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Original Articles

Automatic skin tumour border detection for digital dermoscopy using a new digital image analysis scheme

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Pages 177-183 | Accepted 12 May 2010, Published online: 23 May 2016

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Ranjita Rout & Priyadarsan Parida. (2020) A novel method for melanocytic skin lesion extraction and analysis. Journal of Discrete Mathematical Sciences and Cryptography 23:2, pages 461-473.
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Sarmad Maqsood & Robertas Damaševičius. (2023) Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare. Neural Networks 160, pages 238-258.
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Evgin Goceri. (2023) Evaluation of denoising techniques to remove speckle and Gaussian noise from dermoscopy images. Computers in Biology and Medicine 152, pages 106474.
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Yali Nie, Paolo Sommella, Marco Carratù, Mattias O’Nils & Jan Lundgren. (2022) A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss. Diagnostics 13:1, pages 72.
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Homayoun Rastegar & Davar Giveki. (2022) Designing a new deep convolutional neural network for skin lesion recognition. Multimedia Tools and Applications.
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Farhat Afza, Muhammad Sharif, Mamta Mittal, Muhammad Attique Khan & D. Jude Hemanth. (2022) A hierarchical three-step superpixels and deep learning framework for skin lesion classification. Methods 202, pages 88-102.
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Muhammad Almas Anjum, Javaria Amin, Muhammad Sharif, Habib Ullah Khan, Muhammad Sheraz Arshad Malik & Seifedine Kadry. (2020) Deep Semantic Segmentation and Multi-Class Skin Lesion Classification Based on Convolutional Neural Network. IEEE Access 8, pages 129668-129678.
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Tanzila Saba, Muhammad Attique Khan, Amjad Rehman & Souad Larabi Marie-Sainte. (2019) Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction. Journal of Medical Systems 43:9.
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Abder-Rahman Ali, Jingpeng Li, Sally Jane O'Shea, Guang Yang, Thomas Trappenberg & Xujiong Ye. (2019) A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images. A Deep Learning Based Approach to Skin Lesion Border Extraction With a Novel Edge Detector in Dermoscopy Images.
Lavinia Ferrante di Ruffano, Yemisi Takwoingi, Jacqueline Dinnes, Naomi Chuchu, Susan E Bayliss, Clare Davenport, Rubeta N Matin, Kathie Godfrey, Colette O'Sullivan, Abha Gulati, Sue Ann Chan, Alana Durack, Susan O'Connell, Matthew D Gardiner, Jeffrey Bamber, Jonathan J Deeks & Hywel C Williams. (2018) Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults. Cochrane Database of Systematic Reviews 2018:12.
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Muhammad Nasir, Muhammad Attique Khan, Muhammad Sharif, Ikram Ullah Lali, Tanzila Saba & Tassawar Iqbal. (2018) An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach. Microscopy Research and Technique 81:6, pages 528-543.
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Jorge J. Suárez-Cuenca, Amara Tilve, Ricardo López, Gonzalo Ferro, Javier Quiles & Miguel Souto. (2017) Integrating CAD modules in a PACS environment using a wide computing infrastructure. International Journal of Computer Assisted Radiology and Surgery 12:4, pages 657-667.
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Xiao-Feng Mei, Feng-Ying Xie & Zhi-Guo Jiang. (2016) Uneven illumination removal based on fully convolutional network for dermoscopy images. Uneven illumination removal based on fully convolutional network for dermoscopy images.
Alexandra Nasonova, Andrey Nasonov, Andrey Krylov, Ivan Pechenko, Alexey Umnov & Natalia Makhneva. 2014. Image Analysis and Recognition. Image Analysis and Recognition 159 166 .
Konstantin Korotkov & Rafael Garcia. (2012) Computerized analysis of pigmented skin lesions: A review. Artificial Intelligence in Medicine 56:2, pages 69-90.
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Qaisar Abbas, M.E. Celebi & Irene Fondón García. (2011) Hair removal methods: A comparative study for dermoscopy images. Biomedical Signal Processing and Control 6:4, pages 395-404.
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