MSc Medical Visualisation & Human Anatomy School of Innovation & Technology

Shona Cumming

(She/Her)

Hello, my name is Shona Cumming, and I am a Neuroscience graduate (BSc Hons) from the University of Glasgow. During my undergraduate studies, I discovered a passion for neuroanatomy, medical imaging, and science communication. A pivotal moment in my academic journey came during my third year of undergrad when I attended a talk by the founder of Axial3D. This presentation sparked my interest in advancing personalised medicine through the innovative use of 3D imaging technology. Inspired by this experience, I decided to further my education by pursuing a Master’s in Medical Visualisation and Human Anatomy.

Over the past year, I have thoroughly enjoyed expanding my skill set and learning about a diverse range of disciplines, including: volumetric visualisation, 3D modelling, and app development. All of which are integral to the field of medical visualisation. My studies have also provided me with hands-on experience in cadaveric dissection, allowing me to gain a comprehensive understanding of human anatomy that goes beyond theoretical knowledge.

I look forward to applying the skills and knowledge I have gained from the Master’s as I embark on a career as a Biomedical Imaging Scientist. I am excited about the potential to contribute to the advancement of personalised medicine, using innovative imaging techniques to enhance patient care and outcomes.

Contact
shonacummingx@gmail.com
S.Cumming1@student.gsa.ac.uk
Works
Interactive Visualisation
Thesis Project: Comparison of CT to 3D vs X-ray to 3D
Volumetric Visualisation
3D Modelling

Interactive Visualisation

“You and Your Colon” was a collaborative project developed by myself and two of my very talented colleagues, Hannah Milne and Summer Skelton. This app is an interactive public health awareness campaign, designed to educate the general public about the normal function of the colon and the development of colon cancer, with a focus on promoting colon cancer screening. The app was built using Unity and coded in C#.

Main menu

Screenshot of the 3D model information scene

Screenshot of the polyp development animation scene

Screenshot of the polyp removal scene where the user drags a tool over to a polyp to remove it

Screenshot of the scrollable risks and symptoms page

Screenshot of the drag and drop scene with timer and feedback

Screenshot of the quiz scene

Screenshot of the quiz instant feedback

You and your colon play though

Thesis Project: Comparison of CT to 3D vs X-ray to 3D

My thesis project was conducted in collaboration with Axial3D, a leading company in the medical visualisation field. The project was developed in response to a frequently posed question by Axial3D’s customers: Is it possible to create clinically accurate 3D reconstructions from X-rays?

3D reconstructions of human anatomy are a transformative technology with a wide range of applications, particularly in advancing personalised medicine in orthopaedics. They are especially valuable for surgical planning and the development of medical devices. While CT scans are currently the gold standard for generating 3D reconstructions, X-rays often provide sufficient diagnostic information for many medical conditions. Biplanar X-rays, typically captured from anteroposterior and lateral views, offer an enhanced perspective of the anatomy being examined. This project aimed to compare the accuracy of 3D knee reconstructions derived from CT scans versus those from biplanar X-rays for patient-specific applications, with careful consideration given to the biplanar X-ray 3D reconstruction method.

Axial3D utilised machine learning algorithms to automatically segment the bones of the knee from both CT and biplanar X-ray data to create label maps. I derived models of the bones from the label maps using 3DSlicer and processed them in MeshLab. Quantitative analysis was then undertaken to assess the accuracy of the biplanar X-ray predictions compared to the CT predictions. Two different approaches were taken to the quantitative analysis in MeshLab to provide a comprehensive comparison of the models. The findings of this study were then evaluated within the context of surgical planning and medical device companies.

I would like to express my gratitude to my supervisors, Dr. Claire Fitton, Dr. Matthieu Poyade, and Helen McGhee, for their guidance throughout the project. Additionally, I would like to thank the rest of the team at Axial3D for their support and the opportunity to collaborate with them on this project.

 

Distance From Reference Mesh

CT vs Biplanar X-ray

Biplanar vs CT Choropleth Maps

Patella Outlier

Fibula Animation

Model Comparison

Biplanar Models of the Knee

Femur Animation

CT Choropleth Map

Biplanar Choropleth Map

Thesis Project Presentation

Volumetric Visualisation

Volumetric visualisation was my favourite module in the medical visualisation course. The following images were derived from CT and MRI data using 3DSlicer and MITK, combining indirect and direct volume rendering techniques.

Pre-Op Pelvis

Post-Op Pelvis

Tooth: Direct Volume Render

Tooth: Indirect Volume Render

Brain Tumor: Axial and Coronal Section

Activity of the Tumor from fMRI Data

Right Lung Tumor Attachment Point

Lung Tumors

3D Modelling

“Anatomy of the Underarm Throw” was created for the 3D modelling module using 3DSMax and Zbrush. I initially felt apprehensive about this project due to my limited background in art. Despite the challenges, this experience provided me with a valuable understanding of the 3D modelling process, as well as insights into animation and rendering. This project also emphasised the interdisciplinary nature of 3D modeling, showcasing how it draws on multiple fields to create a cohesive final product.

Anatomy of the Under Arm Throw

Hand close up

Bicep close up

Preliminary bicep

Hand and Humerus Sculpt

Bicep Sculpt