Name
Abstract | ||
|---|---|---|
Portable X-ray radiographs are heavily used in the ICU for detecting significant or unexpected conditions requiring immediate changes in patient management. One concern for effective patient management relates to the ability to detect the proper positioning of tubes that have been inserted into the patient. These include, for example, endo-tracheal tubes (ET), feeding tubes (FT), naso-gastric tubes (NT), and other tubes. Proper tube positioning can help to ensure delivery or disposal of liquids and air/gases to and from the patient during a treatment procedure. Improper tube positioning can cause patient discomfort, render a treatment ineffective, or can even be life-threatening. However, because the poor image quality in portable AP X-ray images due to the variability in patients, apparatus positioning, and X-ray exposure, it is often difficult for clinicians to visually detect the position of tube tips. Thus, there is a need for detecting and identifying tube position and type to assist clinicians. The purpose of this paper is to present a computer-aided method for automated detection of tubes and identification of tube types. Use of this method may allow clinicians to detect the tube tips more easily and accurately, thus improving the quality of patient management in the ICU. |
Year | DOI | Venue |
|---|---|---|
2008 | null | BIOSIGNALS 2008: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING, VOL II |
Keywords | Field | DocType |
Gaussian filter,contrast-limited adaptive histogram equalization (CLAHE),hough transform,tube | Computer vision,Computer science,Radiography,Artificial intelligence | Conference |
Volume | Issue | ISSN |
2 | null | null |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||