Image analysis

1. A method for determining the area and/or the volume of a retinal lesion, the method comprising:

1) obtaining Optical Coherence Tomography (OCT) data from a subject with a retinal lesion with a system comprising:

a) an OCT apparatus; and

b) software to calculate an area and/or volume of the region of interest V by implementing the following steps in response to a user of the system:

i) acquiring three-dimensional OCT data comprising at least a first segment and a second segment comprising a retinal lesion;

ii) acquiring two-dimensional image data comprising the tissue abnormality, wherein the tissue abnormality in the three-dimensional OCT data corresponds to the retinal lesion in the two-dimensional data;

iii) drawing a boundary around the retinal lesion in the two-dimensional image data, the boundary enclosing an area A, wherein the two-dimensional image data and three-dimensional OCT data are registered via a computer processor so that the retinal lesion is identified in the three-dimensional OCT data by the boundary drawn on the two-dimensional image and displayed on a computer screen;

iv) calculating a volume v within the boundary and between the first segment and the second segment;

v) calculating an average thickness t between the first segment and the second segment along the boundary; and

vi) calculating the volume of the region of interest V=v−(t×A); and

2) via operation of the system, determining the area and/or the volume of the retinal lesion by acquiring the OCT data, drawing the boundary, and calculating area and/or volume of the retinal lesion.

2. The method of claim 1 , wherein the two-dimensional image data is OCT fundus data, a two-dimensional image produced by integrating three-dimensional OCT data, a cross-sectional slice of three-dimensional OCT data, or a photograph.

3. The method of claim 1 , wherein the boundary is a circle, ellipse, polygon, or irregular shape.

4. The method of claim 1 , further comprising determining a greatest linear distance across the region of interest in the two-dimensional image data.

5. The method of claim 1 , wherein the boundary is a continuous boundary or a discontinuous boundary comprising one or more points, dots, straight line segments, or curved line segments marking the edges of the region of interest.

6. The method of claim 1 , wherein the three-dimensional OCT data is a three-dimensional OCT image.

7. The method of claim 1 , wherein the two-dimensional image data is OCT fundus data, a two-dimensional image produced by integrating three-dimensional OCT data, a cross-sectional slice of three-dimensional OCT data, or a photograph.

8. The method of claim 1 , wherein the area A is calculated by interpolating between a plurality of points indicating the boundary of the region of interest.

9. The method of claim 1 , wherein a user draws the boundary around the region of interest or draws a plurality of points indicating the boundary around the region of interest.

10. The method of claim 1 , wherein a user draws the boundary around the region of interest or draws a plurality of points indicating the boundary around the region of interest using a computer input device.

11. The method of claim 1 , wherein a user draws the boundary around the region of interest or draws a plurality of points indicating the boundary around the region of interest using a mouse, touchscreen, trackball, joystick, trackpad, stylus, or light pen.

12. The method of claim 1 , wherein automated image processing draws the boundary around the region of interest.

13. The method of claim 1 , wherein the boundary is provided on normal biological tissue.