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http://hdl.handle.net/10609/127688
Title: | Classificació del Melanoma mitjançant visualització artificial |
Author: | Casellas La Rosa, Pol |
Tutor: | Torre Gallart, Jordi de la |
Abstract: | It is called cancer in the set of diseases in which an uncontrolled process is observed in cell division in ANY part of the body. Today, cancer is one of the diseases with the highest mortality rate. More specifically, skin cancer is the most common type of cancer among the human population. Melanoma is the deadliest form, causing 75% of deaths from epithelial cancer. Despite the high mortality rate, as in other cancers, a rapid detection pot will lead to greater effectiveness of the treatment. Currently, the Assessment of Skin Diagnosis Diagnosis by Dermatologists has improved markedly thanks to dermatoscopy. However, it could significantly improve the accuracy of diagnostics using image classification algorithms. The image analysis tools that automate the diagnosis of melanoma have a great potential to improve the accuracy of the diagnosis of dermatologists and contribute to a rapid detection of melanoma by increasing, in this way, the probability of cure of the melanoma to millions of people. Throughout this project Patient Image Sets are used in order to determine the existence or not of melanoma using Image Classification algorithms. |
Keywords: | deep learning image classification melanoma |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 3-Jan-2021 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Trabajos finales de carrera, trabajos de investigación, etc. |
Files in This Item:
File | Description | Size | Format | |
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pcasellaslTFM0121memòria.pdf | Memòria del TFM | 2,18 MB | Adobe PDF | View/Open |
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