Literature DB >> 17500464

Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching.

Jiazheng Shi1, Berkman Sahiner, Heang-Ping Chan, Lubomir Hadjiiski, Chuan Zhou, Philip N Cascade, Naama Bogot, Ella A Kazerooni, Yi-Ta Wu, Jun Wei.   

Abstract

An automated method is being developed in order to identify corresponding nodules in serial thoracic CT scans for interval change analysis. The method uses the rib centerlines as the reference for initial nodule registration. A spatially adaptive rib segmentation method first locates the regions where the ribs join the spine, which define the starting locations for rib tracking. Each rib is tracked and locally segmented by expectation-maximization. The ribs are automatically labeled, and the centerlines are estimated using skeletonization. For a given nodule in the source scan, the closest three ribs are identified. A three-dimensional (3D) rigid affine transformation guided by simplex optimization aligns the centerlines of each of the three rib pairs in the source and target CT volumes. Automatically defined control points along the centerlines of the three ribs in the source scan and the registered ribs in the target scan are used to guide an initial registration using a second 3D rigid affine transformation. A search volume of interest (VOI) is then located in the target scan. Nodule candidate locations within the search VOI are identified as regions with high Hessian responses. The initial registration is refined by searching for the maximum cross-correlation between the nodule template from the source scan and the candidate locations. The method was evaluated on 48 CT scans from 20 patients. Experienced radiologists identified 101 pairs of corresponding nodules. Three metrics were used for performance evaluation. The first metric was the Euclidean distance between the nodule centers identified by the radiologist and the computer registration, the second metric was a volume overlap measure between the nodule VOIs identified by the radiologist and the computer registration, and the third metric was the hit rate, which measures the fraction of nodules whose centroid computed by the computer registration in the target scan falls within the VOI identified by the radiologist. The average Euclidean distance error was 2.7 +/- 3.3 mm. Only two pairs had an error larger than 10 mm. The average volume overlap measure was 0.71 +/- 0.24. Eighty-three of the 101 pairs had ratios larger than 0.5, and only two pairs had no overlap. The final hit rate was 93/101.

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Year:  2007        PMID: 17500464      PMCID: PMC2742217          DOI: 10.1118/1.2712575

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  21 in total

1.  Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images.

Authors:  Y Sato; S Nakajima; N Shiraga; H Atsumi; S Yoshida; T Koller; G Gerig; R Kikinis
Journal:  Med Image Anal       Date:  1998-06       Impact factor: 8.545

2.  Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computer-aided diagnosis system.

Authors:  Metin N Gurcan; Berkman Sahiner; Nicholas Petrick; Heang-Ping Chan; Ella A Kazerooni; Philip N Cascade; Lubomir Hadjiiski
Journal:  Med Phys       Date:  2002-11       Impact factor: 4.071

Review 3.  Mutual-information-based registration of medical images: a survey.

Authors:  Josien P W Pluim; J B Antoine Maintz; Max A Viergever
Journal:  IEEE Trans Med Imaging       Date:  2003-08       Impact factor: 10.048

4.  Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.

Authors:  Ted W Way; Lubomir M Hadjiiski; Berkman Sahiner; Heang-Ping Chan; Philip N Cascade; Ella A Kazerooni; Naama Bogot; Chuan Zhou
Journal:  Med Phys       Date:  2006-07       Impact factor: 4.071

5.  A correlation-based approach to calculate rotation and translation of moving cells.

Authors:  Cyrus A Wilson; Julie A Theriot
Journal:  IEEE Trans Image Process       Date:  2006-07       Impact factor: 10.856

6.  Image registration with auto-mapped control volumes.

Authors:  Eduard Schreibmann; Lei Xing
Journal:  Med Phys       Date:  2006-04       Impact factor: 4.071

7.  Selective enhancement filters for nodules, vessels, and airway walls in two- and three-dimensional CT scans.

Authors:  Qiang Li; Shusuke Sone; Kunio Doi
Journal:  Med Phys       Date:  2003-08       Impact factor: 4.071

8.  On measuring the change in size of pulmonary nodules.

Authors:  Anthony P Reeves; Antoni B Chan; David F Yankelevitz; Claudia I Henschke; Bryan Kressler; William J Kostis
Journal:  IEEE Trans Med Imaging       Date:  2006-04       Impact factor: 10.048

9.  Lung cancer screening using low-dose spiral CT: results of baseline and 1-year follow-up studies.

Authors:  Takeshi Nawa; Tohru Nakagawa; Suzushi Kusano; Yoshimichi Kawasaki; Youichi Sugawara; Hajime Nakata
Journal:  Chest       Date:  2002-07       Impact factor: 9.410

10.  Results of three-year mass screening programme for lung cancer using mobile low-dose spiral computed tomography scanner.

Authors:  S Sone; F Li; Z G Yang; T Honda; Y Maruyama; S Takashima; M Hasegawa; S Kawakami; K Kubo; M Haniuda; T Yamanda
Journal:  Br J Cancer       Date:  2001-01-05       Impact factor: 7.640

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  6 in total

1.  Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski; Mark A Helvie; Jun Wei; Chuan Zhou; Yao Lu
Journal:  Med Phys       Date:  2012-01       Impact factor: 4.071

2.  Characterization of mammographic masses based on level set segmentation with new image features and patient information.

Authors:  Jiazheng Shi; Berkman Sahiner; Heang-Ping Chan; Jun Ge; Lubomir Hadjiiski; Mark A Helvie; Alexis Nees; Yi-Ta Wu; Jun Wei; Chuan Zhou; Yiheng Zhang; Jing Cui
Journal:  Med Phys       Date:  2008-01       Impact factor: 4.071

Review 3.  Multimodality image registration with software: state-of-the-art.

Authors:  Piotr J Slomka; Richard P Baum
Journal:  Eur J Nucl Med Mol Imaging       Date:  2009-03       Impact factor: 9.236

4.  Pulmonary nodule registration: rigid or nonrigid?

Authors:  Suicheng Gu; David Wilson; Jun Tan; Jiantao Pu
Journal:  Med Phys       Date:  2011-07       Impact factor: 4.071

5.  Bidirectional elastic image registration using B-spline affine transformation.

Authors:  Suicheng Gu; Xin Meng; Frank C Sciurba; Hongxia Ma; Joseph Leader; Naftali Kaminski; David Gur; Jiantao Pu
Journal:  Comput Med Imaging Graph       Date:  2014-01-25       Impact factor: 4.790

6.  Automated iterative neutrosophic lung segmentation for image analysis in thoracic computed tomography.

Authors:  Yanhui Guo; Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Jun Wei; Lubomir M Hadjiiski; Ella A Kazerooni
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

  6 in total

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