An Integrated Framework of Skin Lesion Detection and Recognition through Saliency Method and Optimal Deep Neural Network Feature Selection
Published in Neural Computing and Applications (Springer), 2019
Authors:
M. Attique Khan, Tallha Akram, Muhammad Sharif, Kashif Javed, Muhammad Rashid, Syed Ahmad Chan Bukhari
This work presents an integrated framework for skin lesion detection and recognition by combining saliency-based segmentation with optimal deep feature selection. The proposed method improves classification performance by focusing on the most discriminative regions and features extracted from dermoscopic images.
Contributions 📃
- A framework for automatic skin lesion detection and classification.
- Use of saliency-based segmentation to focus on relevant lesion regions.
- Extraction of deep features from pretrained CNN models.
- Optimal feature selection to improve classification accuracy.
- Evaluation on dermoscopic image datasets with improved performance.
📖 Citation (BibTeX)
@article{khan2020integrated,
title = {An Integrated Framework of Skin Lesion Detection and Recognition through Saliency Method and Optimal Deep Neural Network Feature Selection},
author = {Khan, M. Attique and Akram, Tallha and Sharif, Muhammad and Javed, Kashif and Rashid, Muhammad and Bukhari, Syed Ahmad Chan},
journal = {Neural Computing and Applications},
volume = {32},
number = {20},
pages = {15929--15948},
year = {2020},
publisher = {Springer},
doi = {10.1007/s00521-019-04514-0}
}