Segmentation and 3D reconstruction from optical coherence tomography images
Corressponding author's email:
halm@hcmute.edu.vnKeywords:
OCT, enhancing images, noise filter, morphology, segmentation, 3D reconstructionAbstract
Extracting object in 2-D images which are taken by image acquisition devices in medical such as X-ray, CT, MRI, OCT, etc. and reconstructing of 3D images to get a general observation is a complicated problem. This method will assist to diagnose clinical diseases more accurately. Optical Coherence Tomography (OCT) with such advantages as high resolution and non-invasive imaging is a device that has been more and more promoted for research of objects in the medical field. However, images obtained from OCT contain noise and salt-pepper noise, which cause many difficulties in the extraction process and several segmentation methods to be unworkable. This paper proposes a novel segmentation method based on the dynamic boundary to extract spinal cord objects from OCT images which are taken on the spine of a mouse. This method has successfully extracted the spinal cord and worked automatically, followed by 3D image reconstruction of the spinal cord from segmented 2D image data.
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