Welcome to the website of HELiCoiD: HypErspectraL Imaging Cancer Detection.
HELICoiD is a European collaborative project funded by the Research Executive Agency, through the Future and Emerging Technologies (FET-Open) programme, under the 7th Framework Programme of the European Union.
The project is a collaboration between four universities, three industrial partners and two hospitals.
It's aim is to use hyperspectral imaging for real-time identification of tumour margins during surgery, helping the surgeon to extract the entire tumour and to spare as much of the healthy tissue as possible.
Hyperspectral imaging is a non-contact, non-ionizing and minimal-invasive sensing technique. Whereas a conventional camera captures images in three colour channels (red, blue and green), a hyperspectral camera captures data over a large number of contiguous and narrow spectral bands, and over a wide spectral range. For this reason it is sometimes known as imaging spectroscopy. Rather than a single image, we instead obtain a data-cube: a stack of images collected at different wavelengths. Each pixel contains an entire spectrum of data.
Real-time Cancer Detection
Starting with some specific types of cancers, HELICoiD is developing a methodology to discriminate between healthy and malignant tissues in real-time during surgical procedures.
Using a dataset of hyperspectral images of healthy and cancerous tissue, an algorithm is being trained to detect differences in their spectral signature using machine learning techniques. The algorithm is then being applied to identify cancerous and healthy tissue in hyperspectral images acquired during surgery. In the future, this information could be provided to the surgeon in real time by overlaying conventional images with a colour-map that indicates the likelihood of that particular area being cancerous.
One of the major applications is likely to be in neurosurgery. While malignant primary brain tumours rank only 13th in the list of cancer incidence rates, their particularly poor prognosis results in them being the fifth most common cause of cancer deaths in under 65s. Among children, they are the second most common form of cancer and the most common cause of cancer death.
Brain tumours, more than any other cancers, can resemble normal neurological tissue, making them difficult to differentiate. Unlike many tumours, they infiltrate the surrounding tissue and their borders are indistinct and difficult to identify. Yet in the brain it is essential to correctly identify the boundary so as to protect the surrounding brain tissue.
The HELICoiD demonstrator system, shown here, was assembled in 2015, and is now being used to capture neurosurgical images in our two partner hospitals. In 2016, dedicated processing hardware was added to allow the HELICoiD image analysis algorithms to run in real time.
Beyond the brain, the project will also look to extend the methods developed to other cancers, and particularly to cancers of the lung and the breast.