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undergraduate thesis
Segmentacija i klasifikacija stanica u slikama s mikroskopa
2023. urn:nbn:hr:200:426900
Lendvaj, Mihael
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

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Lendvaj, M. (2023). Segmentacija i klasifikacija stanica u slikama s mikroskopa (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:426900

Lendvaj, Mihael. "Segmentacija i klasifikacija stanica u slikama s mikroskopa." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:426900

Lendvaj, Mihael. "Segmentacija i klasifikacija stanica u slikama s mikroskopa." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:426900

Lendvaj, M. (2023). 'Segmentacija i klasifikacija stanica u slikama s mikroskopa', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 05 January 2025, https://urn.nsk.hr/urn:nbn:hr:200:426900

Lendvaj M. Segmentacija i klasifikacija stanica u slikama s mikroskopa [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2023 [cited 2025 January 05] Available at: https://urn.nsk.hr/urn:nbn:hr:200:426900

M. Lendvaj, "Segmentacija i klasifikacija stanica u slikama s mikroskopa", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:200:426900

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Metadata
TitleSegmentacija i klasifikacija stanica u slikama s mikroskopa
Title (english)Segmentation and classification of cells in microscope images
AuthorMihael Lendvaj
MentorHrvoje Leventić (mentor)
Committee memberTomislav Galba (predsjednik povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2023-09-22, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Program Engineering
Abstract
Postupak segmentacije i klasifikacije stanica u uzorcima neizostavan je postupak pri otkrivanju mnogih bolesti i analize raznih uzoraka u mnogim istraživanjima. Razvoj računala i sve veći broj otkrića na području tehničkih znanosti omogućio je kroz povijest razvitak raznih metoda analize uzoraka različitih tjelesnih tekućina. U ovom radu opisao se proces brojanja stanica pomoću mikroskopa i hemocitometra, te način korištenja hemocitometra. Pokazalo se kako su brzina i točnost bitni parametri kod analize uzoraka. Bavilo se analizom slike, te mogućnostima segmentacije i klasifikacije, opisalo koliko je priprema podataka važna pri strojnom učenju. Na posljetku se sve to znanje i istraživanje spojio u kreiranje YOLO modela koji prepoznaje stanice na novim slikama u realnom vremenu i broji ih, iscrtava i označava, te prikazuje.
Abstract (english)
The process of segmentation and classification of cells in samples is an indispensable procedure in the detection of many diseases and the analysis of various samples in many researches. The development of computers and the increasing number of discoveries in the field of technical sciences have brought us throughout the history of developing various methods of different body fluids sample analasys. In this paper, I described the process of counting cells using a microscope and a hemocytometer, and how to use the hemocytometer. I studied how speed and accuracy are important parameters when analyzing samples. I dealt with image analysis, segmentation and classification possibilities, described how important data preparation is to us in machine learning. In the end, I combined all this knowledge and research to create a YOLO model that recognizes cells in new images in real time and counts them, plots and labels them, and displays them.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:426900
Study programmeTitle: Undergraduate University Study Programme in Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-10-13 10:27:27