Andrew Mehnert

Dr

  • The University of Western Australia (M010), 35 Stirling Highway,

    6009 Perth

    Australia

  • Source: Scopus
  • Calculated using citation counts from Scopus for publications in the UWA Profiles and Research Repository
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Personal profile

Biography

Andrew obtained his PhD in electrical engineering from the University of Queensland (UQ) in 2004 – Thesis: “Image analysis for the study of chromatin distribution in cell nuclei with application to cervical cancer screening”. He subsequently held the positions of Research Fellow and then Senior Research Fellow in medical image analysis in the School of Information Technology and Electrical Engineering at UQ. From 2011 until his present appointment at UWA, he held the positions of Assistant Professor and then Associate Professor in medical image analysis jointly with the MedTech West centre (located at Sahlgrenska University Hospital, Gothenburg, Sweden) and the Department of Signals and Systems at Chalmers University of Technology.

Roles and responsibilities

Senior Lecturer, Group Leader - Data Management, Analysis and Visualisation

Responsible for introducing, developing and applying data management, analysis and visualisation expertise in collaboration with researchers using microscopy and imaging techniques across various disciplines at UWA

Funding overview

2017: Andrew Mehnert, Kirk Feindel, 'Delivering durable, reliable, high-quality image data', Monash University ex NCRIS Australian National Data Service (118,000 AUD)

2017: Andrew Mehnert, 'Delivering Durable Reliable High Quality Image Data', University of Queensland ex NCRIS Australian National Data Service ANDS (80,000 AUD)

2017: Andrew Mehnert, Andrea Holme, 'Scientific Desktops in the Cloud', Monash University ex EIF/NCRIS National e-Research Collaboration Tools and Resources NeCTAR (46,000 AUD)

2011-2014: EU Marie Curie CIG - "Improved detection and characterisation of breast cancer using multimodal magnetic resonance imaging and novel computer-aided detection/evaluation (CADe) techniques" (87,500 EUR)

2012: Chalmers University of Technology Chalmerska forskningsfonden (12,000 SEK)

2008: QCIF - "Automated Segmentation of the Thigh Musculature for Clinical MRI Investigations into Muscle Asymmetry Using HPC" (33,969 AUD)

2007-2009: ARC-Linkage - "Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology” (501,000 AUD)

2007: QCIF - "Segmentation of Thoracolumbar Muscles from MRI: Morphometric Analysis and
3D Visualisation" (40,000 AUD)

2006: UQ Major Major Equipment and Infrastructure Grant - “An automated microscope for quantitative and virtual microscopy” (128,000 AUD)

2006: UQ Early Career Research Grant - “Improved detection and characterisation of breast cancer using magnetic resonance imaging and advanced computer image analysis and pattern recognition techniques” (20,000 AUD)

2005: QPSF - “Improved breast cancer detection enabled by rapid visualisation of suspicious lesions in DCE-MRI of the breast” (40,000 AUD)

2005: ARC - "Improved early detection of breast cancer enabled by grid-computing and advanced modelling and visualisation of MR images" (55,000 AUD)

Previous positions

3/6/2014 - 26/10/2014: Associate Professor / Docent in Medical Image Analysis, Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden

14/2/2011 - 2/6/2014: Assistant Professor in Imaging, Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden

14/2/2011 - present: Adjunct Senior Research Fellow (medical image analysis), School of ITEE, The University of Queensland, Australia

1/1/2008 - 13/2/2011: Senior Research Fellow (medical image analysis) / Affiliate Academic, School of ITEE, The University of Queensland, Australia

1/1/2005 - 31/12/2007: Research Fellow (medical image analysis), School of ITEE, The University of Queensland, Australia

Research

Andrew’s research interests focus on the development of image analysis methods for biomedical imaging applications involving MRI, CT and optical microscopy. Such methods include visualisation, denoising, spatial co-registration, segmentation, parametric modelling of contrast enhancement (DCE-MRI), computational diffusion MRI and classification (feature extraction, feature selection and classifier design, training and validation).

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