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To calculate the Dice Similarity score of Skin legion images by extracting masks. This task deals with object segmentation and segmentation evaluation.

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Afreen89/Image-Segmentation-and-Detection

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Image-Segmentation-and-Detection

Task 1: Object Segmentation

For each skin lesion image, I have applied Gaussian filter with Ostu threshold and then morphological filter (dilation_ with contour using OpenCV to automatically segment lesion object such as:

b

Task 2: Segmentation Evaluation

The task is to calculate the Dice Similarity (DS) Score of skin lesion dataset where M is the segmented lesion mask from Task 1 and M is the ground truth provided in the dataset here.

The equation to calculate DS score is:

Screenshot 2023-02-03 132440

Results

To get the object segmentation, run automated_legion_detector.py and for DS score, run the dice_similarity_score.py with the dataset. The mean DS score is 0.8 with std. dev of 0.812 which is relatively better considering the data was not completely clean.

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To calculate the Dice Similarity score of Skin legion images by extracting masks. This task deals with object segmentation and segmentation evaluation.

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