no code implementations • 27 Apr 2024 • Lichao Wang, Zhihao Yuan, Jinke Ren, Shuguang Cui, Zhen Li
In this paper, we address two key limitations of existing approaches: 1) their reliance on ground-truth instances as input; and 2) their neglect of the relative positions among potential instances.
no code implementations • 27 Sep 2023 • Lichao Wang, Jiahao Huang, Xiaodan Xing, Yinzhe Wu, Ramyah Rajakulasingam, Andrew D. Scott, Pedro F Ferreira, Ranil De Silva, Sonia Nielles-Vallespin, Guang Yang
This study proposes a pipeline that incorporates a novel style transfer model and a simultaneous super-resolution and segmentation model.
no code implementations • 31 Mar 2023 • Jiahao Huang, Pedro F. Ferreira, Lichao Wang, Yinzhe Wu, Angelica I. Aviles-Rivero, Carola-Bibiane Schonlieb, Andrew D. Scott, Zohya Khalique, Maria Dwornik, Ramyah Rajakulasingam, Ranil De Silva, Dudley J. Pennell, Sonia Nielles-Vallespin, Guang Yang
Our results indicate that the models we discussed in this study can be applied for clinical use at an acceleration factor (AF) of $\times 2$ and $\times 4$, with the D5C5 model showing superior fidelity for reconstruction and the SwinMR model providing higher perceptual scores.
no code implementations • 28 Feb 2023 • Lichao Wang, Jiahao Huang, Xiaodan Xing, Guang Yang
Medical image segmentation is a crucial task in the field of medical image analysis.
no code implementations • 17 Sep 2022 • Xiaodan Xing, Huanjun Wu, Lichao Wang, Iain Stenson, May Yong, Javier Del Ser, Simon Walsh, Guang Yang
Data quality is the key factor for the development of trustworthy AI in healthcare.
no code implementations • 27 Nov 2020 • Lichao Wang, Lanxin Lei, Hongli Song, Weibao Wang
With the gradual maturity of 5G technology, autonomous driving technology has attracted moreand more attention among the research commu-nity.
no code implementations • 26 Aug 2016 • Gerda Bortsova, Michael Sterr, Lichao Wang, Fausto Milletari, Nassir Navab, Anika Böttcher, Heiko Lickert, Fabian Theis, Tingying Peng
A statistical analysis of these measurements requires annotation of mitosis events, which is currently a tedious and time-consuming task that has to be performed manually.
no code implementations • 23 Oct 2015 • Kanishka Sharma, Loic Peter, Christian Rupprecht, Anna Caroli, Lichao Wang, Andrea Remuzzi, Maximilian Baust, Nassir Navab
This paper presents a method for 3D segmentation of kidneys from patients with autosomal dominant polycystic kidney disease (ADPKD) and severe renal insufficiency, using computed tomography (CT) data.