ORCID Profile
0000-0002-3381-214X
Current Organisation
University of Sydney
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Information Systems | Information Systems Development Methodologies | Artificial Intelligence and Image Processing | Pattern Recognition and Data Mining | Image Processing | Information Storage, Retrieval And Management | Simulation And Modelling | Library and Information Studies | Medical and Health Sciences not elsewhere classified | Information Systems Development Methodologies | Simulation and Modelling | Global Information Systems | Health Information Systems (Incl. Surveillance) | Interfaces And Presentation (Excl. Computer-Human Interaction) | Data Storage Representations | Information Systems Organisation | Communications Technologies | Regenerative Medicine (incl. Stem Cells and Tissue Engineering) | Decision Support And Group Support Systems | Multimedia Programming | Medical Devices | Biomaterials | Biomedical Engineering | Antenna Technology | Digital Systems | Computer Communications Networks | Analysis Of Algorithms And Complexity | Multimedia | Astronomy And Astrophysics | Bioinformatics | Pattern Recognition
ANZSRC Socio-Economic Objective (SEO)
Information processing services | Clinical Health (Organs, Diseases and Abnormal Conditions) not elsewhere classified | Diagnostic methods | Diagnostic Methods | Application tools and system utilities | Organs, diseases and abnormal conditions not elsewhere classified | Information and Communication Services not elsewhere classified | Health and Support Services not elsewhere classified | Cancer and related disorders | Solar-photoelectric | Skeletal System and Disorders (incl. Arthritis) | Physical sciences | Information services not elsewhere classified | Health and support services not elsewhere classified | Technological and organisational innovation | Integrated circuits and devices | Expanding Knowledge in the Medical and Health Sciences | Medical Instruments | Health Education and Promotion | Public health not elsewhere classified | Expanding Knowledge in the Biological Sciences | Other |
Related Links
Publications
End-User Development for Interactive Data Analytics: Uncertainty, Correlation and User Confidence
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2017
Cloud-Based Automated Clinical Decision Support System for Detection and Diagnosis of Lung Cancer in Chest CT
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative Learning
Publisher: Springer Nature Switzerland
Date: 2022
Hybrid Refinement-Correction Heatmaps for Human Pose Estimation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Machine Learning-Based Noninvasive Quantification of Single-Imaging Session Dual-Tracer 18F-FDG and 68Ga-DOTATATE Dynamic PET-CT in Oncology
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2022
Unsupervised Two-Path Neural Network for Cell Event Detection and Classification Using Spatiotemporal Patterns
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Illumination-Guided Video Composition via Gradient Consistency Optimization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Real-Time Long-Term Tracking With Prediction-Detection-Correction
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
Automated Decision Support System for Lung Cancer Detection and Classification via Enhanced RFCN With Multilayer Fusion RPN
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
Robust video summarization using collaborative representation of adjacent frames
Publisher: Springer Science and Business Media LLC
Date: 06-2018
Illumination-Invariant Video Cut-Out Using Octagon Sensitive Optimization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2020
Segmenting neuronal structure in 3d optical microscope images via knowledge distillation with teacher-student network
Publisher: IEEE
Date: 04-2019
Biomedical image segmentation for precision radiation oncology
Publisher: Elsevier
Date: 2020
Image-based biomedical data modeling and parametric imaging
Publisher: Elsevier
Date: 2020
Deep Local-Global Refinement Network for Stent Analysis in IVOCT Images
Publisher: No publisher found
Date: 2019
A study on multi-kernel intuitionistic fuzzy C-means clustering with multiple attributes
Publisher: Elsevier BV
Date: 03-2019
Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Deep Color Guided Coarse-to-Fine Convolutional Network Cascade for Depth Image Super-Resolution
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2019
A Unified Collaborative Multikernel Fuzzy Clustering for Multiview Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2018
Deep Convolutional Neural Networks for Human Action Recognition Using Depth Maps and Postures
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
Deep gesture interaction for augmented anatomy learning
Publisher: Elsevier BV
Date: 04-2019
Deep Local-Global Refinement Network for Stent Analysis in IVOCT Images
Publisher: Springer International Publishing
Date: 2019
Graph Sequence Recurrent Neural Network for Vision-Based Freezing of Gait Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Video Summarization via Nonlinear Sparse Dictionary Selection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Feature covariance matrix-based dynamic hand gesture recognition
Publisher: Springer Science and Business Media LLC
Date: 15-09-2018
Optimizing Contextual Feature Learning for Mitosis Detection with Convolutional Recurrent Neural Networks
Publisher: IEEE
Date: 04-2019
Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Retinal Vessel Segmentation Using Minimum Spanning Superpixel Tree Detector
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Noninvasive Input Function Acquisition and Simultaneous Estimations With Physiological Parameters for PET Quantification: A Brief Review
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2020
Survey on Smoothed Particle Hydrodynamics and the Particle Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Modified GAN-CAED to Minimize Risk of Unintentional Liver Major Vessels Cutting by Controlled Segmentation Using CTA/SPET-CT
