no code implementations • 7 Feb 2023 • Wangbin Ding, Lei LI, Junyi Qiu, Sihan Wang, Liqin Huang, Yinyin Chen, Shan Yang, Xiahai Zhuang
For instance, balanced steady-state free precession cine sequences present clear anatomical boundaries, while late gadolinium enhancement and T2-weighted CMR sequences visualize myocardial scar and edema of MI, respectively.
no code implementations • 26 Aug 2022 • Lei LI, Wangbin Ding, Liqun Huang, Xiahai Zhuang, Vicente Grau
Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases.
no code implementations • 8 Aug 2022 • Mengjun Wu, Wangbin Ding, Mingjin Yang, Liqin Huang
By introducing a Sobel fusion module between the two segmentation branches, the spatial information of LA boundaries can be propagated from the LA branch to the scar branch.
1 code implementation • 4 Feb 2022 • Wangbin Ding, Lei LI, Xiahai Zhuang, Liqin Huang
For the label fusion, we design a similarity estimation network (SimNet), which estimates the fusion weight of each atlas by measuring its similarity to the target image.
1 code implementation • 5 Sep 2021 • Lei LI, Wangbin Ding, Liqun Huang, Xiahai Zhuang
In this work, we propose an automatic RV segmentation framework, where the information from long-axis (LA) views is utilized to assist the segmentation of short-axis (SA) views via information transition.
1 code implementation • 16 May 2021 • Wangbin Ding, Lei LI, Xiahai Zhuang, Liqin Huang
However, it is still challenging to develop a multi-modality registration network due to the lack of robust criteria for network training.
no code implementations • 22 Feb 2021 • Shaohua Zheng, Zhiqiang Shen, Chenhao Peia, Wangbin Ding, Haojin Lin, Jiepeng Zheng, Lin Pan, Bin Zheng, Liqin Huang
In addition, explanations of CDAM features proved that the shape and density of nodule regions were two critical factors that influence a nodule to be inferred as malignant, which conforms with the diagnosis cognition of experienced radiologists.
no code implementations • 29 Oct 2020 • Chenyu Liu, Wangbin Ding, Lei LI, Zhen Zhang, Chenhao Pei, Liqin Huang, Xiahai Zhuang
Considering that multi-modal MR images can reflect different tumor biological properties, we develop a novel multi-modal tumor segmentation network (MMTSN) to robustly segment brain tumors based on multi-modal MR images.
no code implementations • 27 Aug 2020 • Lei Li, Veronika A. Zimmer, Wangbin Ding, Fuping Wu, Liqin Huang, Julia A. Schnabel, Xiahai Zhuang
As the target domain could be unknown, we randomly generate a modality vector for the target modality in the style transfer stage, to simulate the domain shift for unknown domains.
no code implementations • 15 Aug 2020 • Wangbin Ding, Lei LI, Xiahai Zhuang, Liqin Huang
For label fusion, we adapt a few-shot learning network to measure the similarity of atlas and target patches.
1 code implementation • 13 Aug 2020 • Zhen Zhang, Chenyu Liu, Wangbin Ding, Sihan Wang, Chenhao Pei, Mingjing Yang, Liqin Huang
The PRSN is designed to segment pathological region based on the result of ASSN, in which a fusion block based on channel attention is proposed to better aggregate multi-modality information from multi-modality CMR images.