Automatic 3D pulmonary nodule detection in CT images: A survey
暂无分享,去创建一个
João Manuel R. S. Tavares | Victor Hugo C. de Albuquerque | Paulo César Cortez | Edson Cavalcanti Neto | P. C. Cortez | José Marques Soares | Igor Rafael S. Valente | J. Tavares | E. C. Neto | J. M. Soares | V. Albuquerque
[1] Lubomir M. Hadjiiski,et al. Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours. , 2006, Medical physics.
[2] J. Dehmeshki,et al. Shape based region growing using derivatives of 3D medical images: application to automatic detection of pulmonary nodules , 2003, 3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the.
[3] Temesguen Messay,et al. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery , 2010, Medical Image Anal..
[4] Wu Suiyuan,et al. Pulmonary Nodules 3D Detection on Serial CT Scans , 2012, 2012 Third Global Congress on Intelligent Systems.
[5] Hiram Madero Orozco,et al. Lung nodule classification in frequency domain using support vector machines , 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).
[6] Anthony P. Reeves,et al. THREE-DIMENSIONAL MULTICRITERION AUTOMATIC SEGMENTATION OF PULMONARY NODULES OF HELICAL COMPUTED TOMOGRAPHY IMAGES , 1999 .
[7] Pawel Badura,et al. Soft computing approach to 3D lung nodule segmentation in CT , 2014, Comput. Biol. Medicine.
[8] P. Taylor,et al. A systematic review of computer-assisted diagnosis in diagnostic cancer imaging. , 2012, European journal of radiology.
[9] David Menotti,et al. ECG arrhythmia classification based on optimum-path forest , 2013, Expert Syst. Appl..
[10] Joyoni Dey,et al. > Replace This Line with Your Paper Identification Number (double-click Here to Edit) < , 2022 .
[11] A. Marchesiello,et al. The symmetric 1:2 resonance , 2013, 1303.2907.
[12] S. Armato,et al. Computerized detection of pulmonary nodules on CT scans. , 1999, Radiographics : a review publication of the Radiological Society of North America, Inc.
[13] M. Masotti,et al. Computer-aided detection of lung nodules via 3D fast radial transform, scale space representation, and Zernike MIP classification. , 2011, Medical physics.
[14] Bin Chen,et al. Automatic segmentation of pulmonary blood vessels and nodules based on local intensity structure analysis and surface propagation in 3D chest CT images , 2012, International Journal of Computer Assisted Radiology and Surgery.
[15] H. Kundel,et al. Lesion conspicuity, structured noise, and film reader error. , 1976, AJR. American journal of roentgenology.
[16] Donato Cascio,et al. Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models , 2012, Comput. Biol. Medicine.
[17] Matthew T. Freedman,et al. Reduction of false positives in lung nodule detection using a two-level neural classification , 1996, IEEE Trans. Medical Imaging.
[18] Hamid Abrishami Moghaddam,et al. Automated detection and classification of pulmonary nodules in 3D thoracic CT images , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.
[19] Jiahui Wang,et al. Computer-aided diagnosis: a 3D segmentation method for lung nodules in CT images by use of a spiral-scanning technique , 2008, SPIE Medical Imaging.
[20] M. Bazzocchi,et al. MAGIC-5: an Italian mammographic database of digitised images for research , 2008, La radiologia medica.
[21] Dorin Comaniciu,et al. Robust 3D Segmentation of Pulmonary Nodules in Multislice CT Images , 2004, MICCAI.
[22] Ricardo A. M. Valentim,et al. Computer-aided detection system for lung cancer in computed tomography scans: Review and future prospects , 2014, BioMedical Engineering OnLine.
[23] Ilaria Gori,et al. Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study , 2010, Medical Image Anal..
[24] F. Laurent,et al. Management strategy of pulmonary nodule in 2013. , 2013, Diagnostic and interventional imaging.
[25] S. Armato,et al. Lung cancers missed at low-dose helical CT screening in a general population: comparison of clinical, histopathologic, and imaging findings. , 2002, Radiology.
