Zobrazeno 1 - 10
of 201
pro vyhledávání: '"Liu, Haofeng"'
Autor:
Yin, Shi, Tan, Hongqi, Chong, Li Ming, Liu, Haofeng, Liu, Hui, Lee, Kang Hao, Tuan, Jeffrey Kit Loong, Ho, Dean, Jin, Yueming
Background: Cone-beam computed tomography (CBCT) plays a crucial role in image-guided radiotherapy, but artifacts and noise make them unsuitable for accurate dose calculation. Artificial intelligence methods have shown promise in enhancing CBCT quali
Externí odkaz:
http://arxiv.org/abs/2411.01575
This paper investigates the bit error rate (BER) and outage probability performance of integrated sensing and communication (ISaC) in uplink non-orthogonal multiple access (NOMA) based Internet of Things (IoT) systems. Specifically, we consider an IS
Externí odkaz:
http://arxiv.org/abs/2408.17449
Surgical video segmentation is a critical task in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, the Segment Anything Model 2 (SAM2) framework has shown superior advancements in image and video s
Externí odkaz:
http://arxiv.org/abs/2408.07931
Point-based interactive editing serves as an essential tool to complement the controllability of existing generative models. A concurrent work, DragDiffusion, updates the diffusion latent map in response to user inputs, causing global latent map alte
Externí odkaz:
http://arxiv.org/abs/2404.01050
Publikováno v:
Medical Image Analysis, 2023, 90:102945
Fundus photography is prone to suffer from image quality degradation that impacts clinical examination performed by ophthalmologists or intelligent systems. Though enhancement algorithms have been developed to promote fundus observation on degraded i
Externí odkaz:
http://arxiv.org/abs/2309.00885
Publikováno v:
International Conference on Medical Image Computing and Computer-Assisted Intervention. (2022) 507-516
As an economical and efficient fundus imaging modality, retinal fundus images have been widely adopted in clinical fundus examination. Unfortunately, fundus images often suffer from quality degradation caused by imaging interferences, leading to misd
Externí odkaz:
http://arxiv.org/abs/2210.09606
Autor:
Li, Heng, Liu, Haofeng, Fu, Huazhu, Shu, Hai, Zhao, Yitian, Luo, Xiaoling, Hu, Yan, Liu, Jiang
Fundus photography is a routine examination in clinics to diagnose and monitor ocular diseases. However, for cataract patients, the fundus image always suffers quality degradation caused by the clouding lens. The degradation prevents reliable diagnos
Externí odkaz:
http://arxiv.org/abs/2206.04684
Publikováno v:
IEEE Transactions on Medical Imaging,2022, 41(7), 1699-1710
Cataracts are the leading cause of vision loss worldwide. Restoration algorithms are developed to improve the readability of cataract fundus images in order to increase the certainty in diagnosis and treatment for cataract patients. Unfortunately, th
Externí odkaz:
http://arxiv.org/abs/2203.07737
In recent years, a myriad of superlative works on intelligent robotics policies have been done, thanks to advances in machine learning. However, inefficiency and lack of transfer ability hindered algorithms from pragmatic applications, especially in
Externí odkaz:
http://arxiv.org/abs/2203.00251
Autor:
Chen, Siwen, Liu, Cheng, Liu, Yuyan, Liu, Jianan, Wang, Zefeng, Liu, Haofeng, Li, Ye, Liu, Min
Publikováno v:
In Science of the Total Environment 1 December 2024 954
