Home
Research
Publication
Download
Teaching
Links
|
|
3D
Tumor Localization and Reconstruction in Bioluminescence Images
This work introduces a novel and efficient algorithm for reconstructing
the 3D shapes of tumors from a set of 2D bioluminescence images which
are taken by the same camera but after continually rotating the animal
by a small angle. The method is efficient and robust enough to be
used for analyzing
the repeated imaging of a same animal transplanted with gene marked
cells. There are several steps in our algorithm. First, the silhouettes
(or boundaries) of the animal and its interior hot spots (corresponding
to tumors) are segmented in the set of bioluminescence images. Second,
the images are registered according to the projection of the animal
rotating axis. Third, the images are mapped onto 3D projection planes
and from the viewpoint of each plane, the visual hulls of the animal
and its interior tumors are reconstructed. Then, the intersection
of visual hulls from all viewpoints approximates the shape of the
animal and its interior tumors. In order to visualize in 3D the structure
of the tumor, we also co-register the BLI-reconstructed crude structure
with detailed anatomical structure extracted from high-resolution
micro-CT on a single platform. The experimental results show promising
performance of our reconstruction and co-registration method.
.Papers
Bioluminense Images
|
-
An animal is injected with tumor cells
expressing Luciferase. Tumors are formed in the animal,
and the animal can be imaged by BLI (e.g. on day 12
after injection) following the injection of D-luciferin
given intraperitoneally. The tumor cells produce light
and show high response in BLI images.
-
An animal (mouse) was injected with
20,000 tumor cells expressing luciferase Tumors were
formed in the abdomen, and the animal was imaged on
day 12 after injection following injection of 150 mg/kg
D-luciferin given intraperitoneally.
-
The animal was anesthetized with isoflurane
inhalation, and immobilized with a cylindrical 50ml
tube that can be rotated by a small angle at a time
from the vertical axis.
-
The animal was then placed on the image
stage of the IVIS 100 machine (Xenogen, Alameda, CA)
and BLI images were acquired when rotating the tube.
-
The same animal was carried over to
the microCT machine in the same position while remaining
under isoflurane anesthesia.
|
Samples
|
-
Using a series of BLI images
taken by the same camera but after continually rotating
the animal by a small angle.
-
Instead of using multiple cameras,
we use a single CCD camera setup which is readily available
in commercial BLI imaging systems (e.g. IVIS 200 imaging
station).
-
We can acquire any number of
images by adjusting the rotation angle; small angle
insures good correspondence points between consecutive
images.
|
Tumor Localization, Segmentation, Reconstruction
|
-
We compute the feature
correspondences between consecutive images to reconstruct
the 3D locations of feature points
-
Reconstruct 3D structures
and tumor depth by shooting rays from corresponding
feature points and computing 3D ray intersection. Setting
up 3D projection plane geometry
-
Segment tumor (high response) area in
every BLI image. Project cylindrical visual hull based
on the tumor areas
|
Registration bewtween Bioluminense Images
and CT images
|
-
Register CT crude structure with structure
reconstructed from BLI using shape registration algorithm
|
Final
Visualization Results
|
-
Recovered tumor shape and location and
visualization after co-registration with microCT
-
Extract mouse surface and skeleton
structure from microCT following standard CT segmentation.
-
Register CT crude structure with structure
reconstructed from BLI using shape registration algorithm
|
|