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A Novel Approach to Extract Colon Lumen from CT Images for Virtual Colonoscopy
作者 :Dongqing Chen ,Zhengrong Liang, Mark R.Wax, Lihong Li
出處 :IEEE ,Transaction on Medical Imaging, Dec. 2000, pp. 1220 - 1226
學生 :林上智指導老師 :張顧耀
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Introduction(1/2)
Colorectal carcinoma is the second leading cause of cancer-related deaths in USA.
Examine the colon require clean colonSegmentation of CT imagesLow-residue diet with ingested contrast sol
utions Enhance materials Remove by computer algorithm
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Introduction(2/2)
The Method is a multistage approach 1.Image classification (low-level):
A modified self-adaptive on-line vector quantization
technique 2.Extraction (high-level):
A region-growing strategy
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Feature Analysis of Image Data
The goal of the low-level processing Classify the body voxel Reduce computing burden
One voxel -> 23dimensional vector ->vector Quantization -> feature vector
Local Volume
(K–L transformation matrix)
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Vector Quantization
The feature vectors were classified into several classes. Generate class Label voxel to class
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Vector Quantization
CT Images, there are four classes: 1.Air 2.Soft tissue 3.Muscle 4.Bone or enhanced materials
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Extraction of the Colon Lumen
The colon lumen consisted of four kinds of labeled voxels: 1.Air 2.Partial volume from air to soft tissue/muscle 3.Enhanced materials 4.Partial volume from enhanced materials to sof
t/muscle
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Results
Bowel Preparation Five volunteers
Take a high fluid Low residue diet
Three patients Physical colon cleansing 1000cc of CO2
CT scan Image size:512x512 Slices:300~450