no code implementations • 23 Mar 2024 • Kesheng Wang, Kunhui Xu, Xiaoyu Chen, Chunlei He, Jianfeng Zhang, Dexing Kong, Qi Dai, Shoujun Huang
For improved segmentation of the pupil and tear meniscus areas, the convolutional neural network Inceptionv3 was first implemented as an image quality assessment model, effectively identifying higher-quality images with an accuracy of 98. 224%.
no code implementations • 10 Oct 2023 • Siyuan Jiang, Yan Ding, Yuling Wang, Lei Xu, Wenli Dai, Wanru Chang, Jianfeng Zhang, Jie Yu, Jianqiao Zhou, Chunquan Zhang, Ping Liang, Dexing Kong
Ultrasound is a vital diagnostic technique in health screening, with the advantages of non-invasive, cost-effective, and radiation free, and therefore is widely applied in the diagnosis of nodules.
no code implementations • 29 May 2021 • Yuanpeng Liu, Qinglei Hui, Zhiyi Peng, Shaolin Gong, Dexing Kong
Existing automatic segmentation methods are mainly based on fully supervised learning and have an extremely high demand for precise annotations, which are very costly and time-consuming to obtain.
no code implementations • 11 Jan 2019 • Xinling Zhang, Xu Li, Ying Chen, Yixin Gan, Dexing Kong, Rongqin Zheng
In this paper, a multi-scale framework with local region based active contour and boundary shape similarity constraint is proposed for the segmentation of levator hiatus in ultrasound images.
no code implementations • 10 May 2016 • Fang Lu, Fa Wu, Peijun Hu, Zhiyi Peng, Dexing Kong
Purpose Segmentation of the liver from abdominal computed tomography (CT) image is an essential step in some computer assisted clinical interventions, such as surgery planning for living donor liver transplant (LDLT), radiotherapy and volume measurement.
no code implementations • 31 Jul 2015 • Fa Wu, Peijun Hu, Dexing Kong
We also introduce two rotational convolution techniques, i. e. rotate-pooling convolution (RPC) and flip-rotate-pooling convolution (FRPC) to boost CNNs' performance on the robustness for rotation transformation.