Predicting Medical Images Using Convolutional Neural Network

A tétel rövid nézete
dc.contributor.advisorTerdik, György
dc.contributor.authorLantang, Oktavian Abraham
dc.contributor.departmentInformatikai tudományok doktori iskolahu
dc.date.accessioned2022-01-26T07:02:48Z
dc.date.available2022-01-26T07:02:48Z
dc.date.created2022hu_HU
dc.date.defended2022-06-22T10:00:00Z
dc.description.abstractCancer is one of the non-contagious diseases that causes the most significant number of human deaths. The time it takes for cancer cells to be identified in a patient’s body significantly impacts how easily they can be treated. An automatic screening method using computer-aided diagnostic (CAD) is one way of early can- cer detection. This dissertation proposes several models that can be adopted as automatic screening methods. The first model is a convolutional-based single neural network built by adopting the Visual Geometry Group (VGG) module. The second model is an ensemble model based on a voting system built by combining three single networks from scratch by adopting three well-known mod- ules: VGG, Inception, and Residual Network modules. The last model is an ensemble model based on interconnected networks. Un- like the previous ensemble model, this model does not use a voting method in decision making but trains all three networks in an ex- tensive linked network to make a single final decision. Furthermore, the success of each model, also the benefits and drawbacks of it are presented.hu_HU
dc.description.correctorLB
dc.format.extent19hu_HU
dc.identifier.urihttp://hdl.handle.net/2437/328164
dc.language.isoenhu_HU
dc.subjectConvolutional Neural Networkhu_HU
dc.subjectCancer Detection
dc.subject.disciplineInformatikai tudományokhu
dc.subject.sciencefieldMűszaki tudományokhu
dc.titlePredicting Medical Images Using Convolutional Neural Networkhu_HU
dc.title.translatedPredicting Medical Images Using Convolutional Neural Networkhu_HU
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