[26] Zhen Ma,et al. A review of algorithms for medical image segmentation and their applications to the female pelvic cavity , 2010, Computer methods in biomechanics and biomedical engineering.
[27] Heber MacMahon,et al. Analysis of a three-dimensional lung nodule detection method for thoracic CT scans , 2000, Medical Imaging: Image Processing.
[28] K. Awai,et al. Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists' detection performance. , 2004, Radiology.
[29] Milan Sonka,et al. 3D segmentation of non-isolated pulmonary nodules in high resolution CT images , 2005, SPIE Medical Imaging.
[30] Miss A.O. Penney. (b) , 1974, The New Yale Book of Quotations.
[31] Bram van Ginneken,et al. Automated detection of pulmonary nodules from low-dose computed tomography scans using a two-stage classification system based on local image features , 2007, SPIE Medical Imaging.
[32] K. Berbaum,et al. Satisfaction of search in diagnostic radiology. , 1989, Investigative radiology.
[33] Matthew T. Freedman,et al. Three-dimensional visualization system as an aid for lung cancer detection , 2000, Medical Imaging.
[34] N. Dubrawsky. Cancer statistics , 1989, CA: a cancer journal for clinicians.
[35] Yoshito Mekada,et al. Detection of small nodules from 3D chest X-ray CT images based on shape features , 2003, CARS.
[36] Jamshid Dehmeshki,et al. Shape based region growing using derivatives of 3D medical images: application to semiautomated detection of pulmonary nodules , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).
[37] Li Cao,et al. A detection approach for solitary pulmonary nodules based on CT images , 2012, Proceedings of 2012 2nd International Conference on Computer Science and Network Technology.
[38] H. D. de Koning,et al. NELSON lung cancer screening study , 2011, Cancer imaging : the official publication of the International Cancer Imaging Society.
[39] Dazhe Zhao,et al. A method of pulmonary nodule detection utilizing multiple support vector machines , 2010, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).
[40] Zaid J. Towfic,et al. The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation , 2007, SPIE Medical Imaging.
[41] Françoise J. Prêteux,et al. 3D Automated Lung Nodule Segmentation in HRCT , 2003, MICCAI.
[42] Noboru Niki,et al. ROI extraction of chest CT images using adaptive opening filter , 2003, SPIE Medical Imaging.
[43] Wei Li,et al. A Three-Dimensional Method for Detection of Pulmonary Nodule , 2009, 2009 2nd International Conference on Biomedical Engineering and Informatics.
[44] Dazhe Zhao,et al. A Study of Pulmonary Nodule Detection in Three-Dimensional Thoracic CT Scans , 2010, 2010 Second International Conference on Computer Modeling and Simulation.
[45] M. Revel,et al. Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? , 2004, Radiology.
[46] Ilaria Gori,et al. Combination of computer-aided detection algorithms for automatic lung nodule identification , 2011, International Journal of Computer Assisted Radiology and Surgery.
[47] Kenji Suzuki. A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD). , 2009, Physics in medicine and biology.
[48] K. Komatsu,et al. Diminution index: A novel 3D feature for pulmonary nodule detection , 2005 .
[49] Tae-Sun Choi,et al. Genetic programming-based feature transform and classification for the automatic detection of pulmonary nodules on computed tomography images , 2012, Inf. Sci..
[50] F. Tajeripour,et al. Lung nodule detection by KNN classifier and active contour modelling and 3D visualization , 2012, The 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012).
[51] Hongli Lin,et al. A pulmonary nodule view system for the Lung Image Database Consortium (LIDC). , 2011, Academic radiology.
[52] W. Heindel,et al. Detection of pulmonary nodules at spiral CT: comparison of maximum intensity projection sliding slabs and single-image reporting , 2001, European Radiology.
[53] Noboru Niki,et al. Nodule detection algorithm based on multislice CT images for lung cancer screening , 2004, SPIE Medical Imaging.
[54] T. Hara,et al. Nodule detection in 3D chest CT images using 2nd order autocorrelation features , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.
