background

Preliminary report of competition for liver region extraction algorithms from three dimensional CT images A.Shimizu a , S.Nawano b a Graduate School of BASE, Tokyo University of Agriculture and Technology b National Cancer Center Hospital East Background Death from liver cancer is over 30,000 per year in Japan Early detection of hepatic cellular carcinoma and metastatic of carcinoma is important CAD system is required to decrease the burden on radiologists Materials & Algorithms in competition 2003 Multi slice CT Scanner Tumor Evaluation Future plans In 2002 and 2003, competitions for liver region extraction algorithms from 3D CT images were held in annual conference of Japan society of Computer Aided Diagnosis of Medical Images (CADM). Arterial phase Equilibrium phase For training For test ameters : phase, size, spatial resolution and image position of the first slice e not registered Images Borders of extracted regions + Original CT images (display window : -110(H.U.) to 190(H.U.)) Methods - Three radiologists evaluated the resultant images visually without any priori knowledge about algorithms -Each resultant image was rated from zero to ten Criteria - False positive and false negative of liver regions weighted by the importance e.g. False negative of tumors decrease the score Results Entry no.1 Binarization and morphological operations to extract initial region + Extraction of liver borders using direction of normal vector and curvature + Reconstruction of liver region using a radial basis function Entry no.2 Binarization and mathematical morphology based approach Entry no.3 Edge extraction using Gabor filters and refinement of the extracted borders Entry no.4 Extraction of initial region in low resolution images using histogram analysis and figure decomposition + refinement of borders based on local region analysis in original resolution images Entry no.5 Watershed based method Entry no.6 Statistical discrimination at each voxel based not only on CT values of normal tissues but also those of lesions + level set method with modified speed function based on anatomical knowledge of liver entry no. case1 case2 Total score arter ial equilibr ium arter ial equilibr ium 1 8 9 7 7 31 2 - - 6 5 11 3 - - - - - 4 7 8 6 7 28 5 4 6 5 6 21 6 8 9 9 9 35 CAD In competition 2004, detection performance of liver cancer will be evaluated Fusion of top 3 results by logical AND, OR and majority vote No.1 No.2 No.3 No.4 No.5 No.6 No.1 No.2 No.3 No.4 No.5 No.6 Size : 512 x 512 x (197 ～ 248) Spacing : (0.587 ～ 0.606)mm x 1.0 mm Number of cases : 2 Size : 512 x 512 x (154 - 267) Spacing : (0.546 - 0.625)mm x 1.0 mm Number of cases : 17 Case1 arterial phase Case2 arterial phase No.1 No.4 No.6 Fusion Case2 equilibrium phase OR AND Majori ty vote HP http://www.tuat.ac.jp/~simizlab/CADM/index0.h

Upload: leala

Post on 23-Jan-2016

24 views

Category:

Documents

2 download

Report

Download

Tags:

Embed Size (px):

DESCRIPTION

Tumor. No.1. No.1. No.2. No.2. No.3. No.3. No.4. No.4. No.5. No.5. No.6. No.6. No.1. No.4. No.6. Fusion. Preliminary report of competition for liver region extraction algorithms from three dimensional CT images A.Shimizu a , S.Nawano b - PowerPoint PPT Presentation

TRANSCRIPT

Preliminary report of competition for liver region extraction algorithms from three dimensional CT images

A.Shimizua, S.Nawanob

a Graduate School of BASE, Tokyo University of Agriculture and Technologyb National Cancer Center Hospital East

Background

Death from liver cancer is over 30,000 per year in Japan

Early detection of hepatic cellular carcinoma and metastatic of carcinoma is important

CAD system is required to decrease the burden on radiologists

Materials & Algorithms in competition 2003

Multi slice CT Scanner

Tumor

Evaluation

Future plans

In 2002 and 2003, competitions for liver region extraction algorithms from 3D CT images were held in annual conference of Japan society of Computer Aided Diagnosis of Medical Images (CADM).

Arterial phase Equilibrium phase

Fortraining

Fortest

- Input parameters : phase, size, spatial resolution and image position of the first slice- Images are not registered

ImagesBorders of extracted regions + Original CT

images (display window : -110(H.U.) to 190(H.U.))

Methods- Three radiologists evaluated the resultant

images visually without any priori knowledge about algorithms

- Each resultant image was rated from zero to ten

Criteria- False positive and false negative of liver

regions weighted by the importance e.g. False negative of tumors decrease the

score

Results

Entry no.1 Binarization and morphological operations to extract initial region + Extraction of liver borders using direction of normal vector and

curvature + Reconstruction of liver region using a radial basis function

Entry no.2 Binarization and mathematical morphology based approach

Entry no.3 Edge extraction using Gabor filters and refinement of the extracted borders

Entry no.4 Extraction of initial region in low resolution images using histogram analysis and figure decomposition + refinement of borders based on local region analysis in original resolution images

Entry no.5 Watershed based method

Entry no.6 Statistical discrimination at each voxel based not only on CT values of normal tissues but also those of lesions + level set method with modified speed function based on anatomical knowledge of liver

entry no.

case1 case2Total scorearteria

lequilibriu

marteri

alequilibriu

1 8 9 7 7 31

2 - - 6 5 11

3 - - - - -

4 7 8 6 7 28

5 4 6 5 6 21

6 8 9 9 9 35

CAD