Zobrazeno 1 - 10
of 2 673
pro vyhledávání: '"Navab Nassir"'
Autor:
Jung, HyunJun, Li, Weihang, Wu, Shun-Cheng, Bittner, William, Brasch, Nikolas, Song, Jifei, Pérez-Pellitero, Eduardo, Zhang, Zhensong, Moreau, Arthur, Navab, Nassir, Busam, Benjamin
Traditionally, 3d indoor datasets have generally prioritized scale over ground-truth accuracy in order to obtain improved generalization. However, using these datasets to evaluate dense geometry tasks, such as depth rendering, can be problematic as t
Externí odkaz:
http://arxiv.org/abs/2410.22715
Autor:
Zhao, Zhihao, Faghihroohi, Shahrooz, Zhao, Yinzheng, Yang, Junjie, Zhong, Shipeng, Huang, Kai, Navab, Nassir, Li, Boyang, Nasseri, M. Ali
Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various eye diseases. Contemporary deep learning-based vascular segmentation models rival human accuracy but still f
Externí odkaz:
http://arxiv.org/abs/2410.21160
Autor:
Zhao, Zhihao, Yang, Junjie, Faghihroohi, Shahrooz, Zhao, Yinzheng, Zapp, Daniel, Huang, Kai, Navab, Nassir, Nasseri, M. Ali
The utilization of longitudinal datasets for glaucoma progression prediction offers a compelling approach to support early therapeutic interventions. Predominant methodologies in this domain have primarily focused on the direct prediction of glaucoma
Externí odkaz:
http://arxiv.org/abs/2410.21130
Autor:
Yeganeh, Yousef, Lazuardi, Rachmadio, Shamseddin, Amir, Dari, Emine, Thirani, Yash, Navab, Nassir, Farshad, Azade
Surgical data science (SDS) is a field that analyzes patient data before, during, and after surgery to improve surgical outcomes and skills. However, surgical data is scarce, heterogeneous, and complex, which limits the applicability of existing mach
Externí odkaz:
http://arxiv.org/abs/2410.17751
Autonomous vehicles demand detailed maps to maneuver reliably through traffic, which need to be kept up-to-date to ensure a safe operation. A promising way to adapt the maps to the ever-changing road-network is to use crowd-sourced data from a fleet
Externí odkaz:
http://arxiv.org/abs/2410.07780
Surgical video-language pretraining (VLP) faces unique challenges due to the knowledge domain gap and the scarcity of multi-modal data. This study aims to bridge the gap by addressing issues regarding textual information loss in surgical lecture vide
Externí odkaz:
http://arxiv.org/abs/2410.00263
Recent advances in generative models for medical imaging have shown promise in representing multiple modalities. However, the variability in modality availability across datasets limits the general applicability of the synthetic data they produce. To
Externí odkaz:
http://arxiv.org/abs/2409.13532
AI-based vascular segmentation is becoming increasingly common in enhancing the screening and treatment of ophthalmic diseases. Deep learning structures based on U-Net have achieved relatively good performance in vascular segmentation. However, small
Externí odkaz:
http://arxiv.org/abs/2410.02808
Autor:
Fehrentz, Maximilian, Azampour, Mohammad Farid, Dorent, Reuben, Rasheed, Hassan, Galvin, Colin, Golby, Alexandra, Wells, William M., Frisken, Sarah, Navab, Nassir, Haouchine, Nazim
We present in this paper a novel approach for 3D/2D intraoperative registration during neurosurgery via cross-modal inverse neural rendering. Our approach separates implicit neural representation into two components, handling anatomical structure pre
Externí odkaz:
http://arxiv.org/abs/2409.11983
Autor:
Dastan, Mine, Fiorentino, Michele, Walter, Elias D., Diegritz, Christian, Uva, Antonio E., Eck, Ulrich, Navab, Nassir
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics 2024
Mixed Reality (MR) is proven in the literature to support precise spatial dental drill positioning by superimposing 3D widgets. Despite this, the related knowledge about widget's visual design and interactive user feedback is still limited. Therefore
Externí odkaz:
http://arxiv.org/abs/2409.10258