Smart Medical Imaging

EPSRC Centre for Doctoral Training

Students

MRes Programme Structure

The CDT in Smart Medical Imaging will adopt a flexible training approach. However, most students will normally follow a 1+3 pathway (1-year MRes at King’s, followed by 3-year PhD at King’s or Imperial).

Year 1 - MRes Healthcare Technologies: This new programme will incorporate rigorous research training, exposure to the clinical imaging challenges and regulatory processes and clinical and commercial translation, providing the students with the skills and cross-disciplinary knowledge required to successfully complete their PhD in years 2-4. During the MRes all students are registered at King's with the taught elements of the programme delivered by King’s academics, with select modules featuring Imperial academics to showcase their research on relevant module topics.

The programme includes one common module, one interdisciplinary group project, one individual research project and specialist elective modules from the relevant pathways of: Medical Imaging, Medical Artificial Intelligence, Medical Devices & Robotics and Smart Molecules.

Core module (30 credits):

  • Critical Skills for Translational Healthcare Technologies (30 credits)

The primary aim of this module is to widen awareness of the local and global healthcare technology environment. The course will develop students’ transferrable skills for critical discussion, written review, presentation skills and creative and reflective communication.

Research projects (90 credits):

  • Extended Group Research Project in Healthcare Technologies (30 credits)
  • Extended Individual Research Project in Healthcare Technologies (60 credits)

All students will undertake two research projects. The first project is a group project with three or four students per group. This approach challenges the students to work on an interdisciplinary project. Supervision of this project will be assisted by senior students alongside academic supervisors. This ensures strong involvement of different student generations within the Centre. The project is assessed through a group presentation and an individual report. The second project is an individual research project.

Optional modules within a Pathway (60 credits):

These modules will ensure deep knowledge in a specific area, with applications for a range of potential research projects. Students can also attend modules from other pathways, should their timetables permit, without formal assessment.

  1. Medical Artificial Intelligence
  • Machine Learning for Biomedical Applications (15 credits)

The module will provide the students with a fundamental grounding in the theoretical and computational skills required to apply machine learning tools to real-world problems. It will provide an understanding of the application of these skills to explore complex high-dimensional data sets, providing an overview of active research areas in machine learning, with biomedical applications.

  • Scientific Programming (15 credits)

This module provides the practical skills necessary for all students interested in machine learning, medical imaging, medical robotics and devices to become proficient and capable at efficiently generating code, robustly recording modifications and effectively optimising their programs individually and within a team. Students will be trained in modern programming languages and their integration into healthcare environments.

  • Advanced Machine Learning (15 credits)

This module will educate students with regards to novel artificial intelligence algorithms for the analysis and predictive modelling of multiple types of healthcare data such as medical images, genetics, clinical/epidemiological variables, and free text. Topics will be learned through a combination of lectures, individual and group lab work and assignments.

  • Medical Image Computing (15 credits)

This module cover topics related to biological and computer vision, image transformations, image processing (enhancement, filtering, edge detection, feature extraction), image segmentation, registration and model-based image analysis.

  • Medical Imaging in Clinical Applications (15 credits)

This module aims to instil an appreciation of the clinical applications of medical imaging. This will include an introduction to the state of art of non-invasive cardiovascular imaging in clinical routine, to the state of art of perinatal imaging (foetus, preterm infant and infants) and to the state of art of neurological imaging in clinical routine.

  1. Medical Imaging
  • Medical Image Acquisition (15 credits)

This module provides detailed knowledge of imaging with non-ionising (MRI, ultrasound) and ionising radiation (CT, SPECT, PET).

  • Medical Image Reconstruction (15 credits)

This module covers mathematical concepts of inverse problems with examples of image reconstruction for CT, PET and MRI.

  • Medical Image Computing (15 credits)

This module covers topics related to biological and computer vision, image transformations, image processing (enhancement, filtering, edge detection, feature extraction), image segmentation, registration and model-based image analysis.

  • Medical Imaging in Clinical Applications (15 credits)

This module aims to instil an appreciation of the clinical applications of medical imaging. This will include an introduction to the state of art of non-invasive cardiovascular imaging in clinical routine, to the state of art of perinatal imaging (foetus, preterm infant and infants) and to the state of art of neurological imaging in clinical routine.

  • Advanced MR Imaging (15 credits)

This module aims to provide a deeper analysis of the physics of MRI for those who will be developing and using advanced MRI techniques.

  1. Smart Molecules
  • Imaging Biology 1 (15 credits)
  • Imaging Biology 2 (15 credits)

These two modules provide detailed knowledge of radio-pharmacology for design, formulation and application of tracers to biological systems (pharmacokinetic, toxicity, dosimetry, cell and animal models, ethics of preclinical research).

  • Imaging Chemistry 1 (15 credits)
  • Imaging Chemistry 2 (15 credits)

These two modules provide fundamental principles of imaging chemistry and metal chelates for different imaging modalities, including bio-conjugate chemistry, nano-particulate probe chemistry and photochemical probes.

  • Medical Imaging in Clinical Applications (15 credits)

This module aims to instil an appreciation of the clinical applications of medical imaging. This will include an introduction to the state of art of non-invasive cardiovascular imaging in clinical routine, to the state of art of perinatal imaging (foetus, preterm infant and infants) and to the state of art of neurological imaging in clinical routine.

  1. Medical Devices & Robotics
  • Scientific Programming (15 credits)

This module provides the practical skills necessary for all students interested in machine learning, medical imaging, medical robotics and devices to become proficient and capable at efficiently generating code, robustly recording modifications and effectively optimising their programs individually and within a team. Students will be trained in modern programming languages and their integration into healthcare environments.

  • Medical Robotics: Theory and Applications (15 credits)

This module provides the relevant knowledge in the field of surgical robotics, both in terms of the contemporary use of surgical robots and the mathematical and computational theory behind them.

  • Medical Technologies: Design and Development (15 credits)

This module provides an overview of medical technology conception, creation and commercialisation with a focus on medical devices and diagnostics; a thorough understanding of regulatory processes involved in taking medical devices from conception to commercialisation; the skills and knowledge to apply human centric design process in discovering unmet clinical needs, defining constraints of the healthcare system, designing appropriate solutions and developing prototypes.

  • Medical Robotics: Hardware Development (15 credits)

This modules will enable students to understand, evaluate and apply the practical aspects of robot development, combining concepts of computer-aided design, 3D printing, manufacturing and system integration.

  • Software and Robotic Integration (15 credits)

The overarching educational aim of this module is to give the students the skills and knowledge required to develop a complete system for a robotic image guided therapy combining different imaging modalities.