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Abstract: We describe a system for respiratory motion correction of MRI-derived roadmaps for use in X-ray guided cardiac catheterisation procedures. The technique uses a subject-specific affine motion model that is quickly constructed from a short pre-procedure MRI scan. We test a dynamic MRI sequence that acquires a small number of high resolution slices, rather than a single low resolution volume. Additionally, we use prior knowledge of the nature of cardiac respiratory motion by constraining the model to use only the dominant modes of motion. During the procedure the motion of the diaphragm is tracked in X-ray fluoroscopy images, allowing the roadmap to be updated using the motion model. X-ray image acquisition is cardiac gated. Validation is performed on four volunteer datasets and three patient datasets. The accuracy of the model in 3D was within 5mm in 97.6% of volunteer validations. For the patients, 2D accuracy was improved from 5 to 13mm before applying the model to 2–4mm afterwards. For the dynamic MRI sequence comparison, the highest errors were found when using the low resolution volume sequence with an unconstrained model. [Copyright &y& Elsevier]

B Background: b Use of augmented reality (AR) based image guidance systems (IGS) has been proposed as a method to improve anatomical orientation during laparoscopic liver surgery (LLS) with potential benefits for patients. In addition enhanced visualisation methods with the potential to improve mental integration between surgeons and AR environment will be presented. During surgery a 3D liver model was manually overlayed onto the laparoscopic screen (registration) to create an AR environment. [Extracted from the article]

B Background: b Use of augmented reality (AR) based image guidance systems (IGS) has been proposed as a method to improve anatomical orientation during laparoscopic liver surgery (LLS) with potential benefits for patients. In addition enhanced visualisation methods with the potential to improve mental integration between surgeons and AR environment will be presented. During surgery a 3D liver model was manually overlayed onto the laparoscopic screen (registration) to create an AR environment. [Extracted from the article]