Abstract
In this paper, we introduce a method for estimating patient-specific reference bony shape models for planning of reconstructive surgery for patients with acquired craniomaxillofacial (CMF) trauma. We propose an automatic bony shape estimation framework using pre-traumatic portrait photographs and post-traumatic head computed tomography (CT) scans. A 3D facial surface is first reconstructed from the patient’s pre-traumatic photographs. An initial estimation of the patient’s normal bony shape is then obtained with the reconstructed facial surface via sparse representation using a dictionary of paired facial and bony surfaces of normal subjects. We further refine the bony shape model by deforming the initial bony shape model to the post-traumatic 3D CT bony model, regularized by a statistical shape model built from a database of normal subjects. Experimental results show that our method is capable of effectively recovering the patient’s normal facial bony shape in regions with defects, allowing CMF surgical planning to be performed precisely for a wider range of defects caused by trauma.
Original language | English (US) |
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Pages (from-to) | 327-335 |
Number of pages | 9 |
Journal | Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention |
Volume | 11768 |
DOIs | |
State | Published - Oct 2019 |
Keywords
- Adaptive-focus deformable shape model (AFDSM)
- Craniomaxillofacial (CMF)
- Facial bone estimation
- Simulation
- Sparse representation
- Surgical planning
- Three-dimensional facial reconstruction
- Trauma
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science