Hui Cui's HomePage

About Me

I am a Senior Lecturer at La Trobe University. Before joining La Trobe, I was a Research Fellow at School of Computer Science, The University of Sydney (2016 ~ 2018). I received my PhD and MPhil degrees in Computer Science with specialization in Medical Image Computing from The University of Sydney, Australia in 2016 and 2013 under the supervision of Prof David Dagan Feng, A/Prof Xiuying Wang and Clinical Professor Michael Fulham. I also worked closely with Dr Jianlong Zhou from UTS in graph topology. I obtained my Bachelor of Engineering degree from Harbin Institute of Technology (China C9 University) in 2011.

My research area is in Biomedical Image Analysis, Machine Learning, Deep Learning, and Biomedical and Health Informatics. My current research mainly focuses on

Integration of Imaging with Non-Imaging Biomarkers

Segmentation in biomedical images

Cancer analysis in histopathology images

Graph theory and neural network

AI for precision oncology, early diagnosis and prognosis of disease and cancer, etc.

I also work closely with industry partners, clinicians and radiologists from major hospitals in China and Australia to translate the developed medical technologies into clinical workflow and industry applications.

If you are a self-motivated student with proficient programming skills and strong interests in the research directions, please send me your CV.

News

Mar 2024: One paper accepted in IEEE Transactions on Medical Imaging (IEEE TMI) (CORE A*). [ code ]
Mar 2024: One paper accepted for oral presentation in ICME 2024
Jan 2024: One paper accepted in Bioinformatics
Jan 2024: One paper accepted in ISBI 2024
Oct 2023: I was promoted to Level C Senior Lecturer (equiv. to Associate Professor in North American system) !
Oct 2023: Two papers accepted in BIBM 2023. The implementation of "MGCT: Mutual-Guided Cross-Modality Transformer for Survival Outcome Prediction using Integrative Histopathology-Genomic Features" can be found via [ MGCT code]
Oct 2023: One paper accepted in Expert Systems with Applications.
May 2023: One paper early accepted in MICCAI 2023 (ERA Core A). [ code]
Jan 2023: I started the leadership role of Department Teaching & Learning (T&L) Coordinator.
Dec 2022: One paper accepted in International Journal of Radiation Oncology - Biology - Physics (Red Journal).
Nov 2022: One paper accepted in Applied Soft Computing.
July 2022: One paper in MICCAI 2022 - CDMRI Workshop
May 2022: Two papers early accepted in MICCAI 2022 (ERA Core A)
Jan 2022: I was appointed as the course coordinator of all our department's postgraduate degrees (except Cyber)
Dec 2021: One paper accepted in IEEE Journal of Biomedical and Health Informatics (IEE JBHI) (CORE A*)
Oct 2021: One paper accepted in IEEE Journal of Biomedical and Health Informatics (IEE JBHI) (CORE A*)
Sep 2021: One paper accepted in IEEE Transactions on Visualization and Computer Graphics (IEE TVCG) (CORE A)
Aug 2021: One paper accepted in Knowledge based system. [ code]
July 2021: One paper accepted in Medical Image Analysis
July 2021: One paper in MICCAI 2021 - CDMRI Workshop
July 2021: Four papers accepted in IJCNN (Core B) and EMBC
June 2021: One more paper accepted in MICCAI 2021 (ERA Core A)
May 2021: My first-authored papers early accepted by MICCAI 2021 (ERA Core A)
Mar 2021: One paper accepted in Expert Systems with Applications. [ code]
Nov 2020: One paper accepted in Applied Soft Computing. [ code]
June 2020: My first-authored paper accepted in MICCAI 2020 (ERA Core A)
Mar 2019: I moved to Melbourne and joined La Trobe University as a lecturer in Interactive Digital Media (equiv. to Assistant Professor in North American system)

Selected Publications

Jin Q, Zou C, Cui H, et al, "Multi-modality contrastive learning for sarcopenia screening from hip X-rays and clinical information", MICCAI 2023. [ paper & code]

Du M, Cui H*, et al "Learning from Deep Stereoscopic Attention for Simulator Sickness Prediction", IEEE TVCG 2023.

