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Spinal pain relief procedures with the assistance of the MRI‐updated statistical shape model
Author(s) -
Alimohamadi Gilakjan Samaneh,
Majedi Hossein,
Makki Abadi Bahador,
Ahmadian Alireza
Publication year - 2020
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.2085
Subject(s) - computer science , imaging phantom , real time mri , medicine , radiology , artificial intelligence , magnetic resonance imaging , computer vision
Background Updating the statistical shape model (SSM) used in image guidance systems for the treatment of back pain using pre‐op computed tomography (CT) and intra‐op ultrasound (US) is challenging due to the scarce availability of pre‐op images and the low resolution of the two imaging modalities. Methods A new approach is proposed here to update SSMs based on the sparse representation of the preoperative MRI images of patients as well as CT images, followed by displaying the injection needle and 3D tracking view of the patients' spine. Results The statistical analysis shows that updating the SSM using the patients' available MRI images (in more than 95% of the cases) instead of CT images (in less than 5%) will help maintain the required accuracy of needle injection based on the evaluation of injection in different parts of the phantom. Conclusion The results show that using the proposed model helps reduce the dosage and processing time significantly while maintaining the precision required for the pain procedures.