Zobrazeno 1 - 10
of 321
pro vyhledávání: '"Yaoqin, Xie"'
Publikováno v:
Earth and Space Science, Vol 11, Iss 10, Pp n/a-n/a (2024)
Abstract There are many problems in space debris monitoring with ground‐based telescopes, such as too many stars in the same field of view, uneven background and optical distortion in the optical system. We propose a two‐stage weak debris detecti
Externí odkaz:
https://doaj.org/article/059399da66a547b5aebb92567d44a953
Publikováno v:
Sensors, Vol 24, Iss 18, p 5900 (2024)
Recognizing sleep posture is crucial for the monitoring of people with sleeping disorders. Existing contact-based systems might interfere with sleeping, while camera-based systems may raise privacy concerns. In contrast, radar-based sensors offer a p
Externí odkaz:
https://doaj.org/article/87a43ccc250d4456bc08c15d03f81c04
Autor:
Shaode Yu, Mingxue Jin, Tianhang Wen, Linlin Zhao, Xuechao Zou, Xiaokun Liang, Yaoqin Xie, Wanlong Pan, Chenghao Piao
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-18 (2023)
Abstract Background Breast cancer (BC) is one of the most common cancers among women. Since diverse features can be collected, how to stably select the powerful ones for accurate BC diagnosis remains challenging. Methods A hybrid framework is designe
Externí odkaz:
https://doaj.org/article/d86556d3fc4e45178bbe8060d3381ec2
Publikováno v:
Bioengineering, Vol 11, Iss 1, p 2 (2023)
Radar signal has been shown as a promising source for human identification. In daily home sleep-monitoring scenarios, large-scale motion features may not always be practical, and the heart motion or respiration data may not be as ideal as they are in
Externí odkaz:
https://doaj.org/article/dd521a4ad961449fb15afdbf68ad4a2c
Autor:
Isah Salim Ahmad, Na Li, Tangsheng Wang, Xuan Liu, Jingjing Dai, Yinping Chan, Haoyang Liu, Junming Zhu, Weibin Kong, Zefeng Lu, Yaoqin Xie, Xiaokun Liang
Publikováno v:
Bioengineering, Vol 10, Iss 11, p 1314 (2023)
The detection of Coronavirus disease 2019 (COVID-19) is crucial for controlling the spread of the virus. Current research utilizes X-ray imaging and artificial intelligence for COVID-19 diagnosis. However, conventional X-ray scans expose patients to
Externí odkaz:
https://doaj.org/article/a379d06fbde44685a52bccc63be0263f
Autor:
Na Li, Xuanru Zhou, Shupeng Chen, Jingjing Dai, Tangsheng Wang, Chulong Zhang, Wenfeng He, Yaoqin Xie, Xiaokun Liang
Publikováno v:
Frontiers in Oncology, Vol 13 (2023)
ObjectiveTo develop a contrast learning-based generative (CLG) model for the generation of high-quality synthetic computed tomography (sCT) from low-quality cone-beam CT (CBCT). The CLG model improves the performance of deformable image registration
Externí odkaz:
https://doaj.org/article/201e4957baba4625948d348393b0ac6f
Publikováno v:
Frontiers in Oncology, Vol 12 (2022)
The application of metal nanoparticles (MNPs) as sensitization materials is a common strategy that is used to study dose enhancement in radiotherapy. Recent in vitro tests have revealed that magnetic gold nanoparticles (NPs) can be used in cancer the
Externí odkaz:
https://doaj.org/article/243d5338b41b4f4cb62da449654cebc9
Publikováno v:
IEEE Access, Vol 9, Pp 3315-3325 (2021)
Breast cancer is one of the most common malignancies in women. The prone position in Partial Breast Irradiation (PBI) can better protect the heart and lung during radiotherapy. Supine position is used for CT imaging during treatment planning. The pos
Externí odkaz:
https://doaj.org/article/1f8ea299bab046fb81459809153b64e6
Autor:
Guoya Dong, Jingjing Dai, Na Li, Chulong Zhang, Wenfeng He, Lin Liu, Yinping Chan, Yunhui Li, Yaoqin Xie, Xiaokun Liang
Publikováno v:
Bioengineering, Vol 10, Iss 2, p 144 (2023)
Two-dimensional (2D)/three-dimensional (3D) registration is critical in clinical applications. However, existing methods suffer from long alignment times and high doses. In this paper, a non-rigid 2D/3D registration method based on deep learning with
Externí odkaz:
https://doaj.org/article/e90bd27da4d943cd9686497d40334799
Publikováno v:
Bioengineering, Vol 9, Iss 12, p 804 (2022)
Automatic pain estimation plays an important role in the field of medicine and health. In the previous studies, most of the entire image frame was directly imported into the model. This operation can allow background differences to negatively affect
Externí odkaz:
https://doaj.org/article/b354d4702d9047a9b103f9d35dafead8