Browsing by Author "Fernandes, Paulo R."
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- Automated femoral landmark extraction for optimal prosthesis placement in total hip arthroplastyPublication . Almeida, Diogo F. de; Ruben, Rui; Folgado, João; Fernandes, Paulo R.; Gamelas, João; Verhegghe, Benedict; Beule, Matthieu DeThe automated extraction of anatomical reference landmarks in the femoral volume may improve speed, precision, and accuracy of surgical procedures, such as total hip arthroplasty. These landmarks are often hard to achieve, even via surgical incision. In addition, it provides a presurgical guidance for prosthesis sizing and placement. This study presents an automated workflow for femoral orientation and landmark extraction from a 3D surface mesh. The extraction of parameters such as the femoral neck axis, the femoral middle diaphysis axis, both trochanters and the center of the femoral head will allow the surgeon to establish the correct position of bony cuts to restore leg length and femoral offset. The definition of the medullary canal endosteal wall is used to position the prosthesis' stem. Furthermore, prosthesis alignment and sizing methods were implemented to provide the surgeon with presurgical information about performance of each of the patient‐specific femur‐implant couplings. The workflow considers different commercially available hip stems and has the potential to help the preoperative planning of a total hip arthroplasty in an accurate, repeatable, and reliable way. The positional and orientation errors are significantly reduced, and therefore, the risk of implant failure and subsequent revision surgery are also reduced.
- Fully automatic segmentation of femurs with medullary canal definition in high and in low resolution CT scansPublication . Almeida, Diogo F.; Ruben, Rui; Folgado, João; Fernandes, Paulo R.; Audenaert, Emmanuel; Verhegghe, Benedict; De Beule, MatthieuFemur segmentation can be an important tool in orthopedic surgical planning. However, in order to over- come 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 pre- sented. 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 vol- ume to medical images. In order to achieve this, an adaptation of the active shape model (ASM) tech- nique 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 1 mm. For the low resolution image group the results are also accurate and the average error is less than 1.5 mm. The proposed segmentation pipeline is accurate, robust and completely user free. The method is ro- bust to patient orientation, image artifacts and poorly defined edges. The results excelled even in CT images with a significant slice thickness, i.e., above 5 mm. Medullary canal segmentation increases the geometric information that can be used in orthopedic surgical planning or in finite element analysis.