges in lists": [[8, "selecting-ranges-in-lists"]], "Selecting rows": [[274, "selecting-rows"]], "Selecting rows and columns in pandas DataFrames": [[274, null]], "Semantic segmentation": [[0, "semantic-segmentation"], [135, "semantic-segmentation"]], "Separating test and validation data": [[78, "separating-test-and-validation-data"]], "Sequential labeling": [[0, "sequential-labeling"], [170, "sequential-labeling"]], "Sequential object (re-)labeling": [[170, null]], "Setting up Python and Conda environments": [[1, "setting-up-python-and-conda-environments"]], "Setting up a dataset": [[291, null], [292, null]], "Setting up your computer": [[1, null]], "Shape descriptors based on neighbor meshes": [[195, "shape-descriptors-based-on-neighbor-meshes"]], "Shape descriptors based on neighborhood graphs": 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"Snippets": [[266, null]], "Sobel operator": [[95, "sobel-operator"]], "Solidity map": [[311, "solidity-map"]], "Sorting in tables": [[269, "sorting-in-tables"]], "Sorting lists": [[9, null]], "Sorting tables": [[281, "sorting-tables"]], "Sparse annotations": [[135, "sparse-annotations"]], "Spatial transforms": [[116, null]], "Specific functions": [[14, "specific-functions"]], "Specific measures": [[199, "specific-measures"]], "Specifying the number of rows to query": [[281, "specifying-the-number-of-rows-to-query"]], "Split touching objects": [[124, null]], "Splitting touching objects": [[173, null]], "Spot detection": [[232, "spot-detection"]], "Standard Scaling": [[77, "standard-scaling"]], "Standard scaling": [[301, "standard-scaling"], [302, "standard-scaling"]], "Starting point": [[298, "starting-point"]], "Starting point: Label map": [[312, "starting-point-label-map"]], "Starting point: a binary image": [[188, "starting-point-a-binary-image"], [190, 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of measurements": [[300, null]], "Sub-modules": [[14, "sub-modules"]], "Sub-plots": [[307, "sub-plots"]], "Sub-sampling images": [[55, "sub-sampling-images"]], "Subsequently labeling": [[167, "subsequently-labeling"]], "Summarizing measurements": [[277, null]], "Summarizing subsets of data": [[275, null]], "Summary": [[115, "summary"]], "Summary statistics with Pandas": [[287, "summary-statistics-with-pandas"]], "Supervised machine learning": [[78, null]], "Surface measurements": [[183, null]], "Surface processing": [[177, null]], "Surface quality measurements using vedo in napari": [[176, null]], "Surface vertex classification": [[180, null]], "Surface visualization": [[183, "surface-visualization"]], "Surfaces from individual labels": [[175, "surfaces-from-individual-labels"]], "T-Test": [[290, null]], "Tables": [[10, "tables"]], "Tabular data wrangling": [[273, null]], "Terminology": [[135, null]], "Terminology: What are TP, TN, FP, FN": [[227, "terminology-what-are-tp-tn-fp-fn"]], 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92, "zfish_top_hat": 92, "zip": [12, 25, 185, 188, 254, 256, 279, 282], "zoom": [62, 88, 91, 92, 93, 95, 117, 184, 221], "zoom_factor": [44, 97, 117, 162, 188, 190, 256, 258], "zstd": [69, 244, 246, 247], "zu": [73, 318], "zuckerberg": 319, "zugriff": 318, "zum": 318, "zumutbar": 318, "zur": 318, "zurich": 65, "zusendung": 318, "zustimmung": 318, "zy": 117, "zyx": [49, 65, 112], "\u00b5": [18, 20], "\u00b5m": [103, 104, 115], "\u00ecntensity_mean": 306, "\u00fcbermittelt": 318, "\u00fcbernehmen": 318, "\u00fcberpr\u00fcft": 318, "\u00fcbersendung": 318, "\u00fcberwachen": 318, "\u017eigutyt\u0117": 319}, "titles": ["Glossary", "Setting up your computer", "Trailer: Bio-image Analysis with Python", "Python code in Jupyter notebooks", "Basic math in python", "Pitfalls when working with Jupyter notebooks", "Basic types in python", "Lists and tuples", "Cropping lists", "Sorting lists", "Dictionaries", "Conditions", "Loops", "Functions", "Importing functions and packages", "Python basics", "Custom libraries", "Functional parameters", "Parallelization using numba", "Accessing