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  1. No Access

    Chapter and Conference Paper

    HI-Net: Hyperdense Inception 3D UNet for Brain Tumor Segmentation

    The brain tumor segmentation task aims to classify tissue into the whole tumor (WT), tumor core (TC) and enhancing tumor (ET) classes using multimodel MRI images. Quantitative analysis of brain tumors is criti...

    Saqib Qamar, Parvez Ahmad, Linlin Shen in Brainlesion: Glioma, Multiple Sclerosis, S… (2021)

  2. No Access

    Chapter and Conference Paper

    Context Aware 3D UNet for Brain Tumor Segmentation

    Deep convolutional neural network (CNN) achieves remarkable performance for medical image analysis. UNet is the primary source in the performance of 3D CNN architectures for medical imaging tasks, including br...

    Parvez Ahmad, Saqib Qamar, Linlin Shen… in Brainlesion: Glioma, Multiple Sclerosis, S… (2021)

  3. No Access

    Chapter and Conference Paper

    Hybrid Labels for Brain Tumor Segmentation

    The accurate automatic segmentation of brain tumors enhances the probability of survival rate. Convolutional Neural Network (CNN) is a popular automatic approach for image evaluations. CNN provides excellent r...

    Parvez Ahmad, Saqib Qamar… in Brainlesion: Glioma, Multiple Sclerosis, S… (2020)