bibtype |
J -
Journal Article
|
ARLID |
0561214 |
utime |
20250310153149.0 |
mtime |
20220915235959.9 |
SCOPUS |
85133897966 |
WOS |
000828380000002 |
DOI |
10.1016/j.bspc.2022.103878 |
title
(primary) (eng) |
Videokymogram Analyzer Tool: Human-computer comparison |
specification |
page_count |
12 s. |
media_type |
P |
|
serial |
ARLID |
cav_un_epca*0344243 |
ISSN |
1746-8094 |
title
|
Biomedical Signal Processing and Control |
volume_id |
78 |
publisher |
|
|
keyword |
Image analysis |
keyword |
Videokymography |
keyword |
Vocal fold vibrations |
author
(primary) |
ARLID |
cav_un_auth*0293261 |
name1 |
Zita |
name2 |
Aleš |
institution |
UTIA-B |
full_dept (cz) |
Zpracování obrazové informace |
full_dept (eng) |
Department of Image Processing |
department (cz) |
ZOI |
department (eng) |
ZOI |
full_dept |
Department of Image Processing |
garant |
K |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0283562 |
name1 |
Novozámský |
name2 |
Adam |
institution |
UTIA-B |
full_dept (cz) |
Zpracování obrazové informace |
full_dept |
Department of Image Processing |
department (cz) |
ZOI |
department |
ZOI |
full_dept |
Department of Image Processing |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101238 |
name1 |
Zitová |
name2 |
Barbara |
institution |
UTIA-B |
full_dept (cz) |
Zpracování obrazové informace |
full_dept |
Department of Image Processing |
department (cz) |
ZOI |
department |
ZOI |
full_dept |
Department of Image Processing |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0108377 |
name1 |
Šorel |
name2 |
Michal |
institution |
UTIA-B |
full_dept (cz) |
Zpracování obrazové informace |
full_dept |
Department of Image Processing |
department (cz) |
ZOI |
department |
ZOI |
full_dept |
Department of Image Processing |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0293262 |
name1 |
Herbst |
name2 |
Ch. |
country |
CZ |
|
author
|
ARLID |
cav_un_auth*0322230 |
name1 |
Vydrová |
name2 |
J. |
country |
CZ |
|
author
|
ARLID |
cav_un_auth*0018322 |
name1 |
Švec |
name2 |
J. G. |
country |
CZ |
|
source |
|
source |
|
cas_special |
project |
project_id |
TA04010877 |
agency |
GA TA ČR |
country |
CZ |
ARLID |
cav_un_auth*0322186 |
|
project |
project_id |
TH04010422 |
agency |
GA TA ČR |
country |
CZ |
ARLID |
cav_un_auth*0385138 |
|
project |
project_id |
GA21-03921S |
agency |
GA ČR |
ARLID |
cav_un_auth*0412209 |
|
abstract
(eng) |
Videokymography (VKG) is a modern video recording technique used in laryngology and phoniatrics to examine vocal fold vibrations. To obtain quantitative information on the vocal fold vibration, VKG image analysis is needed but no software has yet been validated for this purpose. Here, we introduce a validated software tool that aids clinicians to evaluate diagnostically important vibration characteristics in VKG and other types of kymographic recordings. State-of-the-art methods for automated image evaluation were implemented and tested on a set of videokymograms with a wide range of vibratory characteristics, including healthy and pathologic voices. The automated image segmentation results were compared to manual segmentation results of six evaluators revealing average differences smaller than one pixel. Furthermore, the automatically categorized vibratory parameters precisely agreed with the average visual assessment in 84 and 91 percent of the cases for pathological and healthy patients, respectively. Based on these results, the newly developed software was found to be a valid, reliable automated tool for the quantification of vocal fold vibrations from VKG images, offering a number of novel features relevant for clinical practice. |
result_subspec |
WOS |
RIV |
JC |
FORD0 |
20000 |
FORD1 |
20200 |
FORD2 |
20206 |
reportyear |
2023 |
mrcbC52 |
2 R hod 4 4rh 4 20250310152704.1 4 20250310153149.0 |
inst_support |
RVO:67985556 |
permalink |
https://hdl.handle.net/11104/0333902 |
confidential |
S |
article_num |
103878 |
mrcbC86 |
n.a. Article Engineering Biomedical |
mrcbC91 |
C |
mrcbT16-e |
ENGINEERINGBIOMEDICAL |
mrcbT16-j |
0.697 |
mrcbT16-s |
1.071 |
mrcbT16-D |
Q3 |
mrcbT16-E |
Q2 |
arlyear |
2022 |
mrcbTft |
\nSoubory v repozitáři: zita-0561214.pdf |
mrcbU14 |
85133897966 SCOPUS |
mrcbU24 |
PUBMED |
mrcbU34 |
000828380000002 WOS |
mrcbU63 |
cav_un_epca*0344243 Biomedical Signal Processing and Control 1746-8094 1746-8108 Roč. 78 č. 1 2022 Elsevier |
|