image files in the owncloud", "Parallelization", "Partial functions", "Advanced python programming", "Divide and rule", "Don\u2019t repeat yourself", "Keep it short and simple", "Prevent magic numbers", "Writing good code", "Writing sustainable code", "Prompting chatGPT", "Prompting for text", "Generating images using DALL-E", "Generating images using Stable Diffusion", "Generating Magnetic Resonance images using DALL-E", "Generating code", "Generating code for processing images", "Generating advanced image analysis code", "Prompting tasks using LangChain", "Prompting bio-image analysis tasks using LangChain", "Allowing language models to choose the right algorithm", "BIA Bob", "Bug fixing", "Documenting code", "Prompting tasks for pandas", "Inpainting using Dall-E", "Inpainting using Stable Diffusion", "Image variations using Dall-E", "Image variations using Stable Diffusion", "Image editing using instruct-pix2pix", "Large language model fine tuning", "Versions of libraries", "Prompt engineering", "Images are arrays of numbers", "Working with images", "Computing with images", "Cropping images", "Indexing numpy arrays", "Multi-channel image data", "Exercise: Analyse the bending of a banana in MRI", "Brightness and Contrast", "Image analysis basics", "Skeletonization", "Pros and cons of image file formats", "Opening CZI files", "Opening image data", "Reading files with AICSImageIO", "Opening LIF files", "Loading multi-channel / multi-position folders of tif-files", "Image file formats", "Tiled image file formats: zarr", "Exploring the BioImage Archive", "Reading meta data from DOI.org", "Exploring the Image Data Resource", "Accessing meta data on Zenodo", "Accessing image files in the nextcloud", "Remote files", "Machine learning basics", "Scaling", "Supervised machine learning", "Unsupervised machine learning", "clEsperanto", "Further reading", "Tracing memory consumption", "GPU accelerated image processing", "Why GPU-acceleration makes sense", "Interactive image visualization with napari", "Multidimensional image stacks", "Inspecting 3D image data with pyclesperanto", "Interactive image visualization with napari", "Image visualization in 3D", "Filtering images", "Noise removal filters", "Background removal filters", "Convolution", "Divide by Gaussian", "Edge detection", "Filter overview", "Image Processing Filters", "Image filtering", "Processing images using SimpleITK", "Filtering images", "Deconvolution on CUDA-compatible GPUs", "Deconvolution on CUDA-compatible GPUs", "Determining the point-spread-function from a bead image by averaging", "Determining the point-spread-function from a bead image by distilling", "An introduction to image deconvolution", "Image deconvolution", "Richardson-Lucy-Deconvolution on OpenCL-compatible GPUs", "Affine transforms using clesperanto", "Affine transforms using cupy", "Affine transforms using scikit-image", "Affine transforms using Scipy", "Coordinate systems", "Croppning images to stitch them later", "Slicing and cropping", "Down-scaling and denoising", "Spatial transforms", "Scaling", "Scaling coordinate lists", "Stitching images", "Axis transposition benchmarking", "Image segmentation", "Thresholding", "Binary mask refinement", "Split touching objects", "Label images", "Gauss-Otsu-labeling", "Touching objects labeling", "Voronoi-Otsu-labeling", "Eroded Otsu-labeling", "3D Image Segmentation", "Image Binarization", "Preventing leaking labels", "Image segmentation", "Seeded watershed for membrane-based cell segmentation", "Terminology", "Voronoi-Otsu-Labeling on binary images", "Object segmentation on OpenCL-compatible GPUs", "Pixel classification on OpenCL-compatible GPUs", "Probability maps", "Training pixel classifiers from folders of images", "Generating feature stacks", "Interactive pixel classification and object segmentation in Napari", "Pixel classification in multi-channel images", "Machine learning for image segmentation", "Pixel classification using Scikit-learn", "Selecting features", "Image