Modified Topological Image Preprocessing for Skin Lesion Classifications
This work addresses skin lesion classification for medical diagnosis, but it appears incremental as it modifies an existing preprocessing method.
The paper tackled skin lesion classification by proposing a modified Topological Data Analysis model for image preprocessing, which improved performance when tested on the HAM10000 dataset using Deep Convolutional Neural Networks and Vision Transformers.
This paper proposes a modified Topological Data Analysis model for skin images preprocessing and enhancements. The skin lesion dataset HAM10000 used with the intention of identifying the important objects in relevant regions of the images. In order to evaluate both the original dataset and the preprocessed dataset, Deep Convolutional Neural Network and Vision Transformer models were utilized to train both models. After training, the experimental results demonstrate that the images preprocessed using the Modified Topological Data Analysis consistently perform better.