Title
Computer-aided detection of sclerotic bone metastases in the spine using watershed algorithm and support vector machines
Abstract
This work presents a computer-aided detection (CAD) system to aid radiologists in finding sclerotic bone metastases in the spine on CT images. The spine is first segmented using thresholding, region growing and a vertebra template. A watershed algorithm and a merging routine segment potential lesion candidates in each two-dimensional (2-D) axial CT image. Next, overlapping 2-D detections on sequential CT slices are merged to form 3-D candidate lesions. For each of these, 30 quantitative features based on shape, density, and location are computed. After a feature filter eliminates clearly false candidates, a ground truth on 10 clinical cases segmented manually by an expert, and the features of each CAD candidate are used to train seven support vector machines. The segmentation algorithm detects 164 out of the 212 manually segmented lesions. A ten-fold cross-validation trained on these detections results in 77.4% sensitivity at an average of 9.44 false positives per case.
Year
DOI
Venue
2011
10.1109/ISBI.2011.5872376
Chicago, IL
Keywords
Field
DocType
bone,computerised tomography,diagnostic radiography,feature extraction,image segmentation,medical image processing,neurophysiology,support vector machines,tumours,computer-aided detection,feature filter,image segmentation,region growing,routine segment potential lesion candidates,sclerotic bone metastases,spine,support vector machines,ten-fold cross-validation,thresholding,two-dimensional axial CT image,vertebra template,watershed algorithm,bone metastasis,computer aided detection,sclerotic lesion
Computer vision,Pattern recognition,Segmentation,Computer science,Support vector machine,Feature extraction,Image segmentation,Artificial intelligence,Region growing,Thresholding,Statistical classification,False positive paradox
Conference
ISSN
ISBN
Citations 
1945-7928 E-ISBN : 978-1-4244-4128-0
978-1-4244-4128-0
5
PageRank 
References 
Authors
0.59
1
4
Name
Order
Citations
PageRank
Tatjana Wiese150.59
Joseph E. Burns2899.51
Jianhua Yao31135110.49
Ronald M. Summers489386.16