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@MedcAILab

MAILab@SZU

Medical AI Lab in Shenzhen University

Introduction

假装是logo

The Medical AI Lab of Shenzhen University, in cooperation with the First Affiliated Hospital of Sun Yat-sen University and other well-known hospitals in and outside the province, has carried out research on AI analysis methods of medical big data, and has carried out application and transformation in cancer, brain disease, digestive tract disease, vascular disease, oral cavity disease and other aspects.

Major research interests

①Lesion detection/segmentation based on medical image and prior knowledge ②Radiomics ③Pathophysiological interpretation of image characteristics

Project code

DSFR Deep Semantic Segmentation Feature-based Radiomics for the Classification Tasks in Medical Image Analysis

3D Lightweight Network for Simultaneous Registration and Segmentation of Organs-at-Risk in CT Images of Head and Neck Cancer

Representative papers (part)

1. 3D Lightweight Network for Simultaneous Registration and Segmentation of Organs-at-Risk in CT Images of Head and Neck Cancer. Huang B#, Ye Y#, Xu Z#, Cai Z, He Y, Zhong Z, Liu L, Chen X, Chen H**, Huang B*. IEEE Transactions on Medical Imaging. 2022 Apr;41(4):951-964. (2022 IF 11.037,中科院1区TOP)

2. Identifying patients with Crohn’s disease at high risk of primary nonresponse to infliximab using a radiomic-clinical model. Li X#, Zhong Y#, Yuan C#, Lin J, Shen X, Guo M, Lu B, Meng J, Wang Y, Zhang N, Luo Z, Hu G, Mao R, Chen M, Sun C, Li Z, Cao Q, Chen B*, Chen Z*, Huang B*, Feng ST*. International Journal of Intelligent Systems. (已接收, 2022 IF 8.993,中科院大类1区TOP)

3. Development and Validation of a Novel Computed-Tomography Enterography Radiomic Approach for Characterization of Intestinal Fibrosis in Crohn’s Disease. Li X#, Liang D#, Meng J#, Zhou J, Chen Z, Huang S, Lu B, Qiu Y, Baker M E, Ye Z, Cao Q, Wang M, Yuan C, Chen Z, Feng S, Zhang Y, Iacucci M, Ghosh S, Rieder F, Sun C, Chen M, Li Z, Mao R*, Huang B*, Feng ST*. Gastroenterology. 2021 Jun;160(7):2303-2316.e11. (2021 IF 22.682,中科院大类1区TOP)

4. Deep Semantic Segmentation Feature-based Radiomics for the Classification Tasks in Medical Image Analysis. Huang B#, Tian J#, Zhang H, Luo Z, Qin J, Huang C, He X, Luo Y, Zhou Y, Dan G, Chen H*, Feng ST* and Yuan C*. IEEE Journal of Biomedical and Health Informatics. 2021 Jul;25(7):2655-2664. (2021 IF 5.772,中科院大类2区TOP,小类1区)

5. Accurate and Feasible Deep Learning Based Semi-automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms. Huang B#, Lin X#, Shen J, Chen X, Chen J, Li ZP, Wang M, Yuan C, Diao XF*, Luo Y*, Feng S*. IEEE Journal of Biomedical and Health Informatics. 2021 Sep;25(9):3498-3506. (2021 IF 5.772,中科院大类2区TOP,小类1区)

6. Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists. Meng J#, Luo Z#, Chen Z, Zhou J, Chen Z, Lu B, Zhang M, Wang Y, Yuan C, Shen X, Huang Q, Zhang Z, Ye Z, Cao Q, Zhou Z, Xu Y, Mao R, Chen M, Sun C, Li Z, Feng ST, Meng X, Huang B*, Li X*. European Radiology. 2022 May 26. Epub ahead of print. (2022 IF 7.034,中科院大类2区TOP)

7. Preoperative prediction of cytokeratin 19 expression for hepatocellular carcinoma with deep learning radiomics based on gadoxetic acid-enhanced magnetic resonancen imaging. Chen Y#, Chen J#, Zhang Y#, Lin Z, Wang M, Huang L, Huang M, Tang M, Zhou X, Peng Z, Chen J, Long T, Huang B*, Feng* ST. Journal of Hepatocellular Carcinoma. 2021 Jul 22;8:795-808. (2021 IF 5.828,中科院大类2区)

8. Preoperative Prediction of Pancreatic Neuroendocrine Neoplasms Grading Based on Enhanced CT Imaging: Validation of Deep Learning with a Convolutional Neural Network. Luo Y#, Chen X#, Chen J#, Song C, Shen J, Xiao H, Chen M, Li ZP, Huang B*, Feng ST*. Neuroendocrinology. 2020;110(5):338-350. (2019 IF 6.804,中科院大类2区)

9. The potential of radiomics in the assessment of intestinal fibrosis in Crohn’s disease: Author’s reply. Li X #, Liang D#, Huang B*. Gastroenterology. 2021 Dec;161(6):2066-2067. (2021 IF 22.682,中科院大类1区TOP)

10. Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study. Huang B#, Wang J#, Sun M, Chen X, Xu D, Li Z, Ma J*, Feng S*, Gao Z*. BMC Cancer. 2020 Apr 15;20(1):322.(2020 IF 3.150,中科院大类3区

Pinned Loading

  1. scikit-radiomics scikit-radiomics Public

    Forked from szuboy/scikit-radiomics

    scikit-radiomics’s documentation!

    Python 2

  2. DSFR DSFR Public

    Deep Semantic Segmentation Feature-based Radiomics for the Classification Tasks in Medical Image Analysis

  3. RS2-net_JBHI_2023 RS2-net_JBHI_2023 Public

    Code for J Biomed Health Inform . 2023

    Python

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