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2021
Real-time hand posture recognition using hand geometric features and Fisher Vector
Publisher: Elsevier BV
Date: 03-2020
Mixed-Weight Neural Bagging for Detecting $m^6A$ Modifications in SARS-CoV-2 RNA Sequencing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2022
Content-based large-scale medical image retrieval
Publisher: Elsevier
Date: 2020
A New Aggregation of DNN Sparse and Dense Labeling for Saliency Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2021
Multi-modality Information Fusion for Radiomics-Based Neural Architecture Search
Publisher: No publisher found
Date: 2020
Similarity Based Block Sparse Subset Selection for Video Summarization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Recent advances in the 3D physiological human
Publisher: Springer London
Date: 2009
Brain Tumor Sequence Registration with Non-iterative Coarse-To-Fine Networks and Dual Deep Supervision
Publisher: Springer Nature Switzerland
Date: 2023
Improving PET-CT Image Segmentation via Deep Multi-modality Data Augmentation
Publisher: Springer International Publishing
Date: 2020
SPST-CNN: Spatial pyramid based searching and tagging of liver’s intraoperative live views via CNN for minimal invasive surgery
Publisher: Elsevier BV
Date: 06-2020
Multi-Pass Fast Watershed for Accurate Segmentation of Overlapping Cervical Cells
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
Fine-Grained and Multiple Classification for Alzheimer's Disease With Wavelet Convolution Unit Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Improving Skin Lesion Segmentation via Stacked Adversarial Learning
Publisher: IEEE
Date: 04-2019
Hyperspectral Image Classification With Global–Local Discriminant Analysis and Spatial–Spectral Context
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Liver Extraction Using Residual Convolution Neural Networks From Low-Dose CT Images
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
OFF-eNET: An Optimally Fused Fully End-to-End Network for Automatic Dense Volumetric 3D Intracranial Blood Vessels Segmentation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Non-iterative Coarse-to-Fine Transformer Networks for Joint Affine and Deformable Image Registration
Publisher: Springer Nature Switzerland
Date: 2023
Malocclusion Treatment Planning via PointNet Based Spatial Transformation Network
Publisher: No publisher found
Date: 2020
Stacked Memory Network for Video Summarization
Publisher: ACM
Date: 15-10-2019
Unsupervised Domain Adaptation to Classify Medical Images Using Zero-Bias Convolutional Auto-Encoders and Context-Based Feature Augmentation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Affective Audio Annotation of Public Speeches with Convolutional Clustering Neural Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer
Publisher: Springer Nature Switzerland
Date: 2023
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
Publisher: Springer Science and Business Media LLC
Date: 03-06-2023
DOI: 10.1007/S11633-022-1406-4
Abstract: Over the last decade, supervised deep learning on manually annotated big data has been progressing significantly on computer vision tasks. But, the application of deep learning in medical image analysis is limited by the scarcity of high-quality annotated medical imaging data. An emerging solution is self-supervised learning (SSL), among which contrastive SSL is the most successful approach to rivalling or outperforming supervised learning. This review investigates several state-of-the-art contrastive SSL algorithms originally on natural images as well as their adaptations for medical images, and concludes by discussing recent advances, current limitations, and future directions in applying contrastive SSL in the medical domain.
Multi-Label classification of multi-modality skin lesion via hyper-connected convolutional neural network
Publisher: Elsevier BV
Date: 11-2020
Deep Multimodal Graph-Based Network for Survival Prediction from Highly Multiplexed Images and Patient Variables
Publisher: Cold Spring Harbor Laboratory
Date: 20-07-2022
DOI: 10.1101/2022.07.19.500604
Abstract: The spatial architecture of the tumour microenvironment and phenotypic heterogeneity of tumour cells have been shown to be associated with cancer prognosis and clinical outcomes, including survival. Recent advances in highly multiplexed imaging, including imaging mass cytometry (IMC), capture spatially resolved, high-dimensional maps that quantify dozens of disease-relevant biomarkers at single-cell resolution, that contain potential to inform patient-specific prognosis. However, existing automated methods for predicting survival typically do not leverage spatial phenotype information captured at the single-cell level, and current methods tend to focus on a single modality, such as patient variables (PVs). There is no end-to-end method designed to leverage the rich information in whole IMC images and all marker channels, and aggregate this information with PVs in a complementary manner to predict survival with enhanced accuracy. We introduce a deep multimodal graph-based network (DMGN) that integrates entire IMC images and multiple PVs for end-to-end survival prediction of breast cancer. We propose a multimodal graph-based module that considers relationships between spatial phenotype information in all image regions and all PVs, and scales each region–PV pair based on its relevance to survival. We propose another module to automatically generate embeddings specialised for each PV to enhance multimodal aggregation. We show that our modules are consistently effective at improving survival prediction performance using two public datasets, and that DMGN can be applied to an independent validation dataset across the same antigens but different antibody clones. Our DMGN outperformed state-of-the-art methods at survival prediction.
