Multiscale Morphological Reconstruction for Hair Removal in Dermoscopy Images

    November 2018 in “ Modern Applied Science ”
    C. F. Ocampo Blandón, E. Restrepo-Parra, Juan Rojas, Felipe Jaramillo
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    🚨 The study is somewhat relevant as it involves hair removal, but it focuses on image processing for medical imaging rather than biological aspects of hair or hair loss.
    TLDR The method accurately detects and removes hair from skin images to improve melanoma diagnosis.
    The paper "Multiscale Morphological Reconstruction for Hair Removal in Dermoscopy Images" from 2018 proposed a method for detecting and removing hair from dermoscopy images, which can distort the diagnosis of melanoma. The method used a convolution of the image with a kernel from the first derivative of the Gaussian function and replaced the hairs using a multiscale morphological reconstruction. A refining stage was also integrated to maintain the quality of the patterns on the lesion. The method was tested on 36 dermoscopy images, which included a total of 586 hairs. The results showed sensitivity and specificity performance measurements of 94.14% and 99.89%, respectively, indicating a high level of accuracy in detecting and removing hair from the images.
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