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"info": {
"author": "Vincent Toureau",
"author_email": "Vincent.Toureau@grenoble-inp.org",
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"description": "# dermoscopic_symmetry\n\ndermoscopic_symmetry is a Python package aiming at study skin lesion's symmetry (regarding shape and textures)\nand help the diagnose of diseases like melanomas.
Basically, the symmetry study is divided into\ntwo parts: shapes symmetry and textures symmetry. Here, shapes means the aspect of the outskirts of a lesion\nand its global form whereas textures stand for colors and types of perceived textures.\n\n**Note :** The package has been built referring to the [PH\u00b2 Dataset](https://www.fc.up.pt/addi/ph2%20database.html).\nSee :\n\n[Teresa Mendon\u00e7a, Pedro M. Ferreira, Jorge Marques, Andre R. S. Marcal, \nJorge Rozeira. PH\u00b2 - A dermoscopic image database for research and \nbenchmarking, 35th International Conference of the IEEE Engineering in \nMedicine and Biology Society, July 3-7, 2013, Osaka, Japan.](https://ieeexplore.ieee.org/document/6610779?tp=&arnumber=6610779&url=http:%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6610779)\n\nTo be able to use it directly and properly, you must download and have \naccess to it.\n\n ## Installation\n\n Use [pip](https://pip.pypa.io/en/stable/) to install the package.\n\n ```bash\n pip install dermoscopic_symmetry\n ```\n These are the Python files used to study the symmetry of skin lesions from the PH\u00b2 Dataset\n (see Usage section):\n\n1. **`shape_symmetry.py`** : containing functions to study the symmetry of shapes in a lesion's image.\n\n2. **`classifier_feeder.py`** : containing functions to create a classifier able to recognize if 2 patches taken in a lesion's\n image are similar or not.
A new dataset called `patchesDataSet`, derivating from the PH\u00b2 Dataset, has been designed to \n train this classifier. It is composed of patches pairs taken in the PH\u00b2 Dataset images with \n one half similar and the other non similar.\n\n3. **`patches_for_texture_symmetry.py`** : containing functions to take patches from a dermoscopic image and extract\nfeatures from them (textures and color).\n\n4. **`texture_symmetry.py`** : containing functions using the previous classifier and features\nto study the symmetry of textures in a lesion's image.\n\n5. **`combined_classifier.py`** : containing functions using only shape features, only textures\nfeatures or both of them to train classifiers and be able to know which one is the best\naccording to expert diagnose in the PH\u00b2 Dataset.\n
Those classifiers are trained according to the `ShapesScores.csv`, `TextureScores.csv` and\n`ShapeAndTextureScores.csv` files contained in the `data` repository. The final models are saved as `shapeModel.pkl`, `textureModel.pkl` and \n`shapeAndTextureModel.pkl` in the `data/models` repository.\n\n**Note :** The code used to create the \npatchesDataSet is given in the **`patches_dataset_creator.py`** file. The **`utils.py`** file contains the utilities \nfunctions.\n\n ## Usage\n\nEach code script has an :\n`example()` function at the beginning aiming at presenting its functionalities. This function is run\nas a default `main`.\n\n## License\n\n[MIT](https://choosealicense.com/licenses/mit/)\n\n\n",
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"summary": "A package to study skin lesion's symmetry and help diagnose diseases like menalomas.",
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