Journal article
Automated bone landmarks prediction on the femur using anatomical deformation technique
Computer aided design, Vol.45(2), pp.505-510
02/2013
DOI: 10.1016/j.cad.2012.10.033
Abstract
Anatomical landmarks on bones play important roles in musculoskeletal simulations and surgical planning. This study develops an anatomically deformable model of the femur to predict bone landmarks automatically and quantifies its prediction accuracy. Forty-three angiographic computed tomography (CT) images of femurs were collected and 14 bone landmarks were manually marked on these images by experts. Surface mesh models of the femur were extracted from the CT images and combined with the bone landmark information to create an anatomical deformable model. The anatomical deformation technique developed in this study predicted bone landmarks automatically as the surface of a deformable model was matched to the surface of a given femur model. The prediction accuracy was quantified using the leave-one-out cross-validation method. The average prediction error for the 14 landmarks ranged from 2.80 to 5.93 mm. While the prediction accuracies of anterior and posterior cruciate ligaments and lateral epicondyle sites were high with averages (standard deviation) of 3.00 (±1.55), 2.80 (±1.76) and 2.97 (±1.87) mm, respectively, those of gluteus minimus, ligament of head of femur and piriformis sites were low with averages of 5.93 (±3.77), 4.89 (±3.49) and 4.87 (±2.70) mm, respectively. Accuracy can be expected to increase with the use of more population data as is the nature of a population-based statistical deformable model.
Details
- Title: Subtitle
- Automated bone landmarks prediction on the femur using anatomical deformation technique
- Creators
- Seung-Yeob Baek - School of Mechanical and Aerospace Engineering, Seoul National University, Seoul, South KoreaJoon-Ho Wang - Department of Orthopaedic Surgery, School of Medicine, Sungkyunkwan University, Samsung Medical Center, Seoul, South KoreaInsub Song - Department of Radiology, School of Medicine, Chung-Ang University, Seoul, South KoreaKunwoo Lee - School of Mechanical and Aerospace Engineering, Seoul National University, Seoul, South KoreaJehee Lee - School of Computer Science and Engineering, Seoul National University, Seoul, South KoreaSeungbum Koo - School of Mechanical Engineering, Chung-Ang University, Seoul, South Korea
- Resource Type
- Journal article
- Publication Details
- Computer aided design, Vol.45(2), pp.505-510
- DOI
- 10.1016/j.cad.2012.10.033
- ISSN
- 0010-4485
- eISSN
- 1879-2685
- Publisher
- Elsevier Ltd
- Grant note
- DOI: 10.13039/501100003725, name: National Research Foundation of Korea; DOI: 10.13039/501100004085, name: Ministry of Education, Science and Technology, award: 2012-0000787, 2012-0004102
- Language
- English
- Date published
- 02/2013
- Academic Unit
- Electrical and Computer Engineering; Industrial and Systems Engineering; Radiation Oncology
- Record Identifier
- 9984047730302771
Metrics
36 Record Views