M. Field

发表

Mixture Model Segmentation for Gait Recognition

Z. Pan, M. Field, D. Stirling, 2008, 2008 ECSIS Symposium on Learning and Adaptive Behaviors for Robotic Systems (LAB-RS).

The role of deep learning and radiomic feature extraction in cancer-specific predictive modelling: a review

M. Field, D. Stirling, M. Carolan, 2018, Translational Cancer Research.

A comparative study of machine learning techniques for the improved prediction of NSCLC survival analysis

M. Field, D. Stirling, M. Carolan, 2018, 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC).

Infrastructure platform for privacy-preserving distributed machine learning development of computer-assisted theragnostics in cancer

M. Field, M. Carolan, D. Thwaites, 2022, J. Biomed. Informatics.

The effect of imputing missing clinical attribute values on training lung cancer survival prediction model performance

Aditya Ghose, Matthew Field, Andre Dekker, 2017, Health Inf. Sci. Syst..

The effect of imputing missing clinical attribute values on training lung cancer survival prediction model performance

M. Field, D. Thwaites, S. Vinod, 2017, Health Information Science and Systems.

A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy

Issam El-Naqa, Matthew Field, Andre Dekker, 2017, Acta oncologica.

Machine learning applications in radiation oncology

M. Field, N. Hardcastle, M. Jameson, 2021, Physics and imaging in radiation oncology.

Implementation of the Australian Computer‐Assisted Theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning

M. Field, A. Dekker, M. Carolan, 2021, Journal of medical imaging and radiation oncology.

Deep learning for segmentation in radiation therapy planning: a review

M. Field, S. Vinod, A. Sowmya, 2021, Journal of medical imaging and radiation oncology.

Using Machine Learning Applied to Radiomic Image Features for Segmenting Tumour Structures

Montserrat Ros, Christian Ritz, Alanna Vial, 2019, 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

Systematic Review of Tumor Segmentation Strategies for Bone Metastases

M. Field, D. Stirling, M. Ros, 2023, Cancers.

Acquisition and distribution of synergistic reactive control skills

Matthew Field, M. Field, 2014 .

Recognizing human motions through mixture modeling of inertial data

Montserrat Ros, Fazel Naghdy, David Stirling, 2015, Pattern Recognit..

Motion capture in robotics review

Fazel Naghdy, Matthew Field, Zengxi Pan, 2009, 2009 IEEE International Conference on Control and Automation.

Human motion capture sensors and analysis in robotics

Fazel Naghdy, David Stirling, Matthew Field, 2011, Ind. Robot.

Multicentre Evaluation of MRI-based Radiomics Features: A Phantom Study.

Yu Sun, Matthew Field, Lois C Holloway, 2020, Medical physics.

Learning Trajectories for Robot Programing by Demonstration Using a Coordinated Mixture of Factor Analyzers

Fazel Naghdy, David Stirling, Matthew Field, 2016, IEEE Transactions on Cybernetics.

Inertial sensing for human motor control symmetry in injury rehabilitation

Montserrat Ros, Fazel Naghdy, David Stirling, 2013, 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

PSPSO: A package for parameters selection using particle swarm optimization

Matthew Field, Martin Carolan, Jonathan Sykes, 2021, SoftwareX.

Motion segmentation for humanoid control planning

Fazel Naghdy, David Stirling, Matthew Field, 2008 .

Assessing the prognostic impact of 3D CT image tumour rind texture features on lung cancer survival modelling

Montserrat Ros, Christian Ritz, Alanna Vial, 2017, 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP).