Výsledky vyhledávání - "Acar, Ayberk"

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An Effectiveness Study Across Baseline and Neural Network-based Force Estimation Methods on the da Vinci Research Kit Si System

Autor: Yang, Hao, Acar, Ayberk, Xu, Keshuai, Deguet, Anton, Kazanzides, Peter, Wu, Jie Ying

In this study, we further investigate the robustness and generalization ability of an neural network (NN) based force estimation method, using the da Vinci Research Kit Si (dVRK-Si). To evaluate our method's performance, we compare the force estimati

Externí odkaz: http://arxiv.org/abs/2405.07453

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MeshBrush: Painting the Anatomical Mesh with Neural Stylization for Endoscopy

Autor: Han, John J., Acar, Ayberk, Kavoussi, Nicholas, Wu, Jie Ying

Style transfer is a promising approach to close the sim-to-real gap in medical endoscopy. Rendering synthetic endoscopic videos by traversing pre-operative scans (such as MRI or CT) can generate structurally accurate simulations as well as ground tru

Externí odkaz: http://arxiv.org/abs/2404.02999

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Depth Anything in Medical Images: A Comparative Study

Autor: Han, John J., Acar, Ayberk, Henry, Callahan, Wu, Jie Ying

Monocular depth estimation (MDE) is a critical component of many medical tracking and mapping algorithms, particularly from endoscopic or laparoscopic video. However, because ground truth depth maps cannot be acquired from real patient data, supervis

Externí odkaz: http://arxiv.org/abs/2401.16600

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