Title Područja primjene umjetne inteligencije u radiografiji
Title (english) APPLICATION AREAS OF ARTIFICIAL INTELLIGENCE IN RADIOGRAPHY
Author Ivana Križić
Mentor Frane Mihanović (mentor)
Committee member Frane Mihanović (član povjerenstva)
Committee member Ljubica Žunić (predsjednik povjerenstva)
Committee member Tatjana Matijaš (član povjerenstva)
Granter University of Split (University Department of Health Studies) Split
Defense date and country 2019-09-02, Croatia
Scientific / art field, discipline and subdiscipline BIOMEDICINE AND HEALTHCARE Clinical Medical Sciences
Abstract U radu je obrađena tema umjetne inteligencije i njezina primjena danas u radiologiji, radiografiji i drugim područjima. U svijetu velikih podataka i poplave informacija sustavi koji primjenjuju umjetnu inteligenciju postaju sve značajniji. U radu su opisane i različite metode kojima se ostvaruje umjetna inteligencija. One uključuju strojno učenje, umjetne neuronske mreže, duboko učenje. Kroz rad su prikazani primjeri uporabe sustava temeljenih na umjetnoj inteligenciji. Ovim diplomskim radom prikazana su dosadašnja znanja, istraživanja i porast publiciranja primjene umjetne inteligencije u radiografiji. Sustavi umjetne inteligencije morali bi biti usmjereni na čovjeka i temeljiti se na obvezi upotrebe sustava u službi općeg dobra, s ciljem poboljšanja ljudske dobrobiti i slobode, poštujući zakone, prva i etičke norme. Umjetna inteligencija uključuje procese rasuđivanja, znanja, automatiziranog planiranja, učenja, obrade, percepcije, manipulacije podacima, stoga je nedvojbeno primjenu pronašla i u radiografiji. Pregledana je literatura i identificirani su članci za primjenu umjetne inteligencije u područjima radiografije poglavito mamografije, ultrazvuka, primjene u Computed Aided Detection (CAD), CT-a, MR-a te u drugim poljima gdje se koriste dijagnostički radiološki modaliteti oslikavanja. Jedno od najperspektivnijih područja inovacija gdje je zabilježen značajan rast u publiciranju u zdravstvu je primjena umjetne inteligencije (UI), prvenstveno u radiologiji.
Abstract (english) One of the most promising areas of health innovation is the application of artificial intelligence (AI), primarily in radiology for medical imaging. This thesis provides basic definitions of terms “machine learning” „deep learning“ and analyses the integration of AI into radiology. Publications on AI have drastically increased in last five years. In this paper we deal with the topic of artificial intelligence and its application in radiology, radiography and other fields. In the world of large data and flood of information, systems that apply artificial intelligence become more and more important. Different methods of artificial intelligence are described. They include machine learning, artificial neural networks, deep learning. Artificial intelligence systems should be oriented to mankind in the service of the general good, improving human well-being, respecting laws and eithic norms. Artificial intelligence involves processes of reasoning, knowledge, automated planning, learning, processing, perception, manipulation of data, so it has undoubtedly found its place in radiography. The literature has been reviewed and articles have been identified for the application of artificial intelligence in areas of x-rays, especially mammography, ultrasound, application to Computed Aided Detection (CAD), CT, MRI and other fields where diagnostic radiological modalities of imaging are used. One of the most promising areas of innovation in healthcare is the use of artificial intelligence (UI), primarily in radiology.
Keywords
Umjetna inteligencija
neuronske mreže
radiologija
radiografija
duboko učenje
strojno učenje
radiomics
precizna medicina
radioterapija
medicinske slike
baze podataka (ključne riječi unio urednik)
Keywords (english)
Artificial intelligence
neural networks
radiology
radiography
deep learning
machine learning
radiomics
precision medicine
radiotherapy
medical images
databases (ključne riječi unio urednik)
Language croatian
URN:NBN urn:nbn:hr:176:685044
Study programme Title: Radiologic Technology (university/graduate) Study programme type: university Study level: graduate Academic / professional title: magistar/magistra radiološke tehnologije (magistar/magistra radiološke tehnologije)
Type of resource Text
File origin Born digital
Access conditions Open access
Terms of use
Repository Repository of the University Department for Health Studies, University of Split
Created on 2020-06-23 09:15:56