Zobrazeno 1 - 10
of 2 420
pro vyhledávání: '"PRINCE, A. L."'
Autor:
Rivas, Carlos A., Zhang, Jinwei, Wei, Shuwen, Remedios, Samuel W., Carass, Aaron, Prince, Jerry L.
Unique identification of multiple sclerosis (MS) white matter lesions (WMLs) is important to help characterize MS progression. WMLs are routinely identified from magnetic resonance images (MRIs) but the resultant total lesion load does not correlate
Externí odkaz:
http://arxiv.org/abs/2410.09639
Autor:
Zhang, Jinwei, Zuo, Lianrui, Liu, Yihao, Remedios, Samuel, Landman, Bennett A., Prince, Jerry L., Carass, Aaron
Automatic magnetic resonance (MR) image processing pipelines are widely used to study people with multiple sclerosis (PwMS), encompassing tasks such as lesion segmentation and brain parcellation. However, the presence of lesion often complicates thes
Externí odkaz:
http://arxiv.org/abs/2410.05027
Autor:
Feng, Anqi, Bian, Zhangxing, Dewey, Blake E., Colinco, Alexa Gail, Zhuo, Jiachen, Prince, Jerry L.
Accurate segmentation of thalamic nuclei is important for better understanding brain function and improving disease treatment. Traditional segmentation methods often rely on a single T1-weighted image, which has limited contrast in the thalamus. In t
Externí odkaz:
http://arxiv.org/abs/2409.06897
Autor:
Hays, Savannah P., Remedios, Samuel W., Zuo, Lianrui, Mowry, Ellen M., Newsome, Scott D., Calabresi, Peter A., Carass, Aaron, Dewey, Blake E., Prince, Jerry L.
Magnetic resonance (MR) imaging is commonly used in the clinical setting to non-invasively monitor the body. There exists a large variability in MR imaging due to differences in scanner hardware, software, and protocol design. Ideally, a processing a
Externí odkaz:
http://arxiv.org/abs/2408.16562
Deformable image registration establishes non-linear spatial correspondences between fixed and moving images. Deep learning-based deformable registration methods have been widely studied in recent years due to their speed advantage over traditional a
Externí odkaz:
http://arxiv.org/abs/2407.10209
Autor:
Hays, Savannah P., Zuo, Lianrui, Liu, Yihao, Feng, Anqi, Zhuo, Jiachen, Prince, Jerry L., Carass, Aaron
Deep learning (DL) has led to significant improvements in medical image synthesis, enabling advanced image-to-image translation to generate synthetic images. However, DL methods face challenges such as domain shift and high demands for training data,
Externí odkaz:
http://arxiv.org/abs/2402.12288
Autor:
Liu, Xiaofeng, Xing, Fangxu, Zhuo, Jiachen, Stone, Maureen, Prince, Jerry L., Fakhri, Georges El, Woo, Jonghye
Understanding the relationship between tongue motion patterns during speech and their resulting speech acoustic outcomes -- i.e., articulatory-acoustic relation -- is of great importance in assessing speech quality and developing innovative treatment
Externí odkaz:
http://arxiv.org/abs/2402.06984
Autor:
Bian, Zhangxing, Alshareef, Ahmed, Wei, Shuwen, Chen, Junyu, Wang, Yuli, Woo, Jonghye, Pham, Dzung L., Zhuo, Jiachen, Carass, Aaron, Prince, Jerry L.
Magnetic Resonance Imaging with tagging (tMRI) has long been utilized for quantifying tissue motion and strain during deformation. However, a phenomenon known as tag fading, a gradual decrease in tag visibility over time, often complicates post-proce
Externí odkaz:
http://arxiv.org/abs/2401.17571
Autor:
Lee, Ho Hin, Saunders, Adam M., Kim, Michael E., Remedios, Samuel W., Remedios, Lucas W., Tang, Yucheng, Yang, Qi, Yu, Xin, Bao, Shunxing, Cho, Chloe, Mawn, Louise A., Rex, Tonia S., Schey, Kevin L., Dewey, Blake E., Spraggins, Jeffrey M., Prince, Jerry L., Huo, Yuankai, Landman, Bennett A.
Publikováno v:
J. Med. Imag. 11(6), 064004 (2024)
Purpose: Eye morphology varies significantly across the population, especially for the orbit and optic nerve. These variations limit the feasibility and robustness of generalizing population-wise features of eye organs to an unbiased spatial referenc
Externí odkaz:
http://arxiv.org/abs/2401.03060
Anisotropic low-resolution (LR) magnetic resonance (MR) images are fast to obtain but hinder automated processing. We propose to use denoising diffusion probabilistic models (DDPMs) to super-resolve these 2D-acquired LR MR slices. This paper introduc
Externí odkaz:
http://arxiv.org/abs/2312.04385