Keyword search (4,163 papers available)

"Mohammad-Rahimi H" Authored Publications:

Title Authors PubMed ID
1 Reliability of Comprehensive Facial Soft Tissue Landmark Detection and Analysis Using Frontal View Photographs Hassanzadeh-Samani S; Pirayesh Z; Motie P; Ghorbanimehr MS; Farzan A; Mohammad-Rahimi H; Behnaz M; Motamedian SR; 40975629
ENCS
2 Deep learning for tooth identification and enumeration in panoramic radiographs Sadr S; Mohammad-Rahimi H; Ghorbanimehr MS; Rokhshad R; Abbasi Z; Soltani P; Moaddabi A; Shahab S; Rohban MH; 38169618
ENCS
3 A deep learning framework to scale linear facial measurements to actual size using horizontal visible iris diameter: a study on an Iranian population Pirayesh Z; Hassanzadeh-Samani S; Farzan A; Rohban MH; Ghorbanimehr MS; Mohammad-Rahimi H; Motamedian SR; 37612309
ENCS

 

Title:A deep learning framework to scale linear facial measurements to actual size using horizontal visible iris diameter: a study on an Iranian population
Authors:Pirayesh ZHassanzadeh-Samani SFarzan ARohban MHGhorbanimehr MSMohammad-Rahimi HMotamedian SR
Link:https://pubmed.ncbi.nlm.nih.gov/37612309/
DOI:10.1038/s41598-023-40839-6
Publication:Scientific reports
Keywords:
PMID:37612309 Category: Date Added:2023-08-24
Dept Affiliation: ENCS

Description:

Digital images allow for the objective evaluation of facial appearance and abnormalities as well as treatment outcomes and stability. With the advancement of technology, manual clinical measurements can be replaced with fully automatic photographic assessments. However, obtaining millimetric measurements on photographs does not provide clinicians with their actual value due to different image magnification ratios. A deep learning tool was developed to estimate linear measurements on images with unknown magnification using the iris diameter. A framework was designed to segment the eyes' iris and calculate the horizontal visible iris diameter (HVID) in pixels. A constant value of 12.2 mm was assigned as the HVID value in all the photographs. A vertical and a horizontal distance were measured in pixels on photographs of 94 subjects and were estimated in millimeters by calculating the magnification ratio using HVID. Manual measurement of the distances was conducted on the subjects and the actual and estimated amounts were compared using Bland-Altman analysis. The obtained error was calculated as mean absolute percentage error (MAPE) of 2.9% and 4.3% in horizontal and vertical measurements. Our study shows that due to the consistent size and narrow range of HVID values, the iris diameter can be used as a reliable scale to calibrate the magnification of the images to obtain precise measurements in further research.





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