diplomsko delo
Jan Rojc (Author), Tomaž Curk (Mentor)

Abstract

Endoskopija je medicinski postopek, ki omogoča neinvaziven vpogled v človeške notranje organe s pomočjo kamere. Endoskopske videoposnetke lahko računalniško obdelujemo v realnem času, kar kirurgom omogoča natančnejšo navigacijo med posegom ter sprejemanje informiranih odločitev na podlagi analiziranih podatkov. Pomembno vlogo pri zajemu podatkov iz videoposnetkov ima vizualno sledenje, ki je v endoskopiji še posebej zahtevno zaradi deformacij tkiva in okluzij. Na podatkovni množici Cholec80 smo testirali natančnost sledenja različnih algoritmov, implementiranih v knjižnici OpenCV. Razvili smo anotacijski program, ki smo ga uporabili za označevanje optimalnega sledenja izbranega dela tkiva v vsakem videoposnetku. Na koncu smo rezultate sledilnikov primerjali z anotacijami, da smo ocenili njihovo uspešnost ter določili najboljši sledilnik.

Keywords

vizualni sledilnik;optični tok;endoskopski videoposnetki;gibanje tkiva;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [J. Rojc]
UDC: 004:616-072.1(043.2)
COBISS: 165971715 Link will open in a new window
Views: 35
Downloads: 2
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Other data

Secondary language: English
Secondary title: Comparison of algorithms for visual tracking of tissue movement in endoscopic videos
Secondary abstract: Endoscopy is a medical procedure that provides a non-invasive view of a person's internal organs using a camera. Endoscopic videos can be processed in real time using computer vision methods, allowing surgeons to navigate more accurately during the procedure and make informed decisions based on the analysed data. Visual tracking plays an important role in capturing data from video, which is particularly challenging in endoscopy due to tissue deformations and occlusions. We tested the tracking accuracy of different algorithms implemented in the OpenCV library on the Cholec80 dataset. We developed an annotation software and used it to specify the optimal tracking of a selected tissue segment in each video. Finally, we compared the results of the trackers with the annotations to evaluate their performance and determine the best tracker.
Secondary keywords: visual tracker;optical flow;endoscopy;endoscopic videos;medicine;computer science;diploma;Endoskopija;Sledilni sistemi (tehnika);Videoposnetki;Medicina;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 38 str.
ID: 19912956