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Thesis topic proposal
 
László Madácsy
Development of computer database and application of machine learning algorithms to assist the real time differentiation between adenomatous and hyperplastic subcentrim

THESIS TOPIC PROPOSAL

Institute: University of Szeged
theoretical medicine
Theoretical Medicine Doctoral School

Thesis supervisor: László Madácsy
Location of studies (in Hungarian): Endokapszula Magánorvosi Centrum Székesfehérvár
Abbreviation of location of studies: ENDOK


Description of the research topic:

The prediction of histology of polyps during colonoscopy can support the resect and discard strategy. The use of recent classification needs expertise and routine. A computer algorithm can be capable to predict the histology based on preprocessed high-resolution images or BASIC classification descriptors. The aim of the current study is to develop a cloud-based deep learning algorithm to predict the polyp histology on high-resolution images made with different virtual chromoendoscopic technique.

Required language skills: english
Number of students who can be accepted: 1

Deadline for application: 2019-12-31


2019. IX. 13.
ODT ülés
Az ODT következő ülésére 2019. november 22-én 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).

 
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