A package to study skin lesion's symmetry and help diagnose diseases like menalomas.
dermoscopic_symmetry is a Python package aiming at study skin lesion's symmetry (regarding shape and textures)
and help the diagnose of diseases like melanomas.
Basically, the symmetry study is divided into two parts: shapes symmetry and textures symmetry. Here, shapes means the aspect of the outskirts of a lesion and its global form whereas textures stand for colors and types of perceived textures.
Note : The package has been built referring to the PH² Dataset. See :
Teresa Mendonça, Pedro M. Ferreira, Jorge Marques, Andre R. S. Marcal, Jorge Rozeira. PH² - A dermoscopic image database for research and benchmarking, 35th International Conference of the IEEE Engineering in Medicine and Biology Society, July 3-7, 2013, Osaka, Japan.
To be able to use it directly and properly, you must download and have access to it.
Use pip to install the package.
pip install dermoscopic_symmetry
These are the Python files used to study the symmetry of skin lesions from the PH² Dataset (see Usage section):
shape_symmetry.py: containing functions to study the symmetry of shapes in a lesion's image.
classifier_feeder.py: containing functions to create a classifier able to recognize if 2 patches taken in a lesion's image are similar or not.
A new dataset called
patchesDataSet, derivating from the PH² Dataset, has been designed to train this classifier. It is composed of patches pairs taken in the PH² Dataset images with one half similar and the other non similar.
patches_for_texture_symmetry.py: containing functions to take patches from a dermoscopic image and extract features from them (textures and color).
texture_symmetry.py: containing functions using the previous classifier and features to study the symmetry of textures in a lesion's image.
combined_classifier.py: containing functions using only shape features, only textures features or both of them to train classifiers and be able to know which one is the best according to expert diagnose in the PH² Dataset.
Those classifiers are trained according to the
ShapeAndTextureScores.csvfiles contained in the
datarepository. The final models are saved as
Note : The code used to create the
patchesDataSet is given in the
patches_dataset_creator.py file. The
utils.py file contains the utilities
Each code script has an :
example() function at the beginning aiming at presenting its functionalities. This function is run
as a default
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