Scientists consider 3D processing for automating cancer detection
Researchers at the University of Hertfordshire in England are developing technology that may make it possible to semi-automate the process for detecting cancerous tumors.
Soodamani Ramalingam, MD, and her team at the university are developing 3D object recognition and image processing, making it possible to get a more accurate picture of human tumors so cancers can be identified and treated accordingly.
They plan to make the technology available within three years to hospitals throughout the United Kingdom. They also are seeking collaborators and further funding for this end.
In collaboration with the Paul Strickland Scanner Centre where clinical image data is acquired, the team is using a combination of fuzzy logic (a type of logic that recognizes more than simple true and false values) and image processing to identify cancer and establish accurately how far it has spread.
“This new method of image analysis imaging will be more accurate in defining tumor edges, and will potentially allow more effective treatments,” Ramalingam said.
According to the researchers, the technology, which will also have applications in other medical fields, will compliment traditional PET and CT scans because the fusion of Fuzzy Logic and Image Processing will produce better defined tumor images and so greater certainty in diagnosis and treatment.
"The classical mathematical approaches to looking at clinical scans do not always produce high resolution images,” said Ramalingam. “In some cases this means that specialists cannot interpret the PET/CT scan very easily, so there is always a certain degree of uncertainty that our advanced analysis techniques will address.”
Soodamani Ramalingam, MD, and her team at the university are developing 3D object recognition and image processing, making it possible to get a more accurate picture of human tumors so cancers can be identified and treated accordingly.
They plan to make the technology available within three years to hospitals throughout the United Kingdom. They also are seeking collaborators and further funding for this end.
In collaboration with the Paul Strickland Scanner Centre where clinical image data is acquired, the team is using a combination of fuzzy logic (a type of logic that recognizes more than simple true and false values) and image processing to identify cancer and establish accurately how far it has spread.
“This new method of image analysis imaging will be more accurate in defining tumor edges, and will potentially allow more effective treatments,” Ramalingam said.
According to the researchers, the technology, which will also have applications in other medical fields, will compliment traditional PET and CT scans because the fusion of Fuzzy Logic and Image Processing will produce better defined tumor images and so greater certainty in diagnosis and treatment.
"The classical mathematical approaches to looking at clinical scans do not always produce high resolution images,” said Ramalingam. “In some cases this means that specialists cannot interpret the PET/CT scan very easily, so there is always a certain degree of uncertainty that our advanced analysis techniques will address.”