Name
Abstract | ||
|---|---|---|
In medical endoscopy more and more surgeons record videos of their interventions in a long-term storage archive for later retrieval. In order to allow content-based search in such endoscopic video archives, the video data needs to be indexed first. However, even the very basic step of content-based indexing, namely content segmentation, is already very challenging due to the special characteristics of such video data. Therefore, we propose to use instrument classification to enable semantic segmentation of laparoscopic videos. In this paper, we evaluate the performance of such an instrument classification approach. Our results show satisfying performance for all instruments used in our evaluation. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CBMI.2015.7153616 | Content-Based Multimedia Indexing |
Keywords | Field | DocType |
image classification,image segmentation,indexing,medical image processing,surgery,video retrieval,content segmentation,content-based indexing,content-based search,instrument classification approach,laparoscopic videos,medical endoscopy,video data indexing | Computer vision,Information retrieval,Computer science,Segmentation,Support vector machine,Search engine indexing,Artificial intelligence,Vocabulary,Multimedia | Conference |
ISSN | Citations | PageRank |
1949-3983 | 6 | 0.50 |
References | Authors | |
14 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manfred Jurgen Primus | 1 | 15 | 2.15 |
| Klaus Schoeffmann | 2 | 509 | 63.01 |
| László Böszörményi | 3 | 485 | 66.44 |