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pro vyhledávání: '"Zhang, Jinwei"'
Recent advances in multi-modal algorithms have driven and been driven by the increasing availability of large image-text datasets, leading to significant strides in various fields, including computational pathology. However, in most existing medical
Externí odkaz:
http://arxiv.org/abs/2406.06393
Autor:
Li, Chao, Zhang, Jinwei, Zhang, Hang, Li, Jiahao, Spincemaille, Pascal, Nguyen, Thanh D., Wang, Yi
Purpose: To develop a pipeline for motion artifact correction in mGRE and quantitative susceptibility mapping (QSM). Methods: Deep learning is integrated with autofocus to improve motion artifact suppression, which is applied QSM of patients with Par
Externí odkaz:
http://arxiv.org/abs/2405.16664
Background: Rim+ lesions in multiple sclerosis (MS), detectable via Quantitative Susceptibility Mapping (QSM), correlate with increased disability. Existing literature lacks quantitative analysis of these lesions. We introduce RimSet for quantitative
Externí odkaz:
http://arxiv.org/abs/2312.16835
Autor:
Zhang, Jinwei, Zuo, Lianrui, Dewey, Blake E., Remedios, Samuel W., Pham, Dzung L., Carass, Aaron, Prince, Jerry L.
Automatic multiple sclerosis (MS) lesion segmentation using multi-contrast magnetic resonance (MR) images provides improved efficiency and reproducibility compared to manual delineation. Current state-of-the-art automatic MS lesion segmentation metho
Externí odkaz:
http://arxiv.org/abs/2312.01460
Content: Microwave is a fast, efficient and energy-saving thermal resource, hence an attempt has been made for applying this technology in the combination tanning using titanium (III) and tannin extracts. In this work, the microwave effects on the co
Externí odkaz:
https://slub.qucosa.de/id/qucosa%3A34274
https://slub.qucosa.de/api/qucosa%3A34274/attachment/ATT-0/
https://slub.qucosa.de/api/qucosa%3A34274/attachment/ATT-0/
Content: Microwave was used as a thermal source to extract collagen acid from the cattle hide in the present work. The effects of microwave on collagen extraction yields were studied under different microwave temperatures, time and hide-liquid ratio.
Externí odkaz:
https://slub.qucosa.de/id/qucosa%3A34275
https://slub.qucosa.de/api/qucosa%3A34275/attachment/ATT-0/
https://slub.qucosa.de/api/qucosa%3A34275/attachment/ATT-0/
Content: In leather making processes, the thermal and non-thermal effect of microwave, especially non-thermal effect, strengthen the combination between collagen and chemicals. Although tanning under microwave makes the leather have better thermal st
Externí odkaz:
https://slub.qucosa.de/id/qucosa%3A34276
https://slub.qucosa.de/api/qucosa%3A34276/attachment/ATT-0/
https://slub.qucosa.de/api/qucosa%3A34276/attachment/ATT-0/
Autor:
Zhang, Jinwei, Zuo, Lianrui, Dewey, Blake E., Remedios, Samuel W., Hays, Savannah P., Pham, Dzung L., Prince, Jerry L., Carass, Aaron
Deep learning algorithms utilizing magnetic resonance (MR) images have demonstrated cutting-edge proficiency in autonomously segmenting multiple sclerosis (MS) lesions. Despite their achievements, these algorithms may struggle to extend their perform
Externí odkaz:
http://arxiv.org/abs/2310.20586
Recent research highlights that the Directed Accumulator (DA), through its parametrization of geometric priors into neural networks, has notably improved the performance of medical image recognition, particularly with small and imbalanced datasets. H
Externí odkaz:
http://arxiv.org/abs/2306.02589
Autor:
Zhang, Jinwei, Dimov, Alexey, Li, Chao, Zhang, Hang, Nguyen, Thanh D., Spincemaille, Pascal, Wang, Yi
Purpose: To improve the generalization ability of convolutional neural network (CNN) based prediction of quantitative susceptibility mapping (QSM) from high-pass filtered phase (HPFP) image. Methods: The proposed network addresses two common generali
Externí odkaz:
http://arxiv.org/abs/2305.03844