IntersectGAN: Learning Domain Intersection for Generating Images with Multiple Attributes
Publisher: ACM
Date: 15-10-2019
A Shortened Model for Logan Reference Plot Implemented via the Self-Supervised Neural Network for Parametric PET Imaging
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
Image-Aligned Dynamic Liver Reconstruction Using Intra-Operative Field of Views for Minimal Invasive Surgery
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2019
A Residual Based Attention Model for EEG Based Sleep Staging
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2020
ECSU-Net: An Embedded Clustering Sliced U-Net Coupled With Fusing Strategy for Efficient Intervertebral Disc Segmentation and Classification
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
A direct volume rendering visualization approach for serial PET-CT scans that preserves anatomical consistency
Publisher: Springer Science and Business Media LLC
Date: 19-01-2019
DOI: 10.1007/S11548-019-01916-2
Abstract: Our aim was to develop an interactive 3D direct volume rendering (DVR) visualization solution to interpret and analyze complex, serial multi-modality imaging datasets from positron emission tomography-computed tomography (PET-CT). Our approach uses: (i) a serial transfer function (TF) optimization to automatically depict particular regions of interest (ROIs) over serial datasets with consistent anatomical structures (ii) integration of a serial segmentation algorithm to interactively identify and track ROIs on PET and (iii) parallel graphics processing unit (GPU) implementation for interactive visualization. Our DVR visualization more easily identifies changes in ROIs in serial scans in an automated fashion and parallel GPU computation which enables interactive visualization. Our approach provides a rapid 3D visualization of relevant ROIs over multiple scans, and we suggest that it can be used as an adjunct to conventional 2D viewing software from scanner vendors.
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer
Publisher: Springer Nature Switzerland
Date: 2023
Regularized Fuzzy Discriminant Analysis for Hyperspectral Image Classification With Noisy Labels
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Dense and Sparse Labeling With Multidimensional Features for Saliency Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2018
EAPT: Efficient Attention Pyramid Transformer for Image Processing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
A propagation-DNN: Deep combination learning of multi-level features for MR prostate segmentation
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.CMPB.2018.12.031
Abstract: Prostate segmentation on Magnetic Resonance (MR) imaging is problematic because disease changes the shape and boundaries of the gland and it can be difficult to separate the prostate from surrounding tissues. We propose an automated model that extracts and combines multi-level features in a deep neural network to segment prostate on MR images. Our proposed model, the Propagation Deep Neural Network (P-DNN), incorporates the optimal combination of multi-level feature extraction as a single model. High level features from the convolved data using DNN are extracted for prostate localization and shape recognition, while labeling propagation, by low level cues, is embedded into a deep layer to delineate the prostate boundary. A well-recognized benchmarking dataset (50 training data and 30 testing data from patients) was used to evaluate the P-DNN. When compared it to existing DNN methods, the P-DNN statistically outperformed the baseline DNN models with an average improvement in the DSC of 3.19%. When compared to the state-of-the-art non-DNN prostate segmentation methods, P-DNN was competitive by achieving 89.9 ± 2.8% DSC and 6.84 ± 2.5 mm HD on training sets and 84.13 ± 5.18% DSC and 9.74 ± 4.21 mm HD on testing sets. Our results show that P-DNN maximizes multi-level feature extraction for prostate segmentation of MR images.
DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Kernelized Mahalanobis Distance for Fuzzy Clustering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Machine learning in medical imaging
Publisher: Elsevier
Date: 2020
Importance of Land, family and culture for a good life: Remote Aboriginal people with disability and carers
Publisher: Wiley
Date: 23-12-2020
DOI: 10.1002/AJS4.96
Deep multi-modality collaborative learning for distant metastases predication in PET-CT soft-tissue sarcoma studies
Publisher: IEEE
Date: 07-2019
Multiple Kernel-Based Discriminant Analysis via Support Vectors for Dimension Reduction
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Vision-Based Freezing of Gait Detection With Anatomic Directed Graph Representation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
Abnormality detection in retinal image by individualized background learning
Publisher: Elsevier BV
Date: 06-2020
Step-wise integration of deep class-specific learning for dermoscopic image segmentation
Publisher: Elsevier BV
Date: 2019
Graph Convolutional Dictionary Selection With L₂, ₚ Norm for Video Summarization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Malocclusion Treatment Planning via PointNet Based Spatial Transformation Network
Publisher: Springer International Publishing
Date: 2020
Unsupervised Landmark Detection-Based Spatiotemporal Motion Estimation for 4-D Dynamic Medical Images
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Multi-modality Information Fusion for Radiomics-Based Neural Architecture Search
Publisher: Springer International Publishing
Date: 2020
Classification of Medical Images in the Biomedical Literature by Jointly Using Deep and Handcrafted Visual Features
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
Non-Contact Sleep Stage Detection Using Canonical Correlation Analysis of Respiratory Sound
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2020
Automatic Detection and Classification System of Domestic Waste via Multimodel Cascaded Convolutional Neural Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Individualized Statistical Modeling of Lesions in Fundus Images for Anomaly Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Multi-Level Adversarial Spatio-Temporal Learning for Footstep Pressure Based FoG Detection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2023
Convolutional sparse kernel network for unsupervised medical image analysis
Publisher: Elsevier BV
Date: 08-2019
DOI: 10.1016/J.MEDIA.2019.06.005
Abstract: The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems. Such supervised approaches, however, are difficult to implement in the medical domain where large volumes of labelled data are difficult to obtain due to the complexity of manual annotation and inter- and intra-observer variability in label assignment. We propose a new convolutional sparse kernel network (CSKN), which is a hierarchical unsupervised feature learning framework that addresses the challenge of learning representative visual features in medical image analysis domains where there is a lack of annotated training data. Our framework has three contributions: (i) we extend kernel learning to identify and represent invariant features across image sub-patches in an unsupervised manner. (ii) We initialise our kernel learning with a layer-wise pre-training scheme that leverages the sparsity inherent in medical images to extract initial discriminative features. (iii) We adapt a multi-scale spatial pyramid pooling (SPP) framework to capture subtle geometric differences between learned visual features. We evaluated our framework in medical image retrieval and classification on three public datasets. Our results show that our CSKN had better accuracy when compared to other conventional unsupervised methods and comparable accuracy to methods that used state-of-the-art supervised convolutional neural networks (CNNs). Our findings indicate that our unsupervised CSKN provides an opportunity to leverage unannotated big data in medical imaging repositories.
Biomedical image visualization and display technologies
Publisher: Elsevier
Date: 2020
Automated Prostate Image Recognition and Segmentation
Publisher: CRC Press
Date: 31-10-2019
Learning Shared and Cluster-Specific Dictionaries for Single Image Super-Resolution
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Unsupervised deep transfer feature learning for medical image classification
Publisher: IEEE
Date: 04-2019
Fast and Accurate Retinal Identification System: Using Retinal Blood Vasculature Landmarks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Video summarization via block sparse dictionary selection
Publisher: Elsevier BV
Date: 02-2020
VoxRec: Hybrid Convolutional Neural Network for Active 3D Object Recognition
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image
Publisher: IEEE
Date: 06-2020
Keyframe Extraction From Laparoscopic Videos via Diverse and Weighted Dictionary Selection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Patch Based Video Summarization With Block Sparse Representation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
A web-based multidisciplinary team meeting visualisation system
Publisher: Springer Science and Business Media LLC
Date: 21-05-2019
DOI: 10.1007/S11548-019-01999-X
Abstract: Multidisciplinary team meetings (MDTs) are the standard of care for safe, effective patient management in modern hospital-based clinical practice. Medical imaging data are often the central discussion points in many MDTs, and these data are typically visualised, by all participants, on a common large display. We propose a Web-based MDT visualisation system (WMDT-VS) to allow in idual participants to view the data on their own personal computing devices with the potential to customise the imaging data, i.e. different view of the data to that of the common display, for their particular clinical perspective. We developed the WMDT-VS by leveraging the state-of-the-art Web technologies to support four MDT visualisation features: (1) 2D and 3D visualisations for multiple imaging modality data (2) a variety of personal computing devices, e.g. smartphone, tablets, laptops and PCs, to access and navigate medical images in idually and share the visualisations (3) customised participant visualisations and (4) the addition of extra local image data for visualisation and discussion. We outlined these MDT visualisation features on two simulated MDT settings using different imaging data and usage scenarios. We measured compatibility and performances of various personal, consumer-level, computing devices. Our WMDT-VS provides a more comprehensive visualisation experience for MDT participants.
Improving PET-CT Image Segmentation via Deep Multi-modality Data Augmentation
Publisher: No publisher found
Date: 2020
Learning visual relationship and context-aware attention for image captioning
Publisher: Elsevier BV
Date: 02-2020
Short-Term Lesion Change Detection for Melanoma Screening With Novel Siamese Neural Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Related Organisations
University Of California Los Angeles
Location: United States of America
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