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Browse Prior Art Database

Fast Inspection of Contents of a Volume of 3D Data

IP.com Disclosure Number: IPCOM000111212D
Original Publication Date: 1994-Feb-01
Included in the Prior Art Database: 2005-Mar-26
Document File: 2 page(s) / 72K

Publishing Venue

IBM

Related People

Galton, N: AUTHOR

Abstract

Disclosed is a fast flexible slicing method of visualizing the shape or property of a volume of 3D data which can be tailored to the capacity of a user's small machine. Given a 3D Volume, it is difficult to quickly visualize the data represented. Although 'volume rendering' is a visualization technique which considers the whole data set, it is expensive in terms of the machine resources it uses and does not always give a clear picture.

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This is the abbreviated version, containing approximately 52% of the total text.

Fast Inspection of Contents of a Volume of 3D Data

      Disclosed is a fast flexible slicing method of visualizing the
shape or property of a volume of 3D data which can be tailored to the
capacity of a user's small machine.   Given a 3D Volume, it is
difficult to quickly visualize the data represented.   Although
'volume rendering' is a visualization technique which considers the
whole data set, it is expensive in terms of the machine resources it
uses and does not always give a clear picture.

     A 3D data volume can be described as consisting of a set of
slices (or cross-sections) which have been stacked together.   Thus,
a volume which has dimensions of 300 x 400 x 50 (in x, y, z,
respectively) would consist of 300 slices in the x-direction, 400
slices in y and 50 slices in z.   Each slice having unit thickness.
The new proposed method involves sampling data slices in a specified
direction (x, y or z) and blending them together to create a
composite picture which gives an impression of the data set.
Blending involves overlaying slices and merging them together in
order to produce a composite result.  A blending algorithm determines
how much each slice contributes to the result.   The number of slices
used depends initially on the size of the data volume.   However,
once a general picture of the data has emerged, the number of slices
sampled can be optimized to suit the user's needs.

     For example, if every 10th slice (of the above volume) is
sampled along the z-axis, a total of 5 slices are extracted - those
at positions 10, 20, 30, 40 and 50 in z.   Each slice has dimensions
of 300 x 400 (in x, y, respectively).  After extracting the slices,
they are blended together to produce a single composite image.   The
number of blending operations is dependent upon the number of slices
that have been chosen.  First, adjacent pairs of slices are overlaid.
Then th...