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Machine Learning Methods for Binary and Multiclass Classification of Melanoma Thickness From Dermoscopic Images

Machine Learning Methods for Binary and Multiclass Classification of Melanoma Thickness From Dermoscopic Images

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 Machine Learning Methods for Binary and Multiclass Classification of Melanoma Thickness From Dermoscopic Images

 Thickness of the melanoma is the most important factor associated with survival in patients with melanoma. It is most commonly reported as a measurement of depth given in millimeters (mm) and computed by means of pathological examination after a biopsy of the suspected lesion. In order to avoid the use of an invasive method in the estimation of the thickness of melanoma before surgery, we propose a computational image analysis system from dermoscopic images.


 


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  • Model: PROJ7170
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Monday 12 June, 2017.

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