Identification and measurement of cutaneous melanoma superficial spreading depth using microscopic hyperspectral imaging technology
Received:March 18, 2020  Revised:November 10, 2020  download
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Author NameAffiliationE-mail
WANG Jian-Sheng Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241 China 
6248954@qq.com 
LI Qing-Li Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241 China
Engineering Research Center of Nanophotonics & Advanced Instrument Ministry of Education East China Normal University Shanghai 200241 China 
qlli@cs.ecnu.edu.cn 
ZHOU Mei Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241 China 
 
SUN Li Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241 China 
 
HU Meng-Han Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241 China 
 
LU Yue Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Center of SHMEC for Space Information and GNSS Shanghai 200241 China 
 
CHU Jun-Hao Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China
Engineering Research Center of Nanophotonics & Advanced Instrument Ministry of Education East China Normal University Shanghai 200241 China 
 
Abstract:This paper presents an automatic approach for measurement of the superficial spreading depth of cutaneous melanomas based on microscopic hyperspectral imaging technology. To extract the skin granular layer, an edge detection method combined with kernel minimum noise fraction is proposed. Then least squares support vector machine based on characteristic spectrum supervision is used to identify malignant melanocytes. The measurement of tumor superficial spreading depth depends on the vertical distance from the skin granular layer to the deepest malignant melanocytes. Experimental results illustrate that the proposed method is possible to provide an effective reference for the diagnosis and treatment of cutaneous melanoma.
keywords:image processing  superficial spreading depth  machine learning  microscopic hyperspectral imaging
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