Mathematical Techniques in Medical Imaging

Details

Title

Mathematical Techniques in Medical Imaging

Type

Stage Two

Module code

HPE117

Requirement

Optional

Module objective

By the end of this module the Clinical Scientist in HSST will be able to analyse, synthesise, critically evaluate and apply knowledge with respect to the mathematical techniques used in the formation, reconstruction, processing and analysis of medical images. Such knowledge will be used in a manner consistent with the roles and responsibilities of a Consultant Clinical Scientist to ensure the safety and efficacy of applying these techniques for patients while effectively communicating the limitations of such techniques. The Clinical Scientist in HSST will be able to synthesise and evaluate standard and innovative practices in the acquisition and analysis of medical images for clinical benefit. They will be able to use such mathematical techniques in the development of computer algorithms to solve problems in clinical diagnosis and monitoring of patient therapy.

Knowledge and understanding

By the end of this module the Clinical Scientist in HSST will analyse, synthesise, critically evaluate and master the basis of the advanced mathematical techniques used in the following areas:

• Image acquisition and reconstruction used in current and emerging medical imaging technologies relevant the their practice, for example:
  • computerised tomography (CT);
  • single photon and positron emission tomography (PET);
  • magnetic resonance imaging (MRI);
  • ultrasound imaging;
  • methods for the acquisition and reconstruction of under sampled data in any modality.
• Image enhancement, for example:
  • filtering in the image or frequency domain;
  • pixel- and local operator-based algorithms;
  • adaptive and multi-scale operations.

• Image segmentation, for example:
  • pixel-, region- and edge-based methods;
  • multi-spectral/multi-modal methods;
  • deformable models;
  • pixel classification algorithms;
  • statistical shape analysis.
• Intra- and inter-modality registration of images, for example:
  • landmark-, shape- and intensity-based algorithms;
  • methods for the validation of registration accuracy;
  • methods for the correction of intrinsic spatial and signal distortions;
  • registration to tissue atlases.
• Modelling and simulation in medical imaging in areas relevant to their practice, for example:
  • pharmacokinetic modelling of endogenous or exogenous tracers;
  • Monte Carlo simulation of imaging system performance;
  • model-based quantitative analysis of image quality.

Technical and clinical skills

By the end of this module the Clinical Scientist in HSST will be able to apply and develop the mathematical techniques described above for an array of image acquisition, reconstruction, processing and analysis techniques with the aim of optimising existing imaging methods and developing new analysis approaches with appropriate understanding of the limitations of the methods. The Clinical Scientist will be expected to be familiar with an appropriate programming language to implement the mathematical methods. They will be able to:

• Use mathematical methods to derive quantitative metrics from clinical imaging data.
• Address sources of errors and uncertainty in the application of mathematical models.
• Clearly communicate mathematical methods, results and their critical evaluation using a range of communication channels to different audiences.
• Devise methods to critically evaluate third-party image processing/analysis software packages.

By the end of this module the Clinical Scientist in HSST will develop the necessary clinical skills to critically develop, deploy and evaluate mathematical techniques in medical imaging. For example they will be able to:

• Apply knowledge and understanding of relevant anatomy and physiology, including physiological variability, to the formulation of mathematical algorithms.
• Synthesise the result of the mathematical processing into a suitable format for clinical interpretation.
• Apply mathematical techniques with due regard to the clinical impact of the methods on patients, staff and general public.

Attitudes and behaviours

By the end of this module the Clinical Scientist in HSST will be expected to evaluate their own response to both normal and complex situations. They will also be expected to consistently demonstrate the professional attributes and insights required of a Consultant Clinical Scientist working within the limits of professional competence referring as appropriate to senior staff and will:

• Show respect and behave in accordance with Good Scientific Practice.
• Establish and influence the culture of health and safety in the workplace.
• Have a clear focus on effective patient-centred service delivery, minimising risk and promoting patient safety.