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Andromeda: “Automated Organ Segmentation and 3D Reconstruction for Medical Imaging”

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  • Full or part time
    Dr Villarini
    Dr Getting
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

The aim of this PhD project is to join image processing and computer vision techniques with medical and biological information, in order to develop an innovative tool for automatic segmentation and 3D reconstruction and visualisation of organs from medical images. The project will have an impact on promoting population health, since automatic segmentation of organs is a crucial and challenging task for improving computed aided diagnosis and laparoscopic surgery assistance, and it can also support radiologist in the daily routine.

The visual inspection slice-by-slice of ultrasound (US), computed tomography (CT) and magnetic resonance (MR) images, requires high skills and concentration and is very time-consuming and expensive. Thus, automatic medical image segmentation is needed to identify the target anatomy and delineate the boundary of the region of interest. This step would enable doctors and researchers to display and manipulate the information in a fast and easy way facilitating further analysis. The expertise gained by the DoS over the last few years, working as researcher on the development of an innovative image guidance system in the Centre for Medical Image Computing (UCL), can be transferred on the realisation of this project. Working within an interdisciplinary research team, the PhD project involves the design and development of automatic segmentation methods for organs and their 3D reconstruction and visualisation. The PhD student will have access to a large database of medical image through our access to UK Biobank, where the student will be able to test, in conjunction with parallel imaging, the different approaches that will be developed during the PhD programme. The PhD candidate will gain experience in medical image analysis and computer vision techniques and will learn how to apply mathematical and computational methods for solving problems in medical imaging field. Additionally the student will take part in the Faculty Doctoral Research Programme and the Graduate School Programme, and will be trained to gain important transferable skills for a future research career progression.

Funding Notes

The Studentship consists of a fee waiver and a stipend of £16,000 per annum. Successful candidates will be expected to undertake some teaching duties.

References

Related publications

E. Bonmati, Y. Hu, R. Rodell, B. Villarini, P. Martin, L. Han, I. Donaldson, H.U. Ahmed, C.M. Moore, M. Emberton, D.C. Barratt , Validation of the needle targeting accuracy of a MRI/TRUS- image-guided system for transperineal prostate cancer biopsy, (2015) CARS-Computer Assisted Radiology and Surgery, 29th International Congress and Exhibition, ISNN 1861-6410 10 (1) (Suppl 1):S181–S182.

A. Angelopoulou, A. Psarrou, and J. Rodriguez, S. Orts-Escolano, J. Azorin-Lopez, Jorge, K. Revett, 3D Reconstruction of Medical Images from Slices Automatically Landmarked with Growing Neural Models. Neurocomputing, 150 (A). pp. 16-25, 2015 ISSN 0925-2312.

Smith L, Thomas EL, Hamer M, Bell JD.The association between objectively measured sitting and standing with body composition: A pilot study using magnetic resonance imaging. BMJ Open 2014; 4:e005476.

How good is research at University of Westminster in Computer Science and Informatics?

FTE Category A staff submitted: 19.65

Research output data provided by the Research Excellence Framework (REF)

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