MitoSeg is a tool developed for mitochondria detection and segmentation based on the algorithm proposed in:
Tasel, S.F., Mumcuoglu, E.U., Hassanpour, R.Z. and Perkins, G., 2016. A validated active contour method driven by parabolic arc model for detection and segmentation of mitochondria. Journal of structural biology, 194(3), pp.253-271.
Please cite this paper if you use MitoSeg in your research.
MitoSeg uses the following libraries:
To compile and use MitoSeg, development files for OpenCV4, Boost, and yaml-cpp must be installed. For GNU/Linux distributions based on Debian (e.g., Ubuntu):
apt install libopencv-dev libboost-dev libboost-program-options-dev libyaml-cpp-dev
Please refer to respective user guides for other GNU/Linux distributions or operating systems.
MitoSeg can be compiled with:
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make -j $(nproc)
mitoseg [OPTION] --zrange # # --psize # FILENAME_PATTERN
| Argument | Description |
|---|---|
--zrange <start slice #> <end slice #> |
Slice z-range start / end. |
--psize <pixel size> |
Pixel size in nm/px. |
FILENAME_PATTERN |
Filename of slice images and slice number tag. %d indicates the position of the slice number tag. For example, mito%d.bmp generates file names such as mito0.bmp, mito1.bmp, etc. and mito%03d.bmp generates file names such as mito000.bmp, mito001.bmp, etc. |
| Argument | Description |
|---|---|
--roi <left> <top> <width> <height> |
Specifies the left and top pixel coordinates and the width and height of the bounding rectangle of the interested region of segmentation. If not used, ROI will be determined automatically. |
--src <directory> |
Specifies the path of the dataset image files. |
--dst <directory> |
Specifies the directory where the outputs (intermediate data and image files, final segmentation image files, an IMOD model file (.mod), and a 3D mesh file (.ply)) are stored. |
--valid <validity threshold> |
Specifies the validity threshold that is explained in the paper. Must be between 0 and 1 (default: 0.75). |
--thick <z-thickness> |
Specifies the snake z-thickness. The given value must be between 5 and 500 (default: 20). Can be set to full to use the whole z-range specified by the --zrange argument. Snake thickness affects the segmentation accuracy; thicker snakes provide continuous smooth segmentation along the z-range, but can also produce more false negatives. |
--phase <phase #> |
Specifies a specific phase to be executed (1, 2, or 3). The --valid and --thick arguments affect the 2nd and 3rd phases, respectively. Hence, if the same portion of the dataset is to be segmented by changing only these arguments, the --phase argument can be used to restart a particular phase to avoid redundant computation manually. If not used, MitoSeg will execute all phases in order. |
--cores |
Specifies the number of CPU cores that work in collaboration to speed up the process. |
--settings-file <file path> |
Specifies the path of a YAML file containing custom segmentation variables. |
-
Process the files dataset_slice0030.tif to dataset_slice0100.tif assuming that pixel size is 2.0nm:
./mitoseg --zrange 30 100 --psize 2.0 dataset_slice%04d.tif -
Process the files mito40.bmp to mito120.bmp from the slices directory, assuming that pixel size is 1.1nm:
./mitoseg --src slices --zrange 40 120 --psize 1.1 mito%d.bmp -
Load custom settings from settings.yaml, process the files slice0020.bmp to slice0080.bmp, assuming the pixel size is 2.1nm, and save the results in the outputs directory:
./mitoseg --settings-file settings.yaml --dst outputs --zrange 20 80 --psize 2.1 slice00%d.bmp
MitoSeg can also be used within a Docker environment, which eliminates the need to prepare the building environment on your computer, and allows MitoSeg to run on various operating systems easily. A sample Dockerfile is provided under the docker directory, which can be used for building a Docker image by executing the following command within the docker directory:
docker build -t mitoseg .
After the image is built, it can be run by executing the provided docker-mitoseg.sh (for Linux/Mac) or docker-mitoseg.cmd (for Windows) scripts. These scripts include instructions and guidelines, and can be modified according to specific needs.