Segmentation with CellPose", "Deep Learning based image segmentation", "Image segmentation with StarDist", "Large Language Vision Models", "Vision Large Language Models for Counting objects", "Modifying borders of tissues", "Identifying labels which touch the background", "Inner and outer cell borders", "Edges of labels", "Merging annotated labels", "Merging labels", "Merging objects using machine learning", "Merging labels according to centroid-distances", "Merging labels according to edge-to-edge-distances", "Mimicking ImageJ\u2019s watershed algorithm", "The mode filter for correcting semantic segmentation results", "Post-processing binary images using morphological operations", "Label image refinement", "Segmentation post-processing", "Post-processing for membrane-based cell segmentation", "Remove labels on image edges", "Select labels using machine learning", "Select labels based on their size", "Sequential object (re-)labeling", "Binary Image Skeletonization", "Smoothing labels", "Splitting touching objects", "Connected component labeling on surfaces", "Creating surfaces", "Surface quality measurements using vedo in napari", "Surface processing", "Saving and loading surfaces", "Smoothing and simplifying surfaces", "Surface vertex classification", "Converting points and surfaces", "From surface data to image data", "Surface measurements", "Visualizing surfaces", "&lt;no title&gt;", "Comparison of measurements from different libraries", "Counting bright objects in images", "Measure distance along a center line", "Measuring distances between objects", "Measure distance to a center line", "Descriptive statistics of [many] lines in an image", "Measuring intensity on label borders", "Quantitative image analysis", "Feature extraction", "Shape descriptors based on neighborhood graphs", "Statistics using Nyxus", "Basic statistics with pyclesperanto", "Statistics using Scikit-image", "Statistics using SimpleITK", "Blob detection", "Local maxima detection", "Blob detection", "Neighborhood definitions", "Count touching neighbors", "Draw distance-meshes between neighbors", "Measure the distance to cells in another label image", "Label neighbor filters", "Neighbor meshes in three dimensions", "Count proximal labels in an other label image", "Neighborhood analysis in tissues", "Regional properties of label", "Statistics of neighbors", "Label touch count and touch portion", "Object classification on OpenCL-compatible GPUs", "Object classification with APOC and SimpleITK-based features", "&lt;no title&gt;", "Random forest decision making statistics", "Interactive object classification in Napari", "Cell classification", "Object classification with scikit-learn", "Counting nuclei according to expression in multiple channels", "Differentiating nuclei according to signal intensity", "Distance-based colocalization", "Measure overlap between two label images", "Colocalization", "Jaccard-Index versus Accuracy", "Metrics to investigate segmentation quality", "Quantitative labeling comparison", "Algorithm validation", "Scenario: Comparing different implementations of the same thresholding algorithm", "Image segmentation quality measurements", "Validation of spot counting pipelines", "Visual labeling comparison", "Simulation of image formation + image restoration", "Counting cell neighbors in tissues", "Simulating data", "Interactive image visualization with napari", "Visualizing region properties in napari", "Interactive cropping with napari", "Tribolium embryo morphometry over time in Napari", "Interactive parameter tuning with napari and magicgui", "Graphical user interfaces", "Tiled image processing", "Map area of objects in tiles", "Connected component labeling in tiles", "Counting nuclei in tiles", "Tiled image processing, a quick run-through", "Measurements in objects in tiled images", "Tiling images - the naive approach", "Tiling images with overlap", "How process files in a folder", "Processing timelapse data", "<code class=\"docutils literal notranslate\"><span