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NucDetect is a Python package that is designed to identify the typical protein foci which which can be observed after DNA double strand breaks (such as γH2AX foci). It uses fluorescence images (in the rgb color space) to to identify and quantify the nucleus and foci on both the red and green channel. After analysis, the results can be either obtained as table or as image with marked foci. Images can be arranged into experiments, which can be divided into groups. Each experiment may then be statistically analysed (each group will be compared to a Poisson distribution and a boxplot will be created). If the automatic detection of foci is not accurat, the user can manually modify the results to add missing foci, merge oversegmented nuclei or remove falsely identified nuclei and/or foci.
NucDetect combines classical image processing with machine learning. For each analysis, the user can choose to either use the image processing based approach for detection or an pre-trained Fully Convolutional Network with U-Net architecture. The differentiation between both approaches is grounded in the experimental status of the ML approach. In the future, both approaches might be compared to improve detection accuracy
The FCN will be trained with data obtained from manually modified automatic detection. This means a classical algorithmic approach is used for nucleus and focus detection, which will be then manually modified to correct errors such as oversegmented nuclei, missing foci et cetera. The so generated data will be then used to train the CNN to obtain higher detection accuracy than a classical image processing approach.
Every component of the UI has an assigned tooltiup. If you do not know what a specific component does, just hover with your mouse cursor over it and a small explanation will appear after a short time.
The main window will be shown on start of the program. It contains the main toolbar (upper row of buttons), the result table (shows the analysis results), the image list (a list of all images found in the folder User/NucDetect/images) and the image toolbar (row of buttons below the image list).
The Main Toolbar contains following buttons (from left to right):
- Load Image: Opens a selection dialog to load an image that is not placed in the images folder
- Experiments: Opens the experiment dialog
- Statistics: Opens the statistics dialog
- CSV: Saves the data shown in the results table. Is inactive, if no image was selected in the images list
- Images: Shows the detected foci and nuclei of the selected image. Is inactive, if no image was selected or if the selected image was not analysed
- Categories: Opens the category dialog. Is inactive if no image was selected.
- Modify: Opens the modification dialog. Is inactive, if no image was selected or if the selected image was not analysed.
- Settings: Opens the settings dialog
The Images Toolbar contains following buttons (from left to right):
- Analyse: analyse the selected image. This will open the analysis settings dialog
- Analyse All: analyse all images in the image list. This will open the analysis settings dialog
- Delete: removes the selected image from the image list
- Delete All: removes all images from the image list
- Reload: Initiates a new scan of the images folder. Will add images to the image list, that are placed there after the program start
Images placed in the folder User/NucDetect/images will be automatically loaded and shown in the image list. If no images are added to the folder User/NucDetect/images, the user needs to place images there and press the reload button (two arrows forming a circle). This can also be used if new images are placed inside the Images folder whilst the program is open.
The progress bar can be found at the bottom of the main window. It will show the analysis or loading progress.