img
img
A Comparison of Automated Segmentation and Manual Tracing for Quantifying Lateral Ventricle Volumes Using MR Imaging     
Yazarlar (8)
Niyazi Acer
Türkiye
Dr. Öğr. Üyesi Burcu KAMAŞAK ARPAÇAY Dr. Öğr. Üyesi Burcu KAMAŞAK ARPAÇAY
Kırşehir Ahi Evran Üniversitesi, Türkiye
Burak Oğuzhan Karapınar
Türkiye
Esra Akkuş Yetkin
Funda İpekten
Serap Baştepe Gray
Levent Değirmencioğlu
Türkiye
Ahmet Turan Ilıca
Türkiye
Devamını Göster
Özet
Objective: Ventricular volume measurements have been proposed as a useful biomarker for several neurological diseases.
The goal of this study was to compare the performance of 3 fully-automated tools, volBrain (http://volbrain.upv.es), ALVIN
(Automatic Lateral Ventricle Delineation) (https://sites.google.com/site/mrilateralventricle/), and MRICloud (http://mricloud.org), with expert hand tracing to quantify lateral ventricle (LV) volume using magnetic resonance images.
Materials and Methods: The sample comprised 24 healthy subjects (age: 25.1±5.7 years, all male). Volumes derived from
each automated measurement were compared to hand tracing results performed by 2 specialists to assess the percent volume
difference using the intraclass correlation coefficient (ICC), concordance correlation coefficient (CCC), Dice index value, and
Bland-Altman analysis.
Results: The ICC agreement of the Manual_1 and Manual_2 was very good (0.979), and there was no statistically significant
difference (p>0.001). The volume difference of all methods was similar. The CCC with MRICloud and ALVIN was higher than
that of volBrain. Bland-Altman plots indicated that the 3 automated methods demonstrated acceptable agreement.
Conclusion: Compared with hand tracing, the LV volumes generated by MRICloud were more accurate than those of
volBrain and ALVIN. LV volume values can provide valuable data related to the volumetric dependencies of the anatomical
structures in various clinical conditions that can now be easily obtained using automated tools.
Anahtar Kelimeler
ALVIN | lateral ventricle | manual tracing | MRICloud | volBrain
Makale Türü Özgün Makale
Makale Alt Türü ESCI dergilerinde yayımlanan tam makale
Dergi Adı Erciyes Medical Journal
Dergi ISSN 2149-2247
Dergi Tarandığı Indeksler emerging sources citation index
Makale Dili İngilizce
Basım Tarihi 01-2022
Cilt No 44
Sayı 2
Sayfalar 148 / 155
Doi Numarası 10.14744/etd.2021.73920
Makale Linki http://dx.doi.org/10.14744/etd.2021.73920