class=\"pre\">zip</span></code> for Processing Paired Folders", "Batch processing", "&lt;no title&gt;", "Measuring features in a time-lapse dataset", "Timelapse analysis", "Cell tracking", "Optimize segmentation algorithms", "Optimizing parameters for membrane-image based cell segmentation", "Optimization basics", "Parameter optimization", "Load and show an image", "Load an image and measure shape of objects in 3D", "Starting point: a label image", "Snippets", "Resave scikit-image example data", "Appending tables", "Exploring tabular data", "Handling NaN values", "Introduction to working with DataFrames", "Pivot tables", "Tabular data wrangling", "Selecting rows and columns in pandas DataFrames", "Summarizing subsets of data", "Tidy-Data", "Summarizing measurements", "Combining tables", "Experimental data", "Querying databases", "Querying databases using SQL", "Method comparison", "Load the data", "Descriptive statistics", "Bland-Altman analysis to compare segmentation algorithms", "Bland-Altman plots in practice", "Descriptive statistics of labeled images", "Descriptive statistics", "Equivalence testing", "T-Test", "Setting up a dataset", "Setting up a dataset", "Plotting the p-value depending on a given normal distribution", "Uniform distribution", "Hypothesis testing", "densMAP", "Feature selection", "Interactive dimensionality reduction and clustering", "Clustering", "Studying spatial distribution of measurements", "Clustering - a quick walkthrough", "Clustering with UMAPs", "Feature correlation", "Visualizing relationships between feature spaces", "Multivariate views", "Plotting Distributions with Seaborn", "Plotting with Matplotlib", "Introduction to Seaborn", "Plotting", "Overlay texts on images", "Parametric maps", "Quantitative maps from neighbor statistics", "Data visualization", "The Napari Assistant", 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"Measuring features on an image and a label image": [[256, "measuring-features-on-an-image-and-a-label-image"]], "Measuring features on the whole time-lapse dataset": [[256, "measuring-features-on-the-whole-time-lapse-dataset"]], "Measuring intensity on label borders": [[192, null]], "Measuring size": [[211, "measuring-size"]], "Measuring the distance between nearest neighbour cells": [[232, "measuring-the-distance-between-nearest-neighbour-cells"]], "Measuring the standard deviation intensity along a line": [[191, "measuring-the-standard-deviation-intensity-along-a-line"]], "Median filter": [[99, "median-filter"]], "Memory management": [[80, "memory-management"]], "Merging annotated labels": [[156, null]], "Merging labels": [[157, null]], "Merging labels according to border intensity": [[157, "merging-labels-according-to-border-intensity"]], "Merging labels according to centroid-distances": [[159, null]], "Merging labels according to edge-to-edge-distances": [[160, null]], "Merging 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"Object classification on OpenCL-compatible GPUs": [[214, null]], "Object classification with APOC and SimpleITK-based features": [[215, null]], "Object classification with scikit-learn": [[220, null]], "Object distance map": [[189, "object-distance-map"]], "Object segmentation on OpenCL-compatible GPUs": [[137, null]], "Opening CZI files": [[63, null]], "Opening LIF files": [[66, null]], "Opening and closing labels": [[164, "opening-and-closing-labels"]], "Opening image data": [[64, null]], "Opening images": [[53, "opening-images"]], "Opposite situation": [[289, "opposite-situation"]], "Optimization basics": [[261, null]], "Optimize segmentation algorithms": [[259, null]], "Optimizing parameters for membrane-image based cell segmentation": [[260, null]], "Orientation map": [[311, "orientation-map"]], "Original image": [[115, "original-image"]], "Other Voronoi-Otsu-Labeling implementations": [[128, "other-voronoi-otsu-labeling-implementations"]], "Other background subtraction 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"Rotation": [[108, "rotation"]], "Roundness