SKIN LESION DETECTION, ANALYSIS AND CLASSIFICATION USING AI
Prof. My Abdelouahed SABRI
Computer-Aided Diagnosis systems have been widely applied in medical image classification. They use the same process as the Content-Based Information Retrieval (CBIR); the offline phase which consists of creating a classification model and the inline phase to predict or classify unknown images using the elaborated classification model. The classification model is elaborated based on extracted features from the training dataset and evaluated on the validation dataset. Features used are generally based on shape, color, and/or texture information. Features extraction step can be avoided using deep learning methods but remains less efficient when dealing with small datasets or high-resolution images. To better understand the image classification process, it would be good to start from the beginning. Going through the CBIR, towards the development of powerful models for the classification of medical images using Machine Learning algorithms. Our examples of applications will be based on the classification of skin cancer images from the well-known dataset used in the ISIC2017 challenge.
To be developed
References- Youssef Filali, Hasnae El Khoukhi, My Abdelouahed Sabri, Ali Yahyaouy and Abdellah Aarab. "New and Efficient Features for Skin Lesion Classification based on Skeletonization". Journal of Computer Science. DOI: 10.3844/jcssp.2019.1225.1236. Septembre 2019, Volume 15, Issue 9. pp 1225.1236. - Youssef Filali, My Abdelouahed Sabri and Abdellah Aarab. "An Improved Segmentation Approach for Skin Lesion Classification". Statistics, Optimization & Information Computing. DOI: 10.19139/soic.v7i2.533. May 2019, Volume 7, Numéro 2, pp 456-467. - Youssef Filali, My Abdelouahed Sabri and Abdellah Aarab, "Improving skin cancer classification based on features fusion and selection". The 1st international conference on Embedded Systems and Artificial Intelligence (ESAI'19). May 02-03, 2019 | Fez, Morocco - Y. Filali, H. El Khoukhi, M. A. Sabri, A. Yahyaouy and A. Aarab, "Texture Classification of skin lesion using convolutional neural network," 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS), April 03-04, Fez, Morocco, 2019, pp. 1-5. doi: 10.1109/WITS.2019.8723791 - Youssef Filali; Assia Ennouni; My Abdelouahed Sabri; Abdellah Aarab. "A study of lesion skin segmentation, features selection and classification approaches," 2018 International Conference on Intelligent Systems and Computer Vision (ISCV). Pages: 1-4. ISBN: 978-1-5386-4396-9. DOI: 10.1109/ISACV.2018.8354069. 2-4 April 2018. Fez, Morocco. - Youssef Filali; Assia Ennouni; My Abdelouahed Sabri; Abdellah Aarab. “Multiscale approach for skin lesion analysis and classification”. 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP). ISBN: 978-1-5386-0551-6. DOI: 10.1109/ATSIP.2017.8075545. 22-24 May 2017. Fez, Morocco. - Assia Ennouni; Youssef Filali; My Abdelouahed Sabri; Abdellah Aarab. “A review on image mining”. 2017 Intelligent Systems and Computer Vision (ISCV). pp. 1-7. Print on Demand(PoD) ISBN: 978-1-5090-4063-6. Electronic ISBN: 978-1-5090-4062-9. DOI: 10.1109/ISACV.2017.8054916. 17-19 April 2017. Fez, Morocco