cloud-based storage, processing and rendering for gegabytes 3d biomedical images
TRANSCRIPT
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Team XYZ: Yan Xu Yu Zhang
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Imaging Processing
Communications
Group A at place AGroup B at place B
(thousands of miles away)
Long distance, Low efficiency
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CommandsResults
Group A Group B
YX
YZ
Hadoop
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• Pipeline I (projection, non-overlapping patches):
• 3D Image Storage: 2D Z slices in jpg
• Libraries: HIPI (FloatImage, JPEGFileInputFormat).
(xy index, FloatImage)
non-overlap XY patches
projection along z
merge to one projected jpg
Jpg seq
same xyindex
2D Z slices Projected Image
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• Pipeline II (3-D filtering, overlapping patches):
(xy index, FloatImage)
overlap XY patches
3-D image filtering
non-overlap XY patches
merge XY patches
(z index, FloatImage)
Jpg seqnamed by xy_z.jpg
Jpg seq
Jpg seq
same xyindex
same Z index
2D Z slicesof original 3D
image
2D Z slicesof processed
3D image
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190 jpg sequencesfor one 3-D image
(54.6MB, 1000 × 1000)Cropped into
5 × 5 patches (200 × 200) )
localhost:50030
Max Projection Mean Projection
Test 3-D image:
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Web Terminal
Image Window
Control Panel
Display original 3D imageExplore 3D image by slicesZoom in and outHand moveDisplay processing result
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Tools
Map-reduce
Java
Javascript
O
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Compatibility
Compatible with ImageJ (open-source Java image processing tool)
Extendibility
Upload and run the script by users
Attractiveness
More user-friendly interface
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Team XYZ
XY YZ