map": [[311, "roundness-map"]], "Saving 3D images": [[62, "saving-3d-images"]], "Saving 4D images": [[62, "saving-4d-images"]], "Saving and loading surfaces": [[178, null]], "Saving as zarr": [[69, "saving-as-zarr"]], "Saving data frames": [[271, "saving-data-frames"]], "Saving surfaces to disk": [[178, "saving-surfaces-to-disk"]], "Scaling": [[77, null], [108, "scaling"], [117, null], [300, "scaling"]], "Scaling coordinate lists": [[118, null]], "Scaling with the voxel size": [[117, "scaling-with-the-voxel-size"]], "Scatter plot": [[186, "scatter-plot"]], "Scatter plots": [[282, "scatter-plots"]], "Scatter plots with seaborn": [[308, "scatter-plots-with-seaborn"]], "Scatter plots with subplots": [[308, "scatter-plots-with-subplots"]], "Scenario: Comparing different implementations of the same thresholding algorithm": [[230, null]], "Scikit-image rescale() with anti-aliasing": [[115, "scikit-image-rescale-with-anti-aliasing"]], "Scikit-image 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92, "zfish_top_hat": 92, "zip": [12, 25, 185, 188, 254, 256, 279, 282], "zoom": [62, 88, 91, 92, 93, 95, 117, 184, 221], "zoom_factor": [44, 97, 117, 162, 188, 190, 256, 258], "zstd": [69, 244, 246, 247], "zu": [73, 318], "zuckerberg": 319, "zugriff": 318, "zum": 318, "zumutbar": 318, "zur": 318, "zurich": 65, "zusendung": 318, "zustimmung": 318, "zy": 117, "zyx": [49, 65, 112], "\u00b5": [18, 20], "\u00b5m": [103, 104, 115], "\u00ecntensity_mean": 306, "\u00fcbermittelt": 318, "\u00fcbernehmen": 318, "\u00fcberpr\u00fcft": 318, "\u00fcbersendung": 318, "\u00fcberwachen": 318, "\u017eigutyt\u0117": 319}, "titles": ["Glossary", "Setting up your computer", "Trailer: Bio-image Analysis with Python", "Python code in Jupyter notebooks", "Basic math in python", "Pitfalls when working with Jupyter notebooks", "Basic types in python", "Lists and tuples", "Cropping lists", "Sorting lists", "Dictionaries", "Conditions", "Loops", "Functions", "Importing functions and packages", "Python basics", "Custom libraries", "Functional parameters", "Parallelization using numba", "Accessing image files in the owncloud", "Parallelization", "Partial functions", "Advanced python programming", "Divide and rule", "Don\u2019t repeat yourself", "Keep it short and simple", "Prevent magic numbers", "Writing good code", "Writing sustainable code", "Prompting chatGPT", "Prompting for text", "Generating images using DALL-E", "Generating images using Stable Diffusion", "Generating Magnetic Resonance images using DALL-E", "Generating code", "Generating code for processing images", "Generating advanced image analysis code", "Prompting tasks using LangChain", "Prompting bio-image analysis tasks using LangChain", "Allowing language models to choose the right algorithm", "BIA Bob", "Bug fixing", "Documenting code", "Prompting tasks for pandas", "Inpainting using Dall-E", "Inpainting using Stable Diffusion", "Image variations using Dall-E", "Image variations using Stable Diffusion", "Image editing using instruct-pix2pix", "Large language model fine tuning", "Versions of libraries", "Prompt engineering", "Images are arrays of numbers", "Working with images", "Computing with images", "Cropping images", "Indexing numpy arrays", "Multi-channel image data", "Exercise: Analyse the bending of a banana in MRI", "Brightness and Contrast", "Image analysis basics", "Skeletonization", "Pros and cons of image file formats", "Opening CZI files", "Opening image data", "Reading files with AICSImageIO", "Opening LIF files", "Loading multi-channel / multi-position folders of tif-files", "Image file formats", "Tiled image file formats: zarr", "Exploring the BioImage Archive", "Reading meta data from DOI.org", "Exploring the Image Data Resource", "Accessing meta data on Zenodo", "Accessing image files in the nextcloud", "Remote files", "Machine learning basics", "Scaling", "Supervised machine learning", "Unsupervised machine learning", "clEsperanto", "Further reading", "Tracing memory