Article ; Online: Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art.
Computers in biology and medicine
2024 Volume 169, Page(s) 107929
Abstract: In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position ... ...
| Abstract | In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position and type of instruments is of great interest. Current work involves both spatial and temporal information, with the idea that predicting the movement of surgical tools over time may improve the quality of the final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify and characterize datasets used for method development and evaluation and quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images and videos. The paper focuses on methods that work purely visually, without markers of any kind attached to the instruments, considering both single-frame semantic and instance segmentation approaches, as well as those that incorporate temporal information. The publications analyzed were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were "instrument segmentation", "instrument tracking", "surgical tool segmentation", and "surgical tool tracking", resulting in a total of 741 articles published between 01/2015 and 07/2023, of which 123 were included using systematic selection criteria. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing the available potential for future developments. |
|---|---|
| MeSH term(s) | Endoscopy ; Minimally Invasive Surgical Procedures ; Robotic Surgical Procedures/methods ; Surgery, Computer-Assisted/methods ; Surgical Instruments ; Image Processing, Computer-Assisted/methods |
| Language | English |
| Publishing date | 2024-01-04 |
| Publishing country | United States |
| Document type | Journal Article ; Review |
| ZDB-ID | 127557-4 |
| ISSN | 1879-0534 ; 0010-4825 |
| ISSN (online) | 1879-0534 |
| ISSN | 0010-4825 |
| DOI | 10.1016/j.compbiomed.2024.107929 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
Full text online
More links
Kategorien
In stock of ZB MED Cologne/Königswinter
| Zs.A 653: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG) |
Order via subito
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.