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pro vyhledávání: '"Tai-An Cheng"'
The UNet architecture has transformed image segmentation. UNet's versatility and accuracy have driven its widespread adoption, significantly advancing fields reliant on machine learning problems with images. In this work, we give a clear and concise
Externí odkaz:
http://arxiv.org/abs/2410.04434
In this article, we develop nonparametric inference methods for comparing survival data across two samples, which are beneficial for clinical trials of novel cancer therapies where long-term survival is a critical outcome. These therapies, including
Externí odkaz:
http://arxiv.org/abs/2409.02209
Shape compactness is a key geometrical property to describe interesting regions in many image segmentation tasks. In this paper, we propose two novel algorithms to solve the introduced image segmentation problem that incorporates a shape-compactness
Externí odkaz:
http://arxiv.org/abs/2406.19400
BP-DeepONet: A new method for cuffless blood pressure estimation using the physcis-informed DeepONet
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, with blood pressure serving as a crucial indicator. Arterial blood pressure (ABP) waveforms provide continuous pressure measurements throughout the cardiac cycle and offer valua
Externí odkaz:
http://arxiv.org/abs/2402.18886
In this study, our goal is to integrate classical mathematical models with deep neural networks by introducing two novel deep neural network models for image segmentation known as Double-well Nets. Drawing inspirations from the Potts model, our model
Externí odkaz:
http://arxiv.org/abs/2401.00456
Investigating blood flow in the cardiovascular system is crucial for assessing cardiovascular health. Computational approaches offer some non-invasive alternatives to measure blood flow dynamics. Numerical simulations based on traditional methods suc
Externí odkaz:
http://arxiv.org/abs/2312.05601
The Euler Elastica (EE) model with surface curvature can generate artifact-free results compared with the traditional total variation regularization model in image processing. However, strong nonlinearity and singularity due to the curvature term in
Externí odkaz:
http://arxiv.org/abs/2308.13471
Deep neural network is a powerful tool for many tasks. Understanding why it is so successful and providing a mathematical explanation is an important problem and has been one popular research direction in past years. In the literature of mathematical
Externí odkaz:
http://arxiv.org/abs/2307.09052
For problems in image processing and many other fields, a large class of effective neural networks has encoder-decoder-based architectures. Although these networks have made impressive performances, mathematical explanations of their architectures ar
Externí odkaz:
http://arxiv.org/abs/2307.09039
Autor:
Thi-Huong Nguyen, Huey-Jiun Ko, Po-Yu Tsai, Tai-Shan Cheng, Thu-Ha Tran, Ly Hien Doan, Michael Hsiao, Peter Mu-Hsin Chang, Hsiao-Sheng Liu, Yi-Ren Hong, Chi-Ying F. Huang
Publikováno v:
Frontiers in Pharmacology, Vol 15 (2024)
Colorectal cancer (CRC) is one of the primary contributors to cancer-related fatalities, with up to 80% of advanced CRC cases exhibiting mutations in the p53 gene. Unfortunately, the development of new compounds targeting mutant p53 is quite limited.
Externí odkaz:
https://doaj.org/article/175e1107fd754719a53e6fa4e741b36b
