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pro vyhledávání: '"Teixeira, Brian"'
Despite recent developments in CT planning that enabled automation in patient positioning, time-consuming scout scans are still needed to compute dose profile and ensure the patient is properly positioned. In this paper, we present a novel method whi
Externí odkaz:
http://arxiv.org/abs/2309.15750
Autor:
Bekhtaoui, Walid, Sa, Ruhan, Teixeira, Brian, Singh, Vivek, Kirchberg, Klaus, Chang, Yao-jen, Kapoor, Ankur
Point cloud based methods have produced promising results in areas such as 3D object detection in autonomous driving. However, most of the recent point cloud work focuses on single depth sensor data, whereas less work has been done on indoor monitori
Externí odkaz:
http://arxiv.org/abs/2005.04258
Autor:
Liu, Siqi, Georgescu, Bogdan, Xu, Zhoubing, Yoo, Youngjin, Chabin, Guillaume, Chaganti, Shikha, Grbic, Sasa, Piat, Sebastian, Teixeira, Brian, Balachandran, Abishek, RS, Vishwanath, Re, Thomas, Comaniciu, Dorin
The Coronavirus Disease (COVID-19) has affected 1.8 million people and resulted in more than 110,000 deaths as of April 12, 2020. Several studies have shown that tomographic patterns seen on chest Computed Tomography (CT), such as ground-glass opacit
Externí odkaz:
http://arxiv.org/abs/2005.01903
Landmark localization is a challenging problem in computer vision with a multitude of applications. Recent deep learning based methods have shown improved results by regressing likelihood maps instead of regressing the coordinates directly. However,
Externí odkaz:
http://arxiv.org/abs/1908.01070
Autor:
Balashova, Elena, Wang, Jiangping, Singh, Vivek, Georgescu, Bogdan, Teixeira, Brian, Kapoor, Ankur
Automatic delineation and measurement of main organs such as liver is one of the critical steps for assessment of hepatic diseases, planning and postoperative or treatment follow-up. However, addressing this problem typically requires performing comp
Externí odkaz:
http://arxiv.org/abs/1904.00073
Autor:
Balashova, Elena, Singh, Vivek, Wang, Jiangping, Teixeira, Brian, Chen, Terrence, Funkhouser, Thomas
We propose a new procedure to guide training of a data-driven shape generative model using a structure-aware loss function. Complex 3D shapes often can be summarized using a coarsely defined structure which is consistent and robust across variety of
Externí odkaz:
http://arxiv.org/abs/1808.01427
Autor:
Teixeira, Brian, Singh, Vivek, Chen, Terrence, Ma, Kai, Tamersoy, Birgi, Wu, Yifan, Balashova, Elena, Comaniciu, Dorin
We present a novel framework that learns to predict human anatomy from body surface. Specifically, our approach generates a synthetic X-ray image of a person only from the person's surface geometry. Furthermore, the synthetic X-ray image is parametri
Externí odkaz:
http://arxiv.org/abs/1805.00553
Autor:
Teixeira, Carol, Teixeira, Brian
Publikováno v:
Perspectives: The Journal of the Canadian Gerontological Nursing Association; 2022, Vol. 43 Issue 2, p6-11, 6p
Autor:
Al-Zogbi L; Laboratory for Computational Sensing and Robotics, Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States., Singh V; Medical Imaging Technologies, Siemens Medical Solutions, Inc. USA, Princeton, NJ, United States., Teixeira B; Medical Imaging Technologies, Siemens Medical Solutions, Inc. USA, Princeton, NJ, United States., Ahuja A; Georgetown Day High School, WA, DC, United States., Bagherzadeh PS; Medical Imaging Technologies, Siemens Medical Solutions, Inc. USA, Princeton, NJ, United States., Kapoor A; Medical Imaging Technologies, Siemens Medical Solutions, Inc. USA, Princeton, NJ, United States., Saeidi H; Laboratory for Computational Sensing and Robotics, Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States., Fleiter T; R. Cowley Shock Trauma Center, Department of Diagnostic Radiology, School of Medicine, University of Maryland, Baltimore, MD, United States., Krieger A; Laboratory for Computational Sensing and Robotics, Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Publikováno v:
Frontiers in robotics and AI [Front Robot AI] 2021 May 25; Vol. 8, pp. 645756. Date of Electronic Publication: 2021 May 25 (Print Publication: 2021).