Layer-Aware iOCT Volume Rendering for Retinal Surgery
| dc.contributor.author | Weiss, Jakob | en_US |
| dc.contributor.author | Eck, Ulrich | en_US |
| dc.contributor.author | Nasseri, Muhamad Ali | en_US |
| dc.contributor.author | Maier, Mathias | en_US |
| dc.contributor.author | Eslami, Abouzar | en_US |
| dc.contributor.author | Navab, Nassir | en_US |
| dc.contributor.editor | Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia | en_US |
| dc.date.accessioned | 2019-09-03T13:49:09Z | |
| dc.date.available | 2019-09-03T13:49:09Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Retinal microsurgery is one of the most challenging types of surgery, yet in practice, intraoperative digital assistance is rare. The introduction of fast, microscope integrated Optical Coherence Tomography (iOCT) has enabled intraoperative imaging of subsurface structures. However, effective intraoperative visualization of this data poses a challenging problem both in terms of performance and engineering as well as for creating easily interpretable visualizations of this data. Most existing research focuses on visualization of diagnostic OCT data where imaging quality is higher and processing times are not an issue. We introduce a perceptually linear color map for a separated encoding of tissue reflectivity and positional information as chrominance and luminance. Based on this color mapping, we propose a Direct Volume Rendering (DVR) method that aids structure perception. To aid subretinal injection tasks, we introduce a novel Layer-Adjusted Maximum Intensity Projection (LA-MIP), correcting for the natural curvature of the retinal tissue. Expert feedback suggests our methods are preferred over baseline methods. Further research is needed to confirm the benefits of our approach in routine clinical applications. | en_US |
| dc.description.sectionheaders | Digital Pathology, Surgery, and Anatomical Education | |
| dc.description.seriesinformation | Eurographics Workshop on Visual Computing for Biology and Medicine | |
| dc.identifier.doi | 10.2312/vcbm.20191239 | |
| dc.identifier.isbn | 978-3-03868-081-9 | |
| dc.identifier.issn | 2070-5786 | |
| dc.identifier.pages | 123-127 | |
| dc.identifier.uri | https://doi.org/10.2312/vcbm.20191239 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/vcbm20191239 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Human | |
| dc.subject | centered computing | |
| dc.subject | Scientific visualization | |
| dc.subject | Computing methodologies | |
| dc.subject | Perception | |
| dc.title | Layer-Aware iOCT Volume Rendering for Retinal Surgery | en_US |