New methodology to quantify biological structures from 2D or 3D images

ANU researchers have developed a new methodology for quantifying the morphology of 2D or 3D images from the brain, neurons, capillary and blood vessel networks.

Background

A growing number of imaging technologies are producing huge volumes of 3D data about biological structures (brain, neurons and blood vessel networks) but the development of analysis tools is lagging behind the technology. Imaging technologies include Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-ray (for coronary angiography), Optical Coherence Tomography (OCT) in particular OCT-angiography of retinal vessels and capillaries, and Microscope data (confocal, multi-photon, etc). The quantification of biological materials by 3D imaging technologies can provide information that could be used by a doctor to achieve diagnosis of a disease or disorder along with results from clinical tests. Improved analysis methodologies are needed to interpret and quantify this data for diagnosis and management of diseases.

Technology

ANU researchers have developed novel morphometric analysis methods for emerging types of 3D data images, in particular images from biological specimens. An extension of the method produces accurate models of 3D images of tubular networks such as capillaries or neurons to which the novel segmentation analysis is applied. Data types to which the new methods can be applied include 3D output from microscopy, optical coherence tomography, cardio-angiography, and magnetic resonance imaging. The methods can be applied to brain images or angiography. The methods are extendable to higher dimensional data such as 3D movies (i.e. 4D). The new morphometric methods exploit higher-order, multi-dimensional, spatial correlations in the image data to provide novel measures that have proved to be more informative than conventional measures such as area or volume. The methods are computationally efficient and convenient.

Advantages

  • Produces accurate 3D models of the tubular vessel network or similar structures
  • Enables quantification of the vessel network from the 3D model
  • Method of quantification is unique and incorporates information related to:
    • measures of vessel surface area
    • measures of vessel curvature - related to resistance to blood flow, and
    • number of loops which are important in capillary beds and angiogenesis in tumours and macular degeneration
  • Can also quantify non-tubular 3D data such as brain imaging data including to quantify disease severity in multiple sclerosis

Data types to which the new methods can be applied include 3D output from microscopy, optical coherence tomography and magnetic resonance imaging. The methods can be applied to brain images or angiography. Applications include diagnosis and management of a variety of health problems including eye, brain and cardiovascular diseases.

Opportunity

ANU is seeking a partner to assist in further developing this technology, or partners to license this technology.