Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans
Highlights • A new fully automatic femur segmentation method for CT images is proposed. • This novel segmentation method defines both the femoral external surface and the medullary canal. • The fast and automatic segmentation method is an important contribution for the development of surgical planni...
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| Published in: | Medical engineering & physics Vol. 38; no. 12; pp. 1474 - 1480 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
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01-12-2016
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| Abstract | Highlights • A new fully automatic femur segmentation method for CT images is proposed. • This novel segmentation method defines both the femoral external surface and the medullary canal. • The fast and automatic segmentation method is an important contribution for the development of surgical planning software efficient in terms of cost and time reduction. • High convergence was achieved for low and high resolution CT images. |
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| AbstractList | Highlights • A new fully automatic femur segmentation method for CT images is proposed. • This novel segmentation method defines both the femoral external surface and the medullary canal. • The fast and automatic segmentation method is an important contribution for the development of surgical planning software efficient in terms of cost and time reduction. • High convergence was achieved for low and high resolution CT images. Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is presented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral volume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) technique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1mm. For the low resolution image group the results are also accurate and the average error is less than 1.5mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is robust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis. •A new fully automatic femur segmentation method for CT images is proposed.•This novel segmentation method defines both the femoral external surface and the medullary canal.•The fast and automatic segmentation method is an important contribution for the development of surgical planning software efficient in terms of cost and time reduction.•High convergence was achieved for low and high resolution CT images. Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive knowledge on the techniques, segmentation should be fully automatic. In this paper a new fully automatic femur segmentation method for CT images is presented. This method is also able to define automatically the medullary canal and performs well even in low resolution CT scans. Fully automatic femoral segmentation was performed adapting a template mesh of the femoral volume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) technique based on the statistical shape model (SSM) and local appearance model (LAM) of the femur with a novel initialization method was used, to drive the template mesh deformation in order to fit the in-image femoral shape in a time effective approach. With the proposed method a 98% convergence rate was achieved. For high resolution CT images group the average error is less than 1mm. For the low resolution image group the results are also accurate and the average error is less than 1.5mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is robust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis. |
| Author | Verhegghe, Benedict Fernandes, Paulo R Folgado, João Almeida, Diogo F Audenaert, Emmanuel Ruben, Rui B De Beule, Matthieu |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27751655$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1302/0301-620X.81B1.8880 10.1109/34.232073 10.1145/37402.37422 10.1016/j.jbiomech.2011.10.038 10.1007/BF01427149 10.1145/361002.361007 10.5435/00124635-200511000-00005 10.1006/cviu.1995.1004 10.1007/s11548-013-0950-3 10.1111/j.2517-6161.1991.tb01825.x 10.1016/1049-9660(91)90036-O 10.1007/s11263-006-7934-5 |
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| Keywords | CT image Statistical shape model (SSM) Total hip arthroplasty Active shape model (ASM) 3D femur segmentation |
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| Snippet | Highlights • A new fully automatic femur segmentation method for CT images is proposed. • This novel segmentation method defines both the femoral external... •A new fully automatic femur segmentation method for CT images is proposed.•This novel segmentation method defines both the femoral external surface and the... Femur segmentation can be an important tool in orthopedic surgical planning. However, in order to overcome the need of an experienced user with extensive... |
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| SubjectTerms | 3D femur segmentation Active shape model (ASM) Automation CT image Femur - diagnostic imaging Humans Image Processing, Computer-Assisted Radiology Signal-To-Noise Ratio Statistical shape model (SSM) Tomography, X-Ray Computed Total hip arthroplasty |
| Title | Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scans |
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