Zobrazeno 1 - 10
of 11 614
pro vyhledávání: '"A. Nassir"'
Shape completion, a crucial task in 3D computer vision, involves predicting and filling the missing regions of scanned or partially observed objects. Current methods expect known pose or canonical coordinates and do not perform well under varying rot
Externí odkaz:
http://arxiv.org/abs/2412.00952
Autor:
Arikan, Demir, Zhang, Peiyao, Sommersperger, Michael, Dehghani, Shervin, Esfandiari, Mojtaba, Taylor, Russel H., Nasseri, M. Ali, Gehlbach, Peter, Navab, Nassir, Iordachita, Iulian
Exudative (wet) age-related macular degeneration (AMD) is a leading cause of vision loss in older adults, typically treated with intravitreal injections. Emerging therapies, such as subretinal injections of stem cells, gene therapy, small molecules o
Externí odkaz:
http://arxiv.org/abs/2411.18521
State-of-the-art novel view synthesis methods such as 3D Gaussian Splatting (3DGS) achieve remarkable visual quality. While 3DGS and its variants can be rendered efficiently using rasterization, many tasks require access to the underlying 3D surface,
Externí odkaz:
http://arxiv.org/abs/2411.16898
Autor:
Hu, Ming, Yuan, Kun, Shen, Yaling, Tang, Feilong, Xu, Xiaohao, Zhou, Lin, Li, Wei, Chen, Ying, Xu, Zhongxing, Peng, Zelin, Yan, Siyuan, Srivastav, Vinkle, Song, Diping, Li, Tianbin, Shi, Danli, Ye, Jin, Padoy, Nicolas, Navab, Nassir, He, Junjun, Ge, Zongyuan
Surgical practice involves complex visual interpretation, procedural skills, and advanced medical knowledge, making surgical vision-language pretraining (VLP) particularly challenging due to this complexity and the limited availability of annotated d
Externí odkaz:
http://arxiv.org/abs/2411.15421
Autor:
Arikan, Demir, Zhang, Peiyao, Sommersperger, Michael, Dehghani, Shervin, Esfandiari, Mojtaba, Taylor, Russel H., Nasseri, M. Ali, Gehlbach, Peter, Navab, Nassir, Iordachita, Iulian
Robotic platforms provide repeatable and precise tool positioning that significantly enhances retinal microsurgery. Integration of such systems with intraoperative optical coherence tomography (iOCT) enables image-guided robotic interventions, allowi
Externí odkaz:
http://arxiv.org/abs/2411.06557
Autor:
Bi, Yuan, Huang, Lucie, Clarenbach, Ricarda, Ghotbi, Reza, Karlas, Angelos, Navab, Nassir, Jiang, Zhongliang
Ultrasound (US) imaging is widely used in routine clinical practice due to its advantages of being radiation-free, cost-effective, and portable. However, the low reproducibility and quality of US images, combined with the scarcity of expert-level ann
Externí odkaz:
http://arxiv.org/abs/2411.04004
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