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Computational Tool Recognizes Filamentary Sections of Neurons and Blood Vessels


Retinal and neuronal segmentation images (right column) can be produced from empirical two-dimensional datasets (left column) thanks to a new computational approach.

A computational tool developed by A*STAR researchers is now available for faster, more reliable screening and diagnosis of serious vascular and neurological conditions including glaucoma, diabetic retinopathy, and Alzheimer's disease, in their early stages.

Credit: IEEE

Researchers at the Agency for Science, Technology and Research (A*STAR) in Singapore have developed a computational tool for faster and more reliable screening and diagnosis of vascular and neurological conditions.

The software automatically segments filamentary structures such as retinal blood vessels and neurons in various biomedical images.

The researchers note similar computer programs have been used to automate the segmentation process, and although these programs reduce human error, their performance is normally optimized to specific tasks, limiting their use.

In order to widen the scope of these programs, the A*STAR researchers, in collaboration with researchers at the Beijing Institute of Technology in China, developed an algorithm that addresses segmentation as a general problem.

The researchers designed a two-step algorithm that sequentially extracts structured and contextual information from experimental data.

A*STAR's Li Cheng says the algorithm represents a stepping stone in efforts to cure eye-related problems and decipher the structure and inner workings of neuronal diagrams.

From A*STAR Research
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