S 2 C-DeLeNet: A parameter transfer based segmentation-classification integration for detecting skin cancer lesions from dermoscopic images

Dermoscopic images ideally depict pigmentation attributes on the skin surface which is highly regarded in the medical community for detection of skin abnormality, disease or even cancer. The identification of such abnormality, however, requires trained eyes and accurate detection necessitates the pr...

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Veröffentlicht in:	Computers in biology and medicine 2022-11, Vol.150, p.106148, Article 106148
Hauptverfasser:	Alam, Md Jahin, Mohammad, Mir Sayeed, Hossain, Md Adnan Faisal, Showmik, Ishtiaque Ahmed, Raihan, Munshi Sanowar, Ahmed, Shahed, Mahmud, Talha Ibn
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Cancer Classification Coders Datasets Deep learning Dermatology Dermoscopy - methods Experimentation Feature extraction Feature maps Humans Image classification Image processing Image Processing, Computer-Assisted - methods Image segmentation Lesions Machine learning Medical imaging Neural networks Neural Networks, Computer Parameters Pigmentation Skin Skin - diagnostic imaging Skin cancer Skin diseases Skin Neoplasms - diagnostic imaging Tactics
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