Skip to content

+44 (0) 1622 691 616

Contact Us

Your Cookie Settings.

We’re using cookies as specified in our cookies policy to give you the best experience on our website. You can find out more about which cookies we are using or switch them off by clicking Manage settings

Accept and continueManage settings

Contact Us

+44 (0) 1622 691 616

View navigation

Resource Hub.

You are here:
  1. Home
  2. >
  3. Resource Hub
  4. >
  5. Case Studies
  6. >
  7. Assisting AiSentia with the development of AI-powered CT imaging technology.

Assisting AiSentia with the development of AI-powered CT imaging technology.

AiSentia emerged as a spin-out company from an industry-leading research project at the University of Oxford. Their aim was simple: to alleviate the need for patients undergoing a CT scan to be given an injection of radiological contrast media (RCM). Instead, AiSentia have created a generative AI model that processes CT X-Ray images and enhances them by raising the contrast of the CT images. This improves the visibility of relevant issues within the human body and eliminates the need for RCM. 

The System C Innovation Delivery team were able to translate the software script from the original research project into a robust powerful cloud-based solution.

Read on to find out how System C worked with AiSentia to help them produce a prototype product.

The Problem

CT scans, which take detailed pictures of the inside of a patient’s body, are a very widely used diagnostic tool.

“In the NHS alone, ~6 million CT scans were performed each year (~150 million scans globally/ year).”

Traditionally, an injection of RCM must be administered, which can cause several potential issues.

  • CT images are becoming much harder to analyse as they only show slightly different shades of greys for various tissues.
  • The RCM used is an iodine-based contrast enhancement agent. It is somewhat toxic and cannot be safely distributed to all patients.
  • Neither extremely sick nor elderly people can be offered the agent, due to potential complications.
  • Conducting CT X-Ray imaging using RCM involves a higher processing time. It requires two trips to the scanner, which means the process is both longer, and more expensive.

The Solution

AiSentia have specifically designed an AI based model to help clinicians to detect abdominal aortic aneurysms. This can prove fatal if it is not detected and treated at an early stage. The newly developed AI software enhances the contrast of the images without RCM and automatically detects the aorta by producing a 3D model of the blood vessel from the CT images. The AI generated model then accurately measures the diameter of the aorta and automatically alerts the user if it exceeds the safe limits.

This innovative solution developed by AiSentia is set to revolutionise CT scanning.

CT scan

What Did System C Do?

 System C’s Innovation Delivery team has partnered with AiSentia to develop a working prototype, to enable the application to be deployed within the healthcare sector.

The Innovation Delivery team has developed a secure, user-friendly web front end and a desktop bulk tool to help support the deployment of the application and enhance the accuracy of CT scans. These prototypes will undergo rigorous testing throughout all key stages within its lifecycle. The software processing will be cloud based, which enables data to be effortlessly synchronised and will help to optimise data flow. Whilst cloud processing allows a streamlined communication process it also helps to increase security and protect patient data as well as making it more accessible to clinicians. 

aisentia-jobs

A detailed look at the app jobs page which allows users to track job status.

System C’s product team helped establish a Python script from AiSentia’s MATLAB code which enabled the generation of contrast enhancements of the affected areas of the body. Although AiSentia’s model is not yet available for clinical use, a prototype of the product was forged. As a result of the collaboration AiSentia now have an excellent quality prototype of their image enhancement system, which is suitable for further development as a medical device. By generating a prototype of AiSentia’s vision System C can gauge production costs, test functionalities, and gain constructive feedback from clinicians and regulators. This prototype gives AiSentia a strong platform to support clinical validation for their approach.

"We were able to convert the python pipeline in such a way that we could host it on a generic cloud platform, without requiring a GPU or other specialised hardware."

 Achievements

 AiSentia’s technology successfully eliminates the need for harmful contrast agents which cause discomfort and unnecessary radiation exposure. It also provides a pathway to seamlessly integrate into the current clinical workflow.

 By achieving AiSentia’s vision, CT and X-Ray scans can become more efficient and help radiology departments raise their productivity by up to 100%.

 James Greig, our lead product developer shared his thoughts on AiSentia’s solution,

"This software could provide huge support for radiographers; it would help them to save time, investigate more cases, and thus save more lives."

aisentia-zoomed-in-viewA single enhanced image, expanded to full screen.

Next Steps

Discover more success stories by checking out our extensive selection of case studies.

We are experienced in developing complex software solutions for the healthcare industry. Please contact us to discuss your ideas, we would love to hear from you.

Other Related Content

AI Hackathon_2

News

Innovating Healthcare with AI - System C's AI Hackathon.

On Wednesday 14th and 15th February in Liverpool we hosted our very first Hackathon at System C.

A Hackathon is an event where people engage in a collaborative engineering initiative over a brief period, typically between 24 and 48 hours. The event starts with a brief of the key objectives, as well as the specific details of the Hackathon. At the end of the Hackathon a series of demonstrations takes place where each group who took part shares and presents their results to the wider team. This allows people to share their ideas and processes to help develop future ideas.

ParkAI-screenshots

Case Studies

Park AI – Using AI to Help Clinicians Monitor Parkinson’s Disease.

Artificial intelligence (AI) has become a critical tool to effectively process this immense amount of data, making machine learning algorithms part of our daily lives. Whenever you use Google, sat nav or social media, AI is working in the background to make your user experience more relevant, efficient and valuable.