This module covers the generalist practicing skills defined in the competencies for Dental Practitioner with a Specialist Interest. As well as lectures...

This module covers the generalist practicing skills defined in the competencies for Dental Practitioner with a Specialist Interest. As well as lectures covering the generalist topics (clinical record keeping, infection control, legislation and good practice guidelines, radiography, and risk management) participants will have to carry out an audit project in their own practices covering one of the topics above.

INDEPENDENT STUDY MODULE|EDUCATION ADVANCED PRACTICE

This module allows participants to study something of their own interest or to consider the work they may have done in a recent non-accredited CPD.
A series of...

This module allows participants to study something of their own interest or to consider the work they may have done in a recent non-accredited CPD.
A series of ten activities supports participants in choosing and focusing engagement with an idea or concept. The module then moves on to think about each participant as a learner and what hinders learning, before returning to the investigation to support learners in finding their own readings in the field of study – the course team will also share some to start participants going!

The module is taught online and can be taken in either the Autumn term, or Spring term or Summer term in 2022-23.
This module belongs to the MA Advanced Educational Practice, MA Education (Advanced Practice) and the Graduate Diploma in Advanced Educational Practice programmes.
Contact ioe.aep@ucl.ac.uk for further information.

Aims:

The module aims to give the students an in-depth introduction to Magnetic Resonance Imaging (MRI) from the computational perspective.

Learning...

Aims:

The module aims to give the students an in-depth introduction to Magnetic Resonance Imaging (MRI) from the computational perspective.Learning outcomes:

On successful completion of the module, a student will be able to:

Understand, in-depth, MRI through learning and implementing, in silico, all the key components of modern MRI systems.
	Gain significant experience in software development for general scientific computing and visualisation.
Content:

Introduction to magnetic resonance imaging.
	Classical description of a magnetic field acting on a single nucleus (equation of motion; rotating frame of reference; concept of magnetic resonance).
	Macroscopic magnetization (concept of relaxation; the Bloch equation).
	Introduction to signal detection and acquisition (free induction decay; spin echoes; inversion recovery; spectroscopy).
	Fourier imaging: the MR physics perspective (k-space; gradient echoes; slice excitation).
	Fourier imaging: the signal processing perspective (fundamentals of continuous and discrete Fourier transforms; sampling theory; image reconstruction).
	Noise modelling and contrast mechanisms.
Requisites:

To be eligible to select this module as an option or elective, a student must: (1) be registered on a programme and year of study for which it is a formally available; and (2) have suitable experience with Matlab.