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Browsing by author "Bi, Lei"

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    • An Automated and Robust Tumours Detection and Segmentation Framework for Whole-Body PET-CT Studies 

      Bi, Lei
      Published 2013-05-24
      A dual-modality positron emission tomography – computed tomography (PET-CT) is one of widely used medical imaging system. It combines functional (from PET) with anatomical (from CT) information, in a co-aligned space, ...
      USyd Access
      Thesis
      View
    • Automated thresholded region classification using a robust feature selection method for PET-CT 

      Bi, Lei; Kim, Jinman; Wen, Lingfeng; Feng, Dagan; Fulham, Michael
      Published 2015-07-23
      Fluorodeoxyglucose Positron Emission Tomography - Computed Tomography (FDG PET-CT) is the preferred imaging modality for staging the lymphomas. Sites of disease usually appear as foci of increased FDG uptake. Thresholding ...
      Open Access
      Conference paper
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    • Automatic Detection and Classification of Regions of FDG Uptake in Whole-Body PET-CT Lymphoma Studies 

      Bi, Lei; Kim, Jinman; Kuman, Ashnil; Wen, Lingfeng; Feng, Dagan; Fulham, Michael
      Published 2017-09-01
      Open Access
      Article
      View
    • Classification of thresholded regions based on selective use of PET, CT and PET-CT image features 

      Bi, Lei; Kim, Jinman; Feng, Dagan; Fulham, Michael
      Published 2014-11-06
      Fluorodeoxyglucose positron emission tomography - computed tomography (FDG PET-CT) is the preferred image modality for lymphoma diagnosis. Sites of disease generally appear as foci of increased FDG uptake. Thresholding ...
      Open Access
      Conference paper
      View
    • Deep Cascaded Fully Convolutional Networks for Medical Image Segmentation 

      Bi, Lei
      Published 2018-03-31
      Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer aided diagnosis (CAD) systems. Recently, deep learning methods based on fully convolutional networks (FCN) ...
      USyd Access
      Thesis
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    • Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks 

      Bi, Lei; Kim, Jinman; Ahn, Euijoon; Kumar, Ashnil; Fulham, Michael; Feng, Dagan
      Published 2017-06-07
      Open Access
      Article
      View
    • Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation 

      Bi, Lei; Feng, David Dagan; Kim, Jinman
      Published 2018-01-01
      Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer-aided diagnosis systems. In recent years, segmentation methods based on fully convolutional networks (FCNs) ...
      Open Access
      Article
      View
    • Improving Skin Lesion Segmentation via Stacked Adversarial Learning 

      Bi, Lei; Feng, Dagan; Fulham, Michael; Kim, Jinman
      Published 2019-01-01
      Segmentation of skin lesions is an essential step in computer aided diagnosis (CAD) for the automated melanoma diagnosis. Recently, segmentation methods based on fully convolutional networks (FCNs) have achieved great ...
      Open Access
      Conference paper
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    • Multi-Label Classification of Multi-Modality Skin Lesion via Hyper-Connected Convolutional Neural Network 

      Bi, Lei; Feng, David Dagan; Fulham, Michael; Kim, Jinman
      Published 2020-01-01
      Objective: Clinical and dermoscopy images (multi-modality image pairs) are routinely used sequentially in the assessment of skin lesions. Clinical images characterize a lesion’s geometry and color; dermoscopy depicts ...
      Embargoed
      Article
      View
    • Recurrent Feature Fusion Learning for Multi-Modality PET-CT Tumor Segmentation 

      Bi, Lei; Fulham, Michael; Li, Nan; Liu, Qiufang; Song, Shaoli; Feng, David Dagan; Kim, Jinman
      Published 2021
      Background and Objective: [18F]-Fluorodeoxyglucose (FDG) positron emission tomography – computed tomography (PET-CT) is now the preferred imaging modality for staging many cancers. PET images characterize tumoral glucose ...
      Open Access
      Article
      View
    • Saliency-Based Lesion Segmentation Via Background Detection in Dermoscopic Images 

      Ahn, Euijoon; Kim, Jinman; Bi, Lei; Kumar, Ashnil; Li, Changyang; Fulham, Michael; Feng, Dagan
      Published 2017-01-16
      Open Access
      Article
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    • Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation 

      Bi, Lei; Kim, Jinman; Kumar, Ashnil; Fulham, Michael; Feng, Dagan
      Published 2017-05-04
      The automated segmentation of regions of interest (ROIs) in medical imaging is the fundamental requirement for the derivation of high-level semantics for image analysis in clinical decision support systems. Traditional ...
      Open Access
      Article
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    • Step-wise Integration of Deep Class-specific Learning for Dermoscopic Image Segmentation 

      Bi, Lei; Kim, Jinman; Ahn, Euijoon; Kumar, Ashnil; Feng, Dagan; Fulham, Michael
      Published 2018-01-01
      The segmentation of abnormal regions on dermoscopic images is an important step for automated computer aided diagnosis (CAD) of skin lesions. Recent methods based on fully convolutional networks (FCN) have been very ...
      Open Access
      Article
      View
    • Unsupervised Brain Tumor Segmentation using a Symmetric-driven Adversarial Network 

      Wu, Xinheng; Bi, Lei; Fulham, Michael; Feng, David Dagan; Zhou, Luping; Kim, Jinman
      Published 2021
      The aim of this study was to computationally model, in an unsupervised manner, a manifold of symmetry variations in normal brains, such that the learned manifold can be used to segment brain tumors from magnetic resonance ...
      Open Access
      Article
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