Hip joint and age relationship in Thai population by image processing technique

Bone age is a critical factor in personal identification, with the hip joint-encompassing the acetabulum and femoral head-commonly used in age estimation. Age assessments rely on factors such as bone porosity and morphological characteristics. These are currently conducted by experts and their conclusions can vary. The logistical challenge of transporting physical bones complicates the process. The increasing use of image processing techniques in the medical field provides a more efficient and convenient alternative. This study used image processing methods to analyze area ratios and percent porosity of the acetabulum and femoral head, with a statistical evaluation of the relationship between these parameters and age at a 90% confidence level (α=0.10). The dataset comprised images from 167 skeletons including 59 females aged 30 to 88 and 108 males aged 28 to 97. The analysis revealed a significant relationship between percent porosity and age in males, both in the acetabulum and femoral head, with <i>P</i>-values below 0.10 but this relationship was not observed in females. A significant relationship between area ratio and age was found in the femoral head region for both genders but not in the acetabulum. The accuracy and comparability of the results were enhanced by applying a standardized image processing protocol.

Authors

Institutions

Publication Details

Journal
Anatomy & Cell Biology
Published
2025-02-07
DOI
https://doi.org/10.5115/acb.24.235
Primary Topic
Hip disorders and treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hip joint and age relationship in Thai population by image processing technique

Nipon Theera‐Umpon, Pasuk Mahakkanukrauh, Apichat Sinthubua, Sukon Prasitwattanaseree et al.
Anatomy & Cell Biology
Hip disorders and treatments
article

Hip joint and age relationship in Thai population by image processing technique

Nipon Theera‐Umpon, Pasuk Mahakkanukrauh, Apichat Sinthubua, Sukon Prasitwattanaseree, Parkpoom Jarupoom, Supachard Krudtong
article en

Abstract

Bone age is a critical factor in personal identification, with the hip joint-encompassing the acetabulum and femoral head-commonly used in age estimation. Age assessments rely on factors such as bone porosity and morphological characteristics. These are currently conducted by experts and their conclusions can vary. The logistical challenge of transporting physical bones complicates the process. The increasing use of image processing techniques in the medical field provides a more efficient and convenient alternative. This study used image processing methods to analyze area ratios and percent porosity of the acetabulum and femoral head, with a statistical evaluation of the relationship between these parameters and age at a 90% confidence level (α=0.10). The dataset comprised images from 167 skeletons including 59 females aged 30 to 88 and 108 males aged 28 to 97. The analysis revealed a significant relationship between percent porosity and age in males, both in the acetabulum and femoral head, with <i>P</i>-values below 0.10 but this relationship was not observed in females. A significant relationship between area ratio and age was found in the femoral head region for both genders but not in the acetabulum. The accuracy and comparability of the results were enhanced by applying a standardized image processing protocol.

Anatomy & Cell BiologyVol. 58(1)
Chiang Mai University (TH), Rajamangala University of Technology Lanna (TH)
Openalex Percentile: Top 96%
Hip disorders and treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.