consumption", "GPU accelerated image processing", "Why GPU-acceleration makes sense", "Interactive image visualization with napari", "Multidimensional image stacks", "Inspecting 3D image data with pyclesperanto", "Interactive image visualization with napari", "Image visualization in 3D", "Filtering images", "Noise removal filters", "Background removal filters", "Convolution", "Divide by Gaussian", "Edge detection", "Filter overview", "Image Processing Filters", "Image filtering", "Processing images using SimpleITK", "Filtering images", "Deconvolution on CUDA-compatible GPUs", "Deconvolution on CUDA-compatible GPUs", "Determining the point-spread-function from a bead image by averaging", "Determining the point-spread-function from a bead image by distilling", "An introduction to image deconvolution", "Image deconvolution", "Richardson-Lucy-Deconvolution on OpenCL-compatible GPUs", "Affine transforms using clesperanto", "Affine transforms using cupy", "Affine transforms using scikit-image", "Affine transforms using Scipy", "Coordinate systems", "Croppning images to stitch them later", "Slicing and cropping", "Down-scaling and denoising", "Spatial transforms", "Scaling", "Scaling coordinate lists", "Stitching images", "Axis transposition benchmarking", "Image segmentation", "Thresholding", "Binary mask refinement", "Split touching objects", "Label images", "Gauss-Otsu-labeling", "Touching objects labeling", "Voronoi-Otsu-labeling", "Eroded Otsu-labeling", "3D Image Segmentation", "Image Binarization", "Preventing leaking labels", "Image segmentation", "Seeded watershed for membrane-based cell segmentation", "Terminology", "Voronoi-Otsu-Labeling on binary images", "Object segmentation on OpenCL-compatible GPUs", "Pixel classification on OpenCL-compatible GPUs", "Probability maps", "Training pixel classifiers from folders of images", "Generating feature stacks", "Interactive pixel classification and object segmentation in Napari", "Pixel classification in multi-channel images", "Machine learning for image segmentation", "Pixel classification using Scikit-learn", "Selecting features", "Image Segmentation with CellPose", "Deep Learning based image segmentation", "Image segmentation with StarDist", "Large Language Vision Models", "Vision Large Language Models for Counting objects", "Modifying borders of tissues", "Identifying labels which touch the background", "Inner and outer cell borders", "Edges of labels", "Merging annotated labels", "Merging labels", "Merging objects using machine learning", "Merging labels according to centroid-distances", "Merging labels according to edge-to-edge-distances", "Mimicking ImageJ\u2019s watershed algorithm", "The mode filter for correcting semantic segmentation results", "Post-processing binary images using morphological operations", "Label image refinement", "Segmentation post-processing", "Post-processing for membrane-based cell segmentation", "Remove labels on image edges", "Select labels using machine learning", "Select labels based on their size", "Sequential object (re-)labeling", "Binary Image Skeletonization", "Smoothing labels", "Splitting touching objects", "Connected component labeling on surfaces", "Creating surfaces", "Surface quality measurements using vedo in napari", "Surface processing", "Saving and loading surfaces", "Smoothing and simplifying surfaces", "Surface vertex classification", "Converting points and surfaces", "From surface data to image data", "Surface measurements", "Visualizing surfaces", "&lt;no title&gt;", "Comparison of measurements from different libraries", "Counting bright objects in images", "Measure distance along a center line", "Measuring distances between objects", "Measure distance to a center line", "Descriptive statistics of [many] lines in an image", "Measuring intensity on label borders", "Quantitative image analysis", "Feature extraction", "Shape descriptors based on neighborhood graphs", "Statistics using Nyxus", "Basic statistics with pyclesperanto", "Statistics using