Jin Q, Cui H, et al "Semi-supervised histological image segmentation via hierarchical consistency enforcement", MICCAI 2022

Guan Y, Cui H, et al "Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network", MICCAI 2021.

Cui H, Xuan P, et al "Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction", MICCAI 2021.

Jin Q, Cui H, et al, "Domain adaptation based self-correction model for COVID-19 infection segmentation in CT images", Expert Systems with Applications, 2021. [ paper & code]

Jin Q, Cui H, et al, "Free-form tumor synthesis in computed tomography images via richer generative adversarial network", Knowledge-Based Systems, 2021. [ paper & code]

Jin Q, Cui H, et al, "Cascade knowledge diffusion network for skin lesion diagnosis and segmentation", Applied Soft Computing, 2020. [ paper & code]

Cui H, Xu Y, et al, "Collaborative Learning of Clinical Attention for Radiotherapy-related Esophageal Fistula Prediction from CT", International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020. (ERA Core A) [paper]

Cui H, Wang X, Zhou J, Gong G, Eberl S, Yin Y, Wang L, Feng D, and Fulham M, "A topo-graph model for indistinct target boundary definition from anatomical images", Computer Methods and Programs in Biomedicine, 2018. [paper]

Cui H, Wang X, Zhou J, Eberl S, Feng D, and Fulham M, "Improved segmentation accuracy for thoracic PET-CT in patients with NSCLC using a multi-graph model (MGM)", Journal of Nuclear Medicine, 2015. Best paper award. [paper]

Cui H, Wang X, Zhou J, Eberl S, Feng D, and Fulham M, "Topology polymorphism graph for lung tumor segmentation in PET-CT images", Physics in Medicine and Biology, 2015. . [paper]

Research Awards

Our research received a list of international research awards including:

Chinese government award for outstanding students abroad, by China Scholarship Council , 2015;

International best absctract award for Australia, by Society of Nuclear Medicine and Molecular Imaging (SNMMI), 2015

Two best oral presentation awards at SNMMI 2015, by Education and Research Foundation and The PET Centre of Excellence of SNMMI.

Teaching

Department Teaching & Learning Coordinator, Department of CS & IT, La Trobe University, 2023-.
Postgraduate Course Coordinator (Master of AI, Master of IT, Master of ICT), Department of CS & IT, La Trobe University, 2022-.
Developer, Coordinator, Lecturer, “Computer Vision”, Department of CS & IT, La Trobe University, 2021-2022.
Coordinator, Lecturer, “Data Mining”, Department of CS & IT, La Trobe University, 2020-.
Developer, Coordinator, Lecturer, “Image Retrieval”, Department of CS & IT, La Trobe University, 2020-2022.
Developer, Coordinator, Lecturer, “Image Processing”, Department of CS & IT, La Trobe University, Semester 1, 2019- 2022.
Guest Lecturer, “Software Development in Java (COMP9103)”, School of Computer Science, The University of Sydney, 2017-2019.
Teaching Assistant, “Software Development in Java (COMP9103)”, School of Computer Science, The University of Sydney, 2014-2018.

Scientific Community Service

Conference Services

Senior Programme Committe: CIKM 2024

Programme Committe: DICTA 2017, CGI 2023, CASA 2024

Reviewer: ICME 2024, MICCAI (2020, 2021, 2022, 2023, 2024)

Journal Reviewer:

Review Editor: Frontiers in Bioinformatics - Integrative Bioinformatics

Pattern Recognition

IEEE Journal Of Biomedical & Health Informatics

IEEE Transactions on Medical Imaging (TMI)

IEEE Transactions on Biomedical Engineering (TBME)

Computerized Medical Imaging and Graphics

Computer Methods and Programs in Biomedicine

Physics in Medicine & Biology

Computers in Biology and Medicine

Medical Physics

Radiation Oncology

International Journal of Computer Assisted Radiology and Surgery

Invited Talks

"Improved segmentation accuracy for thoracic PET-CT in patients with NSCLC using a multi-graph model", The Australian and New Zealand Society of Nuclear Medicine (ANZSNM) meeting, Rotorua, New Zealand. April 2016