Implementation of a tracking and segmentation algorithm of structures in laparoscopic surgery video

Naranjo Fraile, Aida (2019). Implementation of a tracking and segmentation algorithm of structures in laparoscopic surgery video. Thesis (Master thesis), E.T.S.I. Telecomunicación (UPM).

Description

Title: Implementation of a tracking and segmentation algorithm of structures in laparoscopic surgery video
Author/s:
  • Naranjo Fraile, Aida
Contributor/s:
  • Guzmán García, Carmen
Item Type: Thesis (Master thesis)
Masters title: Ingeniería Biomédica
Date: 2019
Subjects:
Freetext Keywords: Computer vision, tracking, laparoscopic surgery video.
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica y Bioingeniería
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Nowadays, laparoscopic surgery is one of the most used surgeries due to the minimal invasion to the patient (mainly because of the small incisions performed), which is why it is included in the group of Minimally Invasive Surgery (MIS). A thin tool with a video camera and a light at the end is used to obtain images from the tissues and organs of the patient. Said images are displayed in a monitor allowing the surgeon to see what is happening inside the body and perform the surgery accurately. This technique requires for surgeons to have a high-level training, for which new pedagogical approaches are being developed. One useful technology is the creation and application of surgical interactive videos for the learning processes of residents. There are several training platforms which uses interactive videos as part of their surgical training curriculum (WebSurg, surgical theater. . . ). However, there are not many authoring tools which allow for the creation of original contents by the teachers or content creators in charge of the residents' training. AMELIE is an authoring tool which provides teachers and content creators with the means for creating interactive videos. Its functionalities include, among others, the ability to show anatomical structures of importance for the understanding of a procedure. This is obtained by means of applying computer vision in those structures. The aim of this project is precisely to implement an improved segmentation and tracking algorithm based on artificial vision capable of recognizing any anatomical structure selected by the teachers or content creators interacting with the authoring tool in a laparoscopic video frame, and following its position during the rest of the selected frames. This information will lead to an improvement in the training processes of surgical residents. The developed algorithm is based on the extraction and matching of image features. It essentially finds important regions in each frame and compares them with the initial Region of Interest (ROI) selected by the user to find the new ROI. Those regions that are similar are recognized as the ROI of the image. After the implementation of this new tracking method, it has been compared to a previously used method in the AMELIE authoring tool, obtaining better results at tracking structures in laparoscopic videos, more concretely a 18,35% better taking into account the average F1 score of both algorithms. This new method improving the overall learning experience of surgeons.

More information

Item ID: 57501
DC Identifier: http://oa.upm.es/57501/
OAI Identifier: oai:oa.upm.es:57501
Deposited by: Biblioteca ETSI Telecomunicación
Deposited on: 13 Dec 2019 08:57
Last Modified: 13 Dec 2019 09:01
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