Product category:
Optical sensors and vision systems
News Release from: Adept Scientific | Subject: Maple
Edited by the Processingtalk Editorial
Team on 07 May 2003
Maple assists researchers using MRI
technology
Researchers are exploring applications of Maple software in the interpretation of images from MRI scans for the early detection and characterisation of small tumours
Researchers at the University of Connecticut Health Centre (UCHC) are exploring applications of Maple in the interpretation of magnetic resonance imaging (MRI) information for the early detection and characterisation of small tumours Vascular networks required for nurturing growth in tumour microenvironments can be much denser than in normal tissue
This article was originally published on Processingtalk on 4 Aug 2004 at 8.00am (UK)
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Vascular density is an important parameter in assessing tumour activity, but it is universally appreciated that accurate determination is a difficult task.
Determination of this parameter is based on manual counting procedures and is observer subjective.
At best, one has to be satisfied with relative measurements.
Moreover, these measurements are very labour intensive and time consuming.
For example, quantification along a major axis of a 1-cm tumour using several histological sections can take up to 200 hours.
This experience prompted the UCHC team to develop a box-counting routine to interrogate digitised microscope images of well-resolved vascular networks.
A Maple program generates a binary map of the microscope images adjusted by selected thresholds.
A second algorithm creates an adjustable-size square box that peruses the entire binary image and tests each pixel site for a value (1 or 0) to provide the basis for counting intersections (1's) and non-intersecting spaces (0's).
In the small limit of s, a relative measure of the vascular density can thus be achieved in a matter of seconds.
The measurements are used to validate the MR images.
The UCHC team is demonstrating new ways that MRI can be used as a superior way to detect and characterise small (2-4 mm), rapidly growing tumours.
This research will enable doctors to use non-invasive MRI to identify and characterise human cancer tumours in their early stages of development and quantitatively follow the course of therapies.
To date preliminary results have been done on mice.
Clinical trials with human patients are anticipated in the near future. Request a free brochure from Adept Scientific ...
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