Real-time raman spectroscopy for non-invasive skin cancer detection - preliminary results

Author(s):  
Jianhua Zhao ◽  
Harvey Lui ◽  
David I. McLean ◽  
Haishan Zeng
2021 ◽  
Vol 118 (23) ◽  
pp. 230501
Author(s):  
H. Lindley-Hatcher ◽  
R. I. Stantchev ◽  
X. Chen ◽  
A. I. Hernandez-Serrano ◽  
J. Hardwicke ◽  
...  

2016 ◽  
Author(s):  
Xu Feng ◽  
Austin J. Moy ◽  
Mia K. Markey ◽  
Matthew C. Fox ◽  
Jason S. Reichenberg ◽  
...  

Author(s):  
Ivan A. Bratchenko ◽  
Dmitry N. Artemyev ◽  
Yulia A. Khristoforova ◽  
Lyudmila A. Bratchenko ◽  
Oleg O. Myakinin ◽  
...  

RSC Advances ◽  
2018 ◽  
Vol 8 (49) ◽  
pp. 28095-28130 ◽  
Author(s):  
Vigneswaran Narayanamurthy ◽  
P. Padmapriya ◽  
A. Noorasafrin ◽  
B. Pooja ◽  
K. Hema ◽  
...  

Recent advances in non-invasive techniques for skin cancer diagnosis.


2021 ◽  
Vol 40 ◽  
pp. 03044
Author(s):  
Shruti Kale ◽  
Reema Kharat ◽  
Sagarika Kalyankar ◽  
Sangita Chaudhari ◽  
Apurva Shinde

Skin Cancer is resulting from the growth of the harmful tumour of the melanocytes the rates are rising to another level. The medical business is advancing with the innovation of recent technologies; newer tending technology and treatment procedures are being developed. The early detection of skin cancer can help the chance of increase in its growth in other parts of body. In recent years, medical practitioners tend to use non invasive Computer aided system to detect the skin cancers in early phase of its spreading instead of relying on traditional skin biopsy methods. Convolution neural network model is proposed and used for early detection of the cancer, and it type. The proposed model could classify the dermoscopic images into correct type with accuracy 91.2%.


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