Wiki source code of 4. Image segmentation with ilastik
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| 1 | == Analysis approach for series of rodent brain section image == | ||
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| 3 | There are two main approaches for the analysis of rodent brain section images. | ||
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| 5 | 1. Pixel classification only (with two or more classes) | ||
| 6 | 1. Pixel classification with two classes (//immunoreactivity// and //background//), followed by object classification with two classes (//objects-of-interest// and //artefact//). | ||
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| 8 | **Which approach is best for my dataset?** | ||
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| 10 | As a general rule, pixel classification is suitable for images in which there are clear differences in the colour, intensity and/ or texture of the feature-of-interest versus the background and other structures. If there is non-specific labelling in the image that is very similar in appearance to the labelling-of-interest, object classification may allow the non-specific labelling to be filtered out based on object level features such as size and shape. The best approach is determined by trial and error. | ||
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| 12 | === Pixel classification workflow === | ||
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| 14 | For a quick introduction, watch: [[https:~~/~~/www.youtube.com/watch?v=5N0XYW9gRZY&feature=youtu.be>>url:https://www.youtube.com/watch?v=5N0XYW9gRZY&feature=youtu.be]] | ||
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| 18 | ==== ==== | ||
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