Scikit-image", "Statistics using SimpleITK", "Blob detection", "Local maxima detection", "Blob detection", "Neighborhood definitions", "Count touching neighbors", "Draw distance-meshes between neighbors", "Measure the distance to cells in another label image", "Label neighbor filters", "Neighbor meshes in three dimensions", "Count proximal labels in an other label image", "Neighborhood analysis in tissues", "Regional properties of label", "Statistics of neighbors", "Label touch count and touch portion", "Object classification on OpenCL-compatible GPUs", "Object classification with APOC and SimpleITK-based features", "&lt;no title&gt;", "Random forest decision making statistics", "Interactive object classification in Napari", "Cell classification", "Object classification with scikit-learn", "Counting nuclei according to expression in multiple channels", "Differentiating nuclei according to signal intensity", "Distance-based colocalization", "Measure overlap between two label images", "Colocalization", "Jaccard-Index versus Accuracy", "Metrics to investigate segmentation quality", "Quantitative labeling comparison", "Algorithm validation", "Scenario: Comparing different implementations of the same thresholding algorithm", "Image segmentation quality measurements", "Validation of spot counting pipelines", "Visual labeling comparison", "Simulation of image formation + image restoration", "Counting cell neighbors in tissues", "Simulating data", "Interactive image visualization with napari", "Visualizing region properties in napari", "Interactive cropping with napari", "Tribolium embryo morphometry over time in Napari", "Interactive parameter tuning with napari and magicgui", "Graphical user interfaces", "Tiled image processing", "Map area of objects in tiles", "Connected component labeling in tiles", "Counting nuclei in tiles", "Tiled image processing, a quick run-through", "Measurements in objects in tiled images", "Tiling images - the naive approach", "Tiling images with overlap", "How process files in a folder", "Processing timelapse data", "<code class=\"docutils literal notranslate\"><span class=\"pre\">zip</span></code> for Processing Paired Folders", "Batch processing", "&lt;no title&gt;", "Measuring features in a time-lapse dataset", "Timelapse analysis", "Cell tracking", "Optimize segmentation algorithms", "Optimizing parameters for membrane-image based cell segmentation", "Optimization basics", "Parameter optimization", "Load and show an image", "Load an image and measure shape of objects in 3D", "Starting point: a label image", "Snippets", "Resave scikit-image example data", "Appending tables", "Exploring tabular data", "Handling NaN values", "Introduction to working with DataFrames", "Pivot tables", "Tabular data wrangling", "Selecting rows and columns in pandas DataFrames", "Summarizing subsets of data", "Tidy-Data", "Summarizing measurements", "Combining tables", "Experimental data", "Querying databases", "Querying databases using SQL", "Method comparison", "Load the data", "Descriptive statistics", "Bland-Altman analysis to compare segmentation algorithms", "Bland-Altman plots in practice", "Descriptive statistics of labeled images", "Descriptive statistics", "Equivalence testing", "T-Test", "Setting up a dataset", "Setting up a dataset", "Plotting the p-value depending on a given normal distribution", "Uniform distribution", "Hypothesis testing", "densMAP", "Feature selection", "Interactive dimensionality reduction and clustering", "Clustering", "Studying spatial distribution of measurements", "Clustering - a quick walkthrough", "Clustering with UMAPs", "Feature correlation", "Visualizing relationships between feature spaces", "Multivariate views", "Plotting Distributions with Seaborn", "Plotting with Matplotlib", "Introduction to Seaborn", "Plotting", "Overlay texts on images", "Parametric maps", "Quantitative maps from neighbor statistics", "Data visualization", "The Napari Assistant", 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