Automated melanoma detection. An algorithm inspired from human intelligence characterizing disordered pattern of melanocytic lesions improving a convolutional neural network - 18/07/24
, Arthur Cartel Foahom Gouabou, PhD a, Meryem Serdi, MS a, Jules Collenne, MS a, Rabah Iguernaissi, PhD a, Marie-Aleth Richard, MD c, Caroline Gaudy-Marqueste, MD, PhD b, c, Jean-Luc Damoiseaux, PhD a, Jean-Jacques Grob, MD, PhD b, c, Djamal Merad, PhD aKey words : computer assisted diagnosis, convolutional neural network, disorder, entropy, global cognitive analysis, handcrafted method, melanoma detection
| Prs Grob and Merad contributed equally to this article as senior authors. |
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| Funding source: This work was supported by ADEREM, DIAMELEX ANR, Canceropôle PACA |
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| Patient consent: Not applicable. |
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| IRB approval status: Not applicable. |
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| Data availability statement: The data set used is from a public data set ISIC (International Skin Imaging Collaboration) 2019, available at data. We adapted this public data set to develop our models with training and test steps, providing presented results. We can make public synthetic images from datageneration. |
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| X handle: Automated detection of melanoma’s disorder |
Vol 91 - N° 2
P. 350-352 - agosto 2024 Ritorno al numeroBenvenuto su EM|consulte, il riferimento dei professionisti della salute.
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