Search Results for author: Fei Shan

Found 10 papers, 2 papers with code

Towards Unified Surgical Skill Assessment

no code implementations CVPR 2021 Daochang Liu, Qiyue Li, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li

In this paper, a unified multi-path framework for automatic surgical skill assessment is proposed, which takes care of multiple composing aspects of surgical skills, including surgical tool usage, intraoperative event pattern, and other skill proxies.

M3Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening from CT Imaging

no code implementations7 Oct 2020 Xuelin Qian, Huazhu Fu, Weiya Shi, Tao Chen, Yanwei Fu, Fei Shan, xiangyang xue

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic.

Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion

1 code implementation27 Aug 2020 Daochang Liu, Yuhui Wei, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li

In the experiments on the binary instrument segmentation task of the 2017 MICCAI EndoVis Robotic Instrument Segmentation Challenge dataset, the proposed method achieves 0. 71 IoU and 0. 81 Dice score without using a single manual annotation, which is promising to show the potential of unsupervised learning for surgical tool segmentation.

Feature Correlation Segmentation

Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field

no code implementations27 Aug 2020 Daochang Liu, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li

Then an objective and automated framework based on neural network is proposed to predict surgical skills through the proxy of COF.

Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan

no code implementations7 May 2020 Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen

To our knowledge, this study is the first work to predict the disease progression and the conversion time, which could help clinicians to deal with the potential severe cases in time or even save the patients' lives.

Classification Computed Tomography (CT) +2

Hypergraph Learning for Identification of COVID-19 with CT Imaging

no code implementations7 May 2020 Donglin Di, Feng Shi, Fuhua Yan, Liming Xia, Zhanhao Mo, Zhongxiang Ding, Fei Shan, Shengrui Li, Ying WEI, Ying Shao, Miaofei Han, Yaozong Gao, He Sui, Yue Gao, Dinggang Shen

The main challenge in early screening is how to model the confusing cases in the COVID-19 and CAP groups, with very similar clinical manifestations and imaging features.

Lung Infection Quantification of COVID-19 in CT Images with Deep Learning

1 code implementation10 Mar 2020 Fei Shan, Yaozong Gao, Jun Wang, Weiya Shi, Nannan Shi, Miaofei Han, Zhong Xue, Dinggang Shen, Yuxin Shi

The performance of the system was evaluated by comparing the automatically segmented infection regions with the manually-delineated ones on 300 chest CT scans of 300 COVID-19 patients.

COVID-19 Image Segmentation Segmentation

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