Image Analysis in Big Data Architecture using Artificial Intelligence - Tchagna Kouanou, Aurelle; Tchiotsop, Daniel; Tchinda, Rene
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In the medical field, data is increasingly growing and traditional methods cannot manage them efficiently. In the computational biomedical, the continuous challenges are management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of the data using machine learning and artificial intelligence techniques. It becomes very important to develop methods and/or architectures based on big data technologies for complete processing of biomedical images data. In this thesis, we propose a complete and…mehr

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Produktbeschreibung
In the medical field, data is increasingly growing and traditional methods cannot manage them efficiently. In the computational biomedical, the continuous challenges are management, analysis, and storage of the biomedical data. Nowadays, big data technology plays a significant role in the management, organization, and analysis of the data using machine learning and artificial intelligence techniques. It becomes very important to develop methods and/or architectures based on big data technologies for complete processing of biomedical images data. In this thesis, we propose a complete and optimal workflow based on big data technology and optimal algorithms drawn from literature to manage biomedical images. Compression step within the proposed optimal workflow will be considered as a study case implementing big data analysis technology. The proposed workflow implements an image compression algorithm for biomedical images, which is based on three main steps, orthogonal transform, vector quantization using machine learning and entropy encoding. The proposed algorithm allows us to develop appropriate and efficient methods to leverage a large number of images into the proposed workflow.
Autorenporträt
Tchagna Aurelle was born in 1990 in Dschang-Cameroon. He obtained a MS degree in Electronic in 2013 from University of Dschang, he graduated in Telecommunication engineering from SUP¿PTIC Yaounde in 2015. He obtained a PhD degree from the University of Dschang where his main items of research include Image processing, AI, Big Data, ML, DL and IoT.