can we obtain depth information from RMI frames?
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jan
el 13 de Sept. de 2015
Comentada: jan
el 15 de Sept. de 2015
Hi everybody, As known depth information can be obtained from stereo images. But what i'm looking for, is it possible to get depth information from RMI images?? otherwise, is there any similar measure for the RMI images??
thanks
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Walter Roberson
el 14 de Sept. de 2015
To expand slightly: You need to approximate depth information from stereo images by examining two images at known distances and angles and using the difference in pixel locations of objects to figure out how far away they must be (the further away, the less they move.) You do this because you have a limited knowledge of the positions of the objects.
For MRI images, however, every voxel has a known location. Scanning is done over a regular grid with known spacing in 2D, and this is repeated for each layer in Z with the distance between the Z layers known. The pixel sizes and the distance between Z layers can be extracted from the headers. Be careful, as it is not uncommon that the Z distance is twice as large as the pixel sizes, so you cannot usually just use pixel indices, but the conversion from indices to coordinates is trivial.
As you can easily calculate the spacial coordinates of every voxel, there is no need to do stereo projection or otherwise approximate locations. You can just calculate distances.
xcoord = column_number * pixel_x_size;
ycoord = row_number * pixel_y_size;
zcoord = slice_number * z_separation;
and then with the x, y, z coordinates of two points in hand, you can use pythagorean theorem, sqrt((x2 - x1)^2 + (y2 - y1)^2 + (z2 - z1)^2)
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Image Analyst
el 14 de Sept. de 2015
You can get relative depth and distances from MRI images.
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Image Analyst
el 14 de Sept. de 2015
Find one point. I don't know what point you want to find though.
Then find the other point. Again, I have no idea what second point you have in mind.
Then use the Pythagorean theorem or the hypot() function to compute the distance (in pixels) between the two points. Multiply by a spatial calibration factor if you need to convert into real world distances, such as millimeters.
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