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4 Result(s)

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  1. No Access

    Chapter and Conference Paper

    A Modified Fuzzy Markov Random Field Incorporating Multiple Features for Liver Tumor Segmentation

    Automated segmentation of liver tumors from computerized tomography (CT) images plays a crucial role in computer-aided pathological diagnosis, surgical planning, and postoperative assessment. However, liver tu...

    Laquan Li, Yan Jiang in Artificial Intelligence (2024)

  2. No Access

    Chapter and Conference Paper

    Abdominal Multi-organ Localization with Adaptive Random Forest in CT Images

    Medical image localization plays an important role in digital medical research, therapy planning, and delivery. However, the presence of noise and low contrast renders automatic abdominal multi-organ localizat...

    Ruihao Wang, Jiaxin Tan, Laquan Li… in Advances in Natural Computation, Fuzzy Sys… (2023)

  3. No Access

    Chapter and Conference Paper

    msFormer: Adaptive Multi-Modality 3D Transformer for Medical Image Segmentation

    Over the past years, Convolutional Neural Networks (CNNs) have dominated the field of medical image segmentation. But they have difficulty representing long-range dependencies. Recently, the Transformer has be...

    Jiaxin Tan, Chuangbo Jiang, Laquan Li… in Pattern Recognition and Computer Vision (2022)

  4. No Access

    Chapter and Conference Paper

    Automatic Liver Lesion Segmentation in CT Combining Fully Convolutional Networks and Non-negative Matrix Factorization

    Automatic liver tumor segmentation is an important step towards digital medical research, clinical diagnosis and therapy planning. However, the existence of noise, low contrast and heterogeneity make the autom...

    Shenhai Zheng, Bin Fang, Laquan Li… in Imaging for Patient-Customized Simulations… (2017)