Bio-Tree Systems, Inc.

Yanchun Wu

Kongbin Kang

Raul A Brauner

Joao Cruz

Embodiments relate to extracting blood vessel geometry from one or more optical coherent tomography (OCT) images for use in analyzing biological structures for diagnostic and therapeutic applications for diseases that can be detected by vascular changes in the retina. An OCT image refers generally to one or more images of any dimension obtained using any one or combination of OCT techniques. Some embodiments include a method of identifying a region of interest of a retina from a plurality of retinal blood vessels in at least one optical coherence tomography (OCT) image of at least a portion of the retina. Some embodiments include a method of distinguishing between a plurality of retinal layers from vessel morphology information of retinal blood vessels in at least one optical coherence tomography (OCT) image of at least a portion of the retina.

Methods of obtaining 3D retinal blood vessel geometry from optical coherent tomography images and methods of analyzing same

Techniques for linking geometry extracted from one or more medical images, the geometry including a plurality of geometric objects each having parameter values including at least one value for location and at least one value for direction/orientation, the plurality of geometric objects comprising a target geometric object and at least two candidate geometric objects, the techniques include: (A) comparing parameter values of the target geometric object with parameter values of the at least two candidate geometric objects, (B) selecting one of the at least two candidate geometric objects to link to the target geometric object based, at least in part, on the comparison; and (C) linking the to target geometric object with the selected candidate geometric object.

Methods and system for linking geometry obtained from images

A system and method for diagnosing retina disease is disclosed. The method comprises capturing a plurality of images of the vascular network within the retina, such as through the use of optical coherence tomography (OCT). This plurality of images are then processed to determine the location and diameter of each vessel in the three-dimensional vascular network in the retina. The vascular network is then divided into a plurality of equal unit volumes. The vessel density, vascular volume density and other metrics can then be determined for each unit volume. This information can then be used to identify retina disease. The information can be parsed and presented in a variety of ways.

System and method for detecting retina disease

According to some aspects, a method of identifying a boundary of a portion of a vasculature is provided, the vasculature comprising a geometric representation of a plurality of vessels. The method comprises logically dividing the geometric representation into a plurality of regions, determining at least one feature within each of the plurality of regions, and defining the boundary of the portion of the vasculature based, at least in part, on the at least one feature determined within each of the plurality of regions, wherein the boundary forms a volume defining a separation between inside and outside of the portion of the vasculature. According to some aspects, a method of performing vascular analysis using a geometric representation of a plurality of vessels of the vasculature is provided. The method comprises computing a boundary of a portion of the vasculature based on the geometric representation, logically dividing the geometric representation within the boundary into a plurality of regions, and analyzing at least one feature for each of the plurality of regions within the boundary.

Vascular analysis methods and apparatus

In one aspect, a method of detecting at least on feature associated with a blood vessel in at least one image of at least one blood vessel using a matched filter adapted to respond to the at least one feature is provided. The method comprises applying a scale detection filter to selected voxels in the at least one image to determine a scale for the matched filter at each of the selected voxels, determining an orientation for the matched filter at each of the selected voxels, wherein determining the orientation is assisted by using the scale determined at each of the selected voxels, applying the matched filter at each of the selected voxels at the scale and the orientation determined at each of the selected voxels to obtain a filter response at each of the selected voxels, and analyzing the filter response at each of the selected voxels to determine if the respective voxel corresponds to the at least one feature.

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Sharon, MA, United States of America

Yanchun Wu