[55] Kunio Doi,et al. New selective nodule enhancement filter and its application for significant improvement of nodule detection on computed tomography , 2004, SPIE Medical Imaging.
[56] Shinji Yamamoto,et al. A detection method of ground glass opacities in chest x-ray CT images using automatic clustering techniques , 2003, SPIE Medical Imaging.
[57] W. J. Tuddenham. Visual search, image organization, and reader error in roentgen diagnosis. Studies of the psycho-physiology of roentgen image perception. , 1962, Radiology.
[58] Lubomir M. Hadjiiski,et al. Computer-aided detection of lung nodules: false positive reduction using a 3D gradient field method and 3D ellipsoid fitting. , 2005, Medical physics.
[59] Richard C. Pais,et al. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. , 2011, Medical physics.
[60] Computer-aided detection of lung nodules by SVM based on 3D matrix patterns. , 2013, Clinical imaging.
[61] R. Engelmann,et al. Segmentation of pulmonary nodules in three-dimensional CT images by use of a spiral-scanning technique. , 2007, Medical physics.
[62] Kunio Doi,et al. Three-dimensional approach to lung nodule detection in helical CT , 1999, Medical Imaging.
[63] João Manuel R S Tavares,et al. Medical image registration: a review , 2014, Computer methods in biomechanics and biomedical engineering.
[64] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[65] Ming Yang,et al. False Positive Reduction in Lung GGO Nodule Detection with 3D Volume Shape Descriptor , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[66] Ayman El-Baz,et al. Automatic Detection of 2D and 3D Lung Nodules in Chest Spiral CT Scans , 2013, Int. J. Biomed. Imaging.
[67] Daisuke Yamamoto,et al. Computer-Aided Diagnosis Systems for Brain Diseases in Magnetic Resonance Images , 2009, Algorithms.
[68] R. Bellotti,et al. A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model. , 2007, Medical physics.
[69] João Paulo Papa,et al. A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier , 2014, Pattern Recognit. Lett..
[70] S. Armato,et al. Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography. , 2003, Medical physics.
[71] João Paulo Papa,et al. Efficient supervised optimum-path forest classification for large datasets , 2012, Pattern Recognit..
[72] Gady Agam,et al. Vessel tree reconstruction in thoracic CT scans with application to nodule detection , 2005, IEEE Transactions on Medical Imaging.
[73] Steven C. Horii,et al. Review: Understanding and Using DICOM, the Data Interchange Standard for Biomedical Imaging , 1997, J. Am. Medical Informatics Assoc..
[74] U. Neisser. VISUAL SEARCH. , 1964, Scientific American.
[75] Jamshid Dehmeshki,et al. Shape-Based Computer-Aided Detection of Lung Nodules in Thoracic CT Images , 2009, IEEE Transactions on Biomedical Engineering.
[76] Kenji Suzuki,et al. Radiologic classification of small adenocarcinoma of the lung: radiologic-pathologic correlation and its prognostic impact. , 2006, The Annals of thoracic surgery.
[77] Y. Kawata,et al. Computer-aided diagnosis for pulmonary nodules based on helical CT images , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).
[78] K. Berbaum,et al. Error in radiology: classification and lessons in 182 cases presented at a problem case conference. , 1992, Radiology.
[79] James V. Miller,et al. Model-Based Analysis of Local Shape for Lesion Detection in CT Scans , 2005, MICCAI.
[80] J. V. van Engelshoven,et al. Miss rate of lung cancer on the chest radiograph in clinical practice. , 1999, Chest.
[81] L. Lusted. Logical analysis in roentgen diagnosis. , 1960, Radiology.
[82] João Manuel R. S. Tavares,et al. A Review on the Current Segmentation Algorithms for Medical Images , 2009, IMAGAPP.
[83] Aly A. Farag,et al. Appearance Models for Robust Segmentation of Pulmonary Nodules in 3D LDCT Chest Images , 2006, MICCAI.
[84] Abbas Z. Kouzani,et al. Automated detection of lung nodules in computed tomography images: a review , 2010, Machine Vision and Applications.
