Skin lesion segmentation based on preprocessing, thresholding and neural networks

Keywords

Jaccard index, Preprocessor, Artificial intelligence, Segmentation, Computer science

References

• Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC)Noel Codella, David A. Gutman, M. Emre Celebi — 2016
• Computer Vision Techniques for the Diagnosis of Skin CancerJacob Scharcanski, M. Emre Celebi — 2013
• Dermoscopy Image AnalysisM. Emre Celebi, Teresa Mendonca, Jorge S. Marques — 2015

Cited by

• An image-based segmentation recommender using crowdsourcing and transfer learning for skin lesion extractionAmira Soudani, Walid Barhoumi — 2019
• Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and ReductionTanzila Saba, Muhammad Attique Khan, Amjad Rehman — 2019
• IoMT Enabled Melanoma Detection Using Improved Region Growing Lesion Boundary ExtractionTanzila Saba, Rabia Javed, Mohd Shafry Mohd Rahim — 2022
• A novel hybrid meta-heuristic contrast stretching technique for improved skin lesion segmentationShairyar Malik, S. M. Riazul Islam, Tallha Akram — 2022
• A Hybrid Preprocessor DE-ABC for Efficient Skin-Lesion Segmentation with Improved ContrastShairyar Malik, Tallha Akram, Imran Ashraf — 2022
• Survey on Computational Techniques for Pigmented Skin Lesion SegmentationShubhasis Khanra, Maitreyee Kuila, Shibaprasad Patra — 2022
• Adaptive Thresholding Skin Lesion Segmentation with Gabor Filters and Principal Component AnalysisD. Thanh, N. N. Hien, V. B. Surya Prasath — 2020
• Skin Lesion Segmentation Based on Region-Edge Markov Random FieldOmran Salih, Serestina Viriri, A. Adegun — 2019

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