Algorithmic Integration and Quantification of Endoscopic and 3D TEE Images in Mitral Valve Surgery

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dc.contributor.authorIvantsits, Matthiasen_US
dc.contributor.authorHuellebrand, Markusen_US
dc.contributor.authorWalczak, Larsen_US
dc.contributor.authorWelz, Jurien_US
dc.contributor.authorGreve, Dustinen_US
dc.contributor.authorWamala, Isaacen_US
dc.contributor.authorSuendermann, Simonen_US
dc.contributor.authorKempfert, Jörgen_US
dc.contributor.authorFalk, Volkmaren_US
dc.contributor.authorHennemuth, Anjaen_US
dc.contributor.editorGarrison, Lauraen_US
dc.contributor.editorJönsson, Danielen_US
dc.date.accessioned2024-09-17T06:06:49Z
dc.date.available2024-09-17T06:06:49Z
dc.date.issued2024
dc.description.abstractMinimally invasive surgery is the state-of-the-art approach for repairing the mitral valve, which controls the blood flow into the left heart chamber. The surgeons rely on camera and sensor technologies to support visualization, navigation, and measurement. As patients are connected to the cardio-pulmonary bypass, the anatomy is severely deformed by the altered pressure conditions. We developed a technique that combines stereo-endoscopic video with three-dimensional transesophageal echocardiography (3D TEE) to improve anatomic visualization and measurement accuracy during mitral valve repairs. Our methodology includes stereo camera calibration, image segmentation, and 3D model reconstruction. Anatomical landmarks are used to align the imaging modalities. This approach allows the visualization of pre-operatively determined mitral valve properties, e.g., overlaying heat maps in stereo endoscopic data. Our validation results showed high precision and accuracy within an error range of 0.5 ± 0.1 mm. The effectiveness of the heatmap visualization in complex prolapse cases varied. Integrating stereoscopic and 3D TEE promises greater precision in mitral valve repairs. In the future, this approach can also be used to visualize local tissue properties or the optimal locations of implants.en_US
dc.description.sectionheadersMedical Visualization and Surgical Assistance
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20241185
dc.identifier.isbn978-3-03868-244-8
dc.identifier.issn2070-5786
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/vcbm.20241185
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/vcbm20241185
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Image segmentation; Matching; Reconstruction; Interest point and salient region detections; Shape inference
dc.subjectComputing methodologies → Image segmentation
dc.subjectMatching
dc.subjectReconstruction
dc.subjectInterest point and salient region detections
dc.subjectShape inference
dc.titleAlgorithmic Integration and Quantification of Endoscopic and 3D TEE Images in Mitral Valve Surgeryen_US
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VCBM 2024: Eurographics Workshop on Visual Computing for Biology and Medicine