Rapid Contour-based Segmentation for 18F-FDG PET Imaging of Lung Tumors by Using ITK-SNAP: Comparison to Expert-based Segmentation.
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Elise M. Blanchet | M. Humbert | E. Durand | P. Chaumet‐Riffaud | D. Montani | V. Lebon | F. Besson | V. Roblot | T. Henry | Céline Meyer | Virgile Chevance | V. Arnould | G. Grimon | Malika Chekroun | L. Mabille | F. Parent | A. Seferian | S. Bulifon | C. Meyer
[1] Wei Lu,et al. Toward a standard for the evaluation of PET‐Auto‐Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation , 2017, Medical physics.
[2] Habib Zaidi,et al. Classification and evaluation strategies of auto‐segmentation approaches for PET: Report of AAPM task group No. 211 , 2017, Medical physics.
[3] Maximilien Vermandel,et al. Is STAPLE algorithm confident to assess segmentation methods in PET imaging? , 2015, Physics in medicine and biology.
[4] L. Massoptier,et al. Impact of consensus contours from multiple PET segmentation methods on the accuracy of functional volume delineation , 2015, European Journal of Nuclear Medicine and Molecular Imaging.
[5] Michalis Aristophanous,et al. A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy. , 2015, Medical physics.
[6] Eric J. W. Visser,et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0 , 2014, European Journal of Nuclear Medicine and Molecular Imaging.
[7] G. Parker,et al. Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome , 2014, Clinical Cancer Research.
[8] Ulas Bagci,et al. A review on segmentation of positron emission tomography images , 2014, Comput. Biol. Medicine.
[9] D. Bates,et al. Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.
[10] S. Baylin,et al. Cancer epigenetics: tumor heterogeneity, plasticity of stem-like states, and drug resistance. , 2014, Molecular cell.
[11] H Zaidi,et al. Contourlet-based active contour model for PET image segmentation. , 2013, Medical physics.
[12] C. Rübe,et al. PET-based delineation of tumour volumes in lung cancer: comparison with pathological findings , 2013, European Journal of Nuclear Medicine and Molecular Imaging.
[13] Milan Sonka,et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.
[14] P. A. Futreal,et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.
[15] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[16] Issam El Naqa,et al. Tools for consensus analysis of experts' contours for radiotherapy structure definitions. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[17] F Hofheinz,et al. Effects of cold sphere walls in PET phantom measurements on the volume reproducing threshold , 2010, Physics in medicine and biology.
[18] Issam El Naqa,et al. Development of RTOG consensus guidelines for the definition of the clinical target volume for postoperative conformal radiation therapy for prostate cancer. , 2010, International journal of radiation oncology, biology, physics.
[19] Issam El Naqa,et al. Elective clinical target volumes for conformal therapy in anorectal cancer: a radiation therapy oncology group consensus panel contouring atlas. , 2009, International journal of radiation oncology, biology, physics.
[20] C. Ménard,et al. RTOG GU Radiation oncology specialists reach consensus on pelvic lymph node volumes for high-risk prostate cancer. , 2009, International journal of radiation oncology, biology, physics.
[21] Chung-Ming Chen,et al. Automatic segmentation of liver PET images , 2008, Comput. Medical Imaging Graph..
[22] G Loi,et al. Threshold segmentation for PET target volume delineation in radiation treatment planning: the role of target-to-background ratio and target size. , 2008, Medical physics.
[23] Nico Karssemeijer,et al. A novel iterative method for lesion delineation and volumetric quantification with FDG PET , 2007, Nuclear medicine communications.
[24] Andreas Bockisch,et al. Segmentation of PET volumes by iterative image thresholding. , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[25] Anne Bol,et al. A gradient-based method for segmenting FDG-PET images: methodology and validation , 2007, European Journal of Nuclear Medicine and Molecular Imaging.
[26] Sasa Mutic,et al. 18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate? , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[27] Guido Gerig,et al. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.
[28] Wilson Roa,et al. A local contrast based approach to threshold segmentation for PET target volume delineation. , 2006, Medical physics.
[29] C. Rübe,et al. Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-Small cell lung cancer. , 2005, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[30] William M. Wells,et al. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation , 2004, IEEE Transactions on Medical Imaging.
[31] Ron Kikinis,et al. Statistical validation of image segmentation quality based on a spatial overlap index. , 2004, Academic radiology.
[32] Di Yan,et al. Defining a radiotherapy target with positron emission tomography. , 2002, International journal of radiation oncology, biology, physics.
[33] S M Larson,et al. Segmentation of lung lesion volume by adaptive positron emission tomography image thresholding , 1997, Cancer.
[34] M. King,et al. SPECT volume quantitation: influence of spatial resolution, source size and shape, and voxel size. , 1991, Medical physics.
[35] J. R. Landis,et al. The measurement of observer agreement for categorical data. , 1977, Biometrics.