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Medical Image Analysis
Volume 14, Issue 3
, Pages 407-428
, June 2010
Location registration and recognition (LRR) for serial analysis of nodules in lung CT scans
References
- . Vessel tree reconstruction in thoracic CT scans with application to nodule detection. IEEE Trans. Med. Imag. 2005;24(4):486–499
- . The reference image database to evaluate response to therapy in lung cancer (RIDER) project: a resource for the development of change-analysis software. Clin. Pharmacol. Ther. 2008;84(4):448–456
- . Registration of vascular images. Int. J. Comp. Vis. 2003;55(2–3):123–138
- Azar, A., Xu, C., Pennec, X., Ayache, N., 2006. An interactive hybrid non-rigid registration framework for 3D medical images. In: IEEE Int. Symp. Biomed. Imaging, pp. 824–827.
- . Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 2002;24(4):509–522
- . A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell. 1992;14(2):239–256
- . Landmark detection in the chest and registration of lung surfaces with an application to nodule registration. Med. Image Anal. 2003;7:265–281
- Boldea, V., Sarrut, D., Clippe, S., 2003. Lung deformation estimation with non-rigid registration for radiotherapy treatment. In: Proc. 6th MICCAI. pp. 770–777.
- . Automatic panoramic image stitching using invariant features. Int. J. Comp. Vis. 2007;74(1):59–73
- Cahill, N.D., Noble, J.A., Hawkes, D.J., 2009. A demons algorithm for image registration with locally adaptive regularization. In: Proc. 12th MICCAI, vol. 1, London, UK, pp. 574–581.
- . Explicit incorporation of prior anatomical information into a nonrigid registration of thoracic and abdominal CT and 18-FDG whole-body emission PET images. IEEE Trans. Med. Imag. 2007;26(2):164–178
- Čech, J., Matas, J., Perďoch, M., 2008. Efficient sequential correspondence selection by cosegmentation. In: Proc. CVPR, Anchorage, AK.
- Chang, C.-C., Lin, C.-J., 2001. LIBSVM: a library for support vector machines. Software available at <http://www.csie.ntu.edu.tw/∼cjlin/libsvm>.
- Charnoz, A., Agnus, V., Soler, L., 2004. Portal vein registration for the follow-up of hepatic tumours. In: Proc. 7th MICCAI, Saint-Malo, France, pp. 878–886.
- . Object modeling by registration of multiple range images. IVC. 1992;10(3):145–155
- Chillet, D., Jomier, J., Cool, D., Aylward, S., 2003. Vascular atlas formation using a vessel-to-image affine registration method. In: Proc. 6th MICCAI, pp. 335–342.
- . Unsupervised learning of an atlas from unlabeled point-sets. IEEE Trans. Pattern Anal. Mach. Intell. 2004;26(2):160–172
- Cool, D., Chillet, D., Kim, J., Guyon, J.-P., Foskey, M., Aylward, S., 2003. Tissue-based affine registration of brain images to form a vascular density atlas. In: Proc. 6th MICCAI, pp. 9–15.
- Cootes, T., Marsland, S., Twining, C., Smith, K., Taylor, C., 2004. Groupwise diffeomorphic non-rigid registration for automatic model building. In: Proc. Eigth ECCV, pp. 316–327.
- . Pattern Classification. John Wiley and Sons; 2001;
- El-Baz, A., Gimel’farb, G., Falk, R., El-Ghar, M.A., Rainey, S., Heredia, D., Shaffer, T., 2009. Toward early diagnosis of lung cancer. In: Proc. 12th MICCAI, vol. 2, London, UK, pp. 682–689.
- Fan, Y., Shen, D., Davatzikos, C., 2005. Classification of structural images via high-dimensional image warping, robust feature extraction, and SVM. In: Proc. 8th MICCAI, Palm Springs, California, USA, pp. 1–8.
- Ferrari, V., Tuytelaars, T., Gool, L.V., 2004. Simultaneous object recognition and segmentation by image exploration. In: Proc. Eigth ECCV, pp. 40–54.
- Frome, A., Huber, D., Kolurri, R., Buelow, T., Malik, J., 2004. Recognizing objects in range data using regional point descriptors. In: Proc. Eigth ECCV.
- . Global Cancer Facts and Figures, 2007. Atlanta, GA: American Cancer Society; 2007;
- . Computer-aided diagnosis in chest radiography: a survey. IEEE Trans. Med. Imag. 2001;20(12):1228–1241
- Gorbunova, V., Lo, P., Ashraf, H., Dirksen, A., Nielsen, M., de Bruijne, M., 2008. Weight Preserving Image Registration for Monitoring Disease Progression in Lung CT. New York, NY, pp. 863–870.