[85] Niccolo Camarlinghi,et al. Automatic detection of lung nodules in computed tomography images: training and validation of algorithms using public research databases , 2013, The European Physical Journal Plus.
[86] Berkman Sahiner,et al. Computer-aided detection of lung nodules: false positive reduction using a 3D gradient field method , 2004, SPIE Medical Imaging.
[87] K. Gunavathi,et al. Efficient and reliable lung nodule detection using a neural network based computer aided diagnosis system , 2012, 2012 International Conference on Emerging Trends in Electrical Engineering and Energy Management (ICETEEEM).
[88] L. Clarke,et al. Fragmentary window filtering for multiscale lung nodule detection: preliminary study. , 1998, Academic radiology.
[89] A. Jemal,et al. Cancer statistics, 2013 , 2013, CA: a cancer journal for clinicians.
[90] O. Miettinen,et al. Early Lung Cancer Action Project: overall design and findings from baseline screening , 1999, The Lancet.
[91] N. Müller,et al. Fleischner Society: glossary of terms for thoracic imaging. , 2008, Radiology.
[92] João Manuel R. S. Tavares. Analysis of Biomedical Images Based on Automated Methods of Image Registration , 2014, ISVC.
[93] B. van Ginneken,et al. Computer-aided diagnosis: how to move from the laboratory to the clinic. , 2011, Radiology.
[94] Berkman Sahiner,et al. Evaluation of computer-aided detection and diagnosis systems. , 2013, Medical physics.
[95] Li Fan,et al. Automatic segmentation of pulmonary nodules by using dynamic 3D cross-correlation for interactive CAD systems , 2002, SPIE Medical Imaging.
[96] Onur Osman,et al. Computerized Lung Nodule Detection Using 3D Feature Extraction and Learning Based Algorithms , 2008, Journal of Medical Systems.
[97] Anselmo Cardoso de Paiva,et al. Automatic detection of small lung nodules in 3D CT data using Gaussian mixture models, Tsallis entropy and SVM , 2014, Eng. Appl. Artif. Intell..
[98] Dinggang Shen,et al. Lung Nodule Growth Analysis from 3D CT Data with a Coupled Segmentation and Registration Framework , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[99] J. Tavares,et al. Computer Image Registration Techniques Applied to Nuclear Medicine Images , 2015 .
[100] S. Matsumoto,et al. Computer-aided detection of lung nodules on multidetector row computed tomography using three-dimensional analysis of nodule candidates and their surroundings , 2008, Radiation Medicine.
[101] Zygmunt Wróbel,et al. Automatic method of analysis of OCT images in assessing the severity degree of glaucoma and the visual field loss , 2014, Biomedical engineering online.
[102] Ke Wang,et al. Automatic Detection of Pulmonary Nodules in Multi-slice CT Based on 3D Neural Networks with Adaptive Initial Weights , 2010, 2010 International Conference on Intelligent Computation Technology and Automation.
[103] João Paulo Papa,et al. EEG signal classification for epilepsy diagnosis via optimum path forest - A systematic assessment , 2014, Neurocomputing.
[104] O. Ucan,et al. Nodule Detection in a Lung Region that's Segmented with Using Genetic Cellular Neural Networks and 3D Template Matching with Fuzzy Rule Based Thresholding , 2008, Korean journal of radiology.
[105] Kenji Suzuki. A review of computer-aided diagnosis in thoracic and colonic imaging. , 2012, Quantitative imaging in medicine and surgery.
[106] Hiroshi Fujita,et al. Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter , 2012, International Journal of Computer Assisted Radiology and Surgery.
[107] Tae-Sun Choi,et al. Automated pulmonary nodule detection based on three-dimensional shape-based feature descriptor , 2014, Comput. Methods Programs Biomed..
[108] Berkman Sahiner,et al. Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computer-aided diagnosis system. , 2002, Medical physics.
[109] Hiroshi Fujita,et al. Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique , 2001, IEEE Transactions on Medical Imaging.