| Summary: | Skin lesions can pose serious health problems if left undetected and untreated. There are detection methods such as excisional biopsy as well as dermoscopy. However, there has been a demand of automating and aiding doctors with their diagnosis through Artificial Intelligence.
The aim of this project is to evaluate the effectiveness of a Deep Learning model, U-NET, in identifying and segmenting the skin lesions from the ISIC 2017 Challenge Dataset.
The evaluation consists of testing the U-NET model’s predicted segmentation accuracy with respect to different image and lesion types.
Through this project, it can be concluded that the U-NET is effective in producing accurate segmentations of skin lesions.
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