- . Evaluation of 3D operators for the detection of anatomical point landmarks in MR and CT images. Comput. Vis. Image Und. 2002;86(2):118–136
- . Multiple View Geometry. Cambridge University Press; 2000;
- Ibáñez, L., Schroeder, W., Ng, L., Cates, J., 2003. The ITK Software Guide: The Insight Segmentation and Registration Toolkit (version 1.4). Kitware Inc.
- . Spatio-Temporal Image Processing: Theory and Scientific Applications. Springer-Verlag New York, Inc; 1993;
- Kaus, M.R., Netsch, T., Kabus, S., Pekar, V., McNutt, T., Fischer, B., 2004. Estimation of organ motion from 4D CT for 4D radiation therapy planning of lung cancer. In: Proc. 7th MICCAI, Saint-Malo, France, pp. 1017–1024.
- Kawata, Y., Niki, N., Ohmatsu, H., Kusumoto, M., Kakinuma, R., Mori, K., Nishiyama, H., Eguchi, K., Kaneko, M., Moriyama, N., 2001. Analysis of pulmonary nodule evolutions using a sequence of three-dimensional thoracic CT images. In: Proc. 4th MICCAI, pp. 103–110. Doi. 10.1007/3-540-45468-3_13.
- Kelman, A., Sofka, M., Stewart, C.V., 2007. Keypoint descriptors for matching across multiple image modalities and non-linear intensity variations. In: Proc. IEEE CVPR Workshop on Image Registr. and Fusion, Minneapolis, MN.
- . Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images. IEEE Trans. Med. Imag. 2003;22(10):1259–1274
- Lai, Z., Hua, J., 2008. 3d surface matching and registration through shape images. In: Proc. 11th MICCAI, New York, NY, pp. 44–51.
- Lange, T., Eulenstein, S., Hünerbein, M., Lamecker, H., Schlag, P.-M., 2004. Augmenting intraoperative 3d ultrasound with preoperative models for navigation in liver surgery. In: Proc. 7th MICCAI, Saint-Malo, France, pp. 534–541.
- . A quasi-dense approach to surface reconstruction from uncalibrated images. IEEE Trans. Pattern Anal. Mach. Intell. 2005;27(3):418–433
- . Establishing a normative atlas of the human lung: inter-subject warping and registration of volumetric CT. Acad. Radiol. 2003;10(3):255–265
- Liu, D., Chen, T., 2004. Soft shape context for iterative closest point registration. In: Proc. IEEE Int. Conf. Image Proc., vol. 2, Singapore, pp. 1081–1084.
- Liu, C., Yuen, J., Torralba, A., 2009. Nonparametric scene parsing: Label transfer via dense scene alignment. In: Proc. CVPR, Miami, FL, pp. 1972–1979.
- . Distinctive image features from scale-invariant keypoints. Int. J. Comp. Vis. 2004;60(2):91–110
- . Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner society. Radiology. 2005;237(2):395–400
- . Thoracic non-rigid registration combining self-organizing maps and radial basis functions. Med. Image Anal. 2005;9(3):237–254
- . Robust techniques for computer vision. In: Medioni G, Kang SB editor. Emerging Topics in Computer Vision. Prentice Hall; 2004;
- Evaluation of lung MDCT nodule annotation across radiologists and methods. 2006;13(10):1254–1265
- . Scale and affine invariant interest point detectors. Int. J. Comp. Vis. 2004;60(1):63–86
- Miller, J.V., Stewart, C.V., 18–20 Jun. 1996. MUSE: Robust surface fitting using unbiased scale estimates. In: Proc. CVPR, pp. 300–306.
- . Efficient shape matching using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 2005;27(11):1832–1837
- Murphy, K., van Ginneken, B., Pluim, J., Klein, S., Staring, M., 2008. Semi-automatic reference standard construction for quantitative evaluation of lung CT registration. In: Proc. 11th MICCAI, New York, NY, pp. 1006–1013.
- Nain, D., Haker, S., Grimson, W.E.L., Jr, E.C., Wells, W.W., Ji, H., Kikinis, R., Westin, C.-F., 2002. Intra-patient prone to supine colon registration for synchronized virtual colonoscopy. In: Proc. 5th MICCAI, pp. 573–580.
- Okada, K., Huang, X., 2007. Robust click-point linking: Matching visually dissimilar local regions. In: Proc. IEEE Int. Workshop on Beyond Multiview Geometry: Robust Estimation and Organization of Shapes from Multiple Cue.
- Pock, T., Urschler, M., Zach, C., Beichel, R., Bischof, H., 2007. A duality based algorithm for tv-l1-optical-flow image registration. In: Proc. 10th MICCAI. Brisbane, Australia, pp. 511–518. Doi 10.1007/978-3-540-75759-7_62.
- Prokop, M., Galanski, M., Molen, A.V.D., Schaefer-prokop, C., 2000. Spiral and Multislice Computed Tomography of the Body. Thieme.
