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5 Oct 2021
On October 5, 2021, a business meeting was held between representatives of the EPAM Systems IT Company Denis Grinev and Sergey Garashchuk with the Rector of the State University “Odessa Polytechnic” Gennadii Alexandrovich Oborskiy.
17 Sept 2021
International Summer School "Augmented Reality and Tourism"
15 July 2021
We invite Master students to participate in the program 2ouble Degree - double degree program with the Slovak Republic
CLASSIFICATION OF SKIN LESIONS USING MULTI-TASK DEEP NEURAL NETWORKS
Skin cancer is the most prevalent type of cancer disease. The most of skin cancer deaths are caused by melanoma, despite being the least common skin cancer. Early and accurate detection and treatment is the best healing, however detection of this type of malignancy in the early stages is not obvious. Data-driven solutions for malignant melanomas detection can make treatment more effective. Convolutional neural networks have been successfully applied in different areas of computer vision, also in the classification of cancer types and stages. But in most cases, images are not enough to reach robust and accurate classification. Such metadata as sex, age, nationality, etc. could also be applied inside the models. In this paper, we propose an end-to-end method for the classification of melanoma stage using convolutional neural networks from an RGB photo and persons' metadata. Also, we provide a method of semi-supervised segmentation of the region of melanoma appearance. From the experimental results, the proposed method demonstrates stable results and learns good general features. The main advantage of this method is that it increases generalization and reduces variance by using an ensemble of the networks, pretrained on a large dataset, and fine-tuned on the target dataset. This method reaches ROC-AUC of 0.93 on 10982 unique unseen images.
Dmitry V. Spodarets
( firstname.lastname@example.org )
Eugene M. Khvedchenya
( email@example.com )
Philip O. Marchenko
, PhD Student
( firstname.lastname@example.org )
Tymchenko, Borys I.
, PhD Student
( email@example.com )
computer vision; convolutional neural networks; multi-task learning; skin cancer; image classification; image segmentation
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Received after revision 17.09.2020
Vol. 3 № 3, 2020
24 Oct 2021
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