Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Schmidt Adam"'
Purpose: Intraoperative ultrasound (US) can enhance real-time visualization in transoral robotic surgery. The surgeon creates a mental map with a pre-operative scan. Then, a surgical assistant performs freehand US scanning during the surgery while th
Externí odkaz:
http://arxiv.org/abs/2412.07741
Purpose: Tissue tracking is critical for downstream tasks in robot-assisted surgery. The Sparse Efficient Neural Depth and Deformation (SENDD) model has previously demonstrated accurate and real-time sparse point tracking, but struggled with occlusio
Externí odkaz:
http://arxiv.org/abs/2410.19996
The Segment Anything Model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each frame and large computational cost limit its usage in robotically assi
Externí odkaz:
http://arxiv.org/abs/2403.08003
Finding point-level correspondences is a fundamental problem in ultrasound (US), since it can enable US landmark tracking for intraoperative image guidance in different surgeries, including head and neck. Most existing US tracking methods, e.g., thos
Externí odkaz:
http://arxiv.org/abs/2403.04969
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 26, Iss 1, Pp 63-79 (2016)
The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on
Externí odkaz:
https://doaj.org/article/e43d7facaeeb43ab9afafef088514030
As computer vision algorithms increase in capability, their applications in clinical systems will become more pervasive. These applications include: diagnostics, such as colonoscopy and bronchoscopy; guiding biopsies, minimally invasive interventions
Externí odkaz:
http://arxiv.org/abs/2310.11475
Quantifying performance of methods for tracking and mapping tissue in endoscopic environments is essential for enabling image guidance and automation of medical interventions and surgery. Datasets developed so far either use rigid environments, visib
Externí odkaz:
http://arxiv.org/abs/2309.16782
Autor:
Kennedy, Eamonn, Vadlamani, Shashank, Lindsey, Hannah M, Peterson, Kelly S, OConnor, Kristen Dams, Murray, Kenton, Agarwal, Ronak, Amiri, Houshang H, Andersen, Raeda K, Babikian, Talin, Baron, David A, Bigler, Erin D, Caeyenberghs, Karen, Delano-Wood, Lisa, Disner, Seth G, Dobryakova, Ekaterina, Eapen, Blessen C, Edelstein, Rachel M, Esopenko, Carrie, Genova, Helen M, Geuze, Elbert, Goodrich-Hunsaker, Naomi J, Grafman, Jordan, Haberg, Asta K, Hodges, Cooper B, Hoskinson, Kristen R, Hovenden, Elizabeth S, Irimia, Andrei, Jahanshad, Neda, Jha, Ruchira M, Keleher, Finian, Kenney, Kimbra, Koerte, Inga K, Liebel, Spencer W, Livny, Abigail, Lovstad, Marianne, Martindale, Sarah L, Max, Jeffrey E, Mayer, Andrew R, Meier, Timothy B, Menefee, Deleene S, Mohamed, Abdalla Z, Mondello, Stefania, Monti, Martin M, Morey, Rajendra A, Newcombe, Virginia, Newsome, Mary R, Olsen, Alexander, Pastorek, Nicholas J, Pugh, Mary Jo, Razi, Adeel, Resch, Jacob E, Rowland, Jared A, Russell, Kelly, Ryan, Nicholas P, Scheibel, Randall S, Schmidt, Adam T, Spitz, Gershon, Stephens, Jaclyn A, Tal, Assaf, Talbert, Leah D, Tartaglia, Maria Carmela, Taylor, Brian A, Thomopoulos, Sophia I, Troyanskaya, Maya, Valera, Eve M, van der Horn, Harm Jan, Van Horn, John D, Verma, Ragini, Wade, Benjamin SC, Walker, Willian SC, Ware, Ashley L, Werner Jr, J Kent, Yeates, Keith Owen, Zafonte, Ross D, Zeineh, Michael M, Zielinski, Brandon, Thompson, Paul M, Hillary, Frank G, Tate, David F, Wilde, Elisabeth A, Dennis, Emily L
An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which
Externí odkaz:
http://arxiv.org/abs/2309.04607
Deformable tracking and real-time estimation of 3D tissue motion is essential to enable automation and image guidance applications in robotically assisted surgery. Our model, Sparse Efficient Neural Depth and Deformation (SENDD), extends prior 2D tra
Externí odkaz:
http://arxiv.org/abs/2305.06477
Autor:
Kolbe-Alexander, Tracy, Gardiner, Paul A., Banchoff, Ann, Schmidt, Adam, Covey-Hansen, Melinda, King, Abby C.
Publikováno v:
Journal of Physical Activity & Health; Nov2024, Vol. 21 Issue 11, p1132-1141, 10p