- . On measuring the change in size of pulmonary nodules. IEEE Trans. Med. Imag. 2006;25(4):435–450
- . On 3d differential operators for detecting point landmarks. IVC. 1997;15(3):219–233
- Rusinkiewicz, S., Levoy, M., 2001. Efficient variants of the ICP algorithm. In: Proc. 3rd Int. Conf. on 3DIM, pp. 224–231.
- Seshamani, S., Rajan, P., Kumar, R., Girgis, H., Dassopoulos, T., Mullin, G., Hager, G., 2009. A meta registration framework for lesion matching. In: Proc. 12th MICCAI, vol. 1, London, UK, pp. 582–589.
- . HAMMER: hierarchical attribute matching mechanism for elastic registration. IEEE Trans. Med. Imag. 2002;21(11):1421–1439
- Shen, H., Fan, L., Qian, J., Odry, B., Novak, C., , Naidich, D., 2002. Real-time correspondence between lung nodules in follow-up multi-slice high resolution CT studies. In: RSNA. Chicago, IL.
- . Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching. Med. Phys. 2007;34(4):1336–1347
- . Computer analysis of computed tomography scans of the lung: a survey. IEEE Trans. Med. Imag. 2006;25(4):385–405
- Sofka, M., Stewart, C.V., 2008. Location registration and recognition (LRR) for longitudinal evaluation of corresponding regions in CT volumes. In: Proc. 11th MICCAI, vol. 2, New York, NY, pp. 989–997.
- Sofka, M., Yang, G., Stewart, C.V., 2007. Simultaneous covariance driven correspondence (CDC) and transformation estimation in the expectation maximization. In: Proc. CVPR. Minneapolis, MN.
- . Robust parameter estimation in computer vision. SIAM Rev. 1999;41(3):513–537
- . Image matching as a diffusion process: an analogy to Maxwell’s demons. Med. Image Anal. 1998;2(3):
- . Matching and anatomical labeling of human airway tree. IEEE Trans. Med. Imag. 2005;24(12):1540–1547
- Urschler, M., Bauer, J., Ditt, H., Bischof, H., May 2006a. SIFT and shape context for feature-based nonlinear registration of thoracic CT images. In: Proc. European Conference Computer Vision Workshop on Computer Vision Approaches to Medical Image Analysis, Graz, Austria, pp. 73–84.
- Urschler, M., Zach, C., Ditt, H., Bischof, H., 2006b. Automatic point landmark matching for regularizing nonlinear intensity registration: Application to thoracic CT images. In: Proc. 9th MICCAI, Copenhagen, Denmark, pp. 710–717.
- Urschler, M., Kluckner, S., Bischof, H., 2007. A framework for comparison and evaluation of nonlinear intra-subject image registration algorithms. In: ISC/NA-MIC Workshop on Open Science at MICCAI 2007.
- . Statistical Learning Theory. Wiley; 1998;
- Vercauteren, T., Pennec, X., Perchant, A., Ayache, N., 2007. Non-parametric diffeomorphic image registration with the demons algorithm. In: Proc. 10th MICCAI, Brisbane, Australia, pp. 319–326.
- Vik, T., Kabus, S., von Berg, J., Ens, K., Dries, S., Klinder, T., Lorenz, C., 2008. Validation and comparison of registration methods for freebreathing 4D lungCT. In: Sahiner, B., Manning, D.J. (Eds.), Proc. SPIE, vol. 6917, Medical Imaging.
- . Treatment of non-small cell lung cancer stage I and stage II. Chest. 2007;132(3):234–242
- Wiemker, R., de Hoop, B., Kabus, S., Gietema, H., Opfer, R., Dharaiya, E., 2008. Performance study of a globally elastic locally rigid matching algorithm for follow-up chest CT. In: Sahiner, B., Manning, D.J. (Eds.), Proc. SPIE, vol. 69, Medical Imaging.
- . Localization of anatomical point landmarks in 3D medical images by fitting 3D parametric intensity models. Med. Image Anal. 2006;10(1):41–58
- . Determining correspondence in 3-D MR brain images using attribute vectors as morphological signatures of voxels. IEEE Trans. Med. Imag. 2004;23(10):1276–1291
- . Registration of challenging image pairs: initialization, estimation, and decision. IEEE Trans. Pattern Anal. Mach. Intell. 2007;23(11):1973–1989
- . Mass preserving nonrigid registration of CT lung images using cubic B-spline. Med. Phys. 2009;36(9):4213–4222
- . Evaluating variability in tumor measurements from same-day repeat CT scans of patients with nonsmall cell lung cancer. Radiology. 2009;252(1):263–272
PII: S1361-8415(10)00021-6
doi: 10.1016/j.media.2010.02.006
© 2010 Elsevier B.V. All rights reserved.
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Medical Image Analysis
Volume 14, Issue 3
, Pages 407-428
, June 2010
