Zobrazeno 1 - 10
of 45 159
pro vyhledávání: '"Oğuz, A"'
Autor:
Li, Hao, Oguz, Baris, Arenas, Gabriel, Yao, Xing, Wang, Jiacheng, Pouch, Alison, Byram, Brett, Schwartz, Nadav, Oguz, Ipek
Placenta volume measured from 3D ultrasound (3DUS) images is an important tool for tracking the growth trajectory and is associated with pregnancy outcomes. Manual segmentation is the gold standard, but it is time-consuming and subjective. Although f
Externí odkaz:
http://arxiv.org/abs/2408.05372
We collect and discuss various results on an important family of knots and links called Turk's head knots and links $Th (p,q)$. In the mathematical literature, they also appear under different names such as rosette knots and links or weaving knots an
Externí odkaz:
http://arxiv.org/abs/2409.20106
Low-dose computed tomography (LDCT) lower potential risks linked to radiation exposure while relying on advanced denoising algorithms to maintain diagnostic quality in reconstructed images. The reigning paradigm in LDCT denoising is based on neural n
Externí odkaz:
http://arxiv.org/abs/2409.13094
This article introduces a novel heuristic for Task and Motion Planning (TAMP) named Interpretable Responsibility Sharing (IRS), which enhances planning efficiency in domestic robots by leveraging human-constructed environments and inherent biases. Ut
Externí odkaz:
http://arxiv.org/abs/2409.05586
We use molecular dynamics to show that plastic slip is a crucial component of the transformation mechanism of a square-to-triangular structural transition. The latter is a stylized analog of many other reconstructive phase transitions. To justify our
Externí odkaz:
http://arxiv.org/abs/2409.04066
Markov Junior is a probabilistic programming language used for procedural content generation across various domains. However, its reliance on manually crafted and tuned probabilistic rule sets, also called grammars, presents a significant bottleneck,
Externí odkaz:
http://arxiv.org/abs/2408.05959
Autor:
Li, Hao, Liu, Han, von Busch, Heinrich, Grimm, Robert, Huisman, Henkjan, Tong, Angela, Winkel, David, Penzkofer, Tobias, Shabunin, Ivan, Choi, Moon Hyung, Yang, Qingsong, Szolar, Dieter, Shea, Steven, Coakley, Fergus, Harisinghani, Mukesh, Oguz, Ipek, Comaniciu, Dorin, Kamen, Ali, Lou, Bin
Publikováno v:
Radiology: Artificial Intelligence 2024;6(5):e230521
Our hypothesis is that UDA using diffusion-weighted images, generated with a unified model, offers a promising and reliable strategy for enhancing the performance of supervised learning models in multi-site prostate lesion detection, especially when
Externí odkaz:
http://arxiv.org/abs/2408.04777
Autor:
Li, Hao, Oguz, Baris, Arenas, Gabriel, Yao, Xing, Wang, Jiacheng, Pouch, Alison, Byram, Brett, Schwartz, Nadav, Oguz, Ipek
Placenta volume measurement from 3D ultrasound images is critical for predicting pregnancy outcomes, and manual annotation is the gold standard. However, such manual annotation is expensive and time-consuming. Automated segmentation algorithms can of
Externí odkaz:
http://arxiv.org/abs/2407.08020
This study presents a novel mechanical metallic reflector array to guide wireless signals to the point of interest, thereby enhancing received signal quality. Comprised of numerous individual units, this device, which acts as a linear Fresnel reflect
Externí odkaz:
http://arxiv.org/abs/2407.19179
We propose a novel framework for retinal feature point alignment, designed for learning cross-modality features to enhance matching and registration across multi-modality retinal images. Our model draws on the success of previous learning-based featu
Externí odkaz:
http://arxiv.org/abs/2407.18362