1039 related articles for article (PubMed ID: 27147360)
1. A Dirichlet process mixture model for automatic (18)F-FDG PET image segmentation: Validation study on phantoms and on lung and esophageal lesions.
Giri MG; Cavedon C; Mazzarotto R; Ferdeghini M
Med Phys; 2016 May; 43(5):2491. PubMed ID: 27147360
[TBL] [Abstract][Full Text] [Related]
2. Defining a radiotherapy target with positron emission tomography.
Black QC; Grills IS; Kestin LL; Wong CY; Wong JW; Martinez AA; Yan D
Int J Radiat Oncol Biol Phys; 2004 Nov; 60(4):1272-82. PubMed ID: 15519800
[TBL] [Abstract][Full Text] [Related]
3. Clinical respiratory motion correction software (reconstruct, register and averaged-RRA), for
Bouyeure-Petit AC; Chastan M; Edet-Sanson A; Becker S; Thureau S; Houivet E; Vera P; Hapdey S
Br J Radiol; 2017 Feb; 90(1070):20160549. PubMed ID: 27936893
[TBL] [Abstract][Full Text] [Related]
4. Adaptive region-growing with maximum curvature strategy for tumor segmentation in
Tan S; Li L; Choi W; Kang MK; D'Souza WD; Lu W
Phys Med Biol; 2017 Jul; 62(13):5383-5402. PubMed ID: 28604372
[TBL] [Abstract][Full Text] [Related]
5. Influence of cold walls on PET image quantification and volume segmentation: a phantom study.
Berthon B; Marshall C; Edwards A; Evans M; Spezi E
Med Phys; 2013 Aug; 40(8):082505. PubMed ID: 23927350
[TBL] [Abstract][Full Text] [Related]
6. Background based Gaussian mixture model lesion segmentation in PET.
Soffientini CD; De Bernardi E; Zito F; Castellani M; Baselli G
Med Phys; 2016 May; 43(5):2662. PubMed ID: 27147375
[TBL] [Abstract][Full Text] [Related]
7. The use of zeolites to generate PET phantoms for the validation of quantification strategies in oncology.
Zito F; De Bernardi E; Soffientini C; Canzi C; Casati R; Gerundini P; Baselli G
Med Phys; 2012 Sep; 39(9):5353-61. PubMed ID: 22957603
[TBL] [Abstract][Full Text] [Related]
8. An iterative technique to segment PET lesions using a Monte Carlo based mathematical model.
Nehmeh SA; El-Zeftawy H; Greco C; Schwartz J; Erdi YE; Kirov A; Schmidtlein CR; Gyau AB; Larson SM; Humm JL
Med Phys; 2009 Oct; 36(10):4803-9. PubMed ID: 19928110
[TBL] [Abstract][Full Text] [Related]
9. Segmentation of PET volumes by iterative image thresholding.
Jentzen W; Freudenberg L; Eising EG; Heinze M; Brandau W; Bockisch A
J Nucl Med; 2007 Jan; 48(1):108-14. PubMed ID: 17204706
[TBL] [Abstract][Full Text] [Related]
10. Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans.
Ulrich EJ; Sunderland JJ; Smith BJ; Mohiuddin I; Parkhurst J; Plichta KA; Buatti JM; Beichel RR
Med Phys; 2018 Jan; 45(1):258-276. PubMed ID: 29091269
[TBL] [Abstract][Full Text] [Related]
11. Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.
Altazi BA; Zhang GG; Fernandez DC; Montejo ME; Hunt D; Werner J; Biagioli MC; Moros EG
J Appl Clin Med Phys; 2017 Nov; 18(6):32-48. PubMed ID: 28891217
[TBL] [Abstract][Full Text] [Related]
12. 18F-FDG-PET partial volume effect correction using a modified recovery coefficient approach based on functional volume and local contrast: physical validation and clinical feasibility in oncology.
Anouan KJ; Lelandais B; Edet-Sanson A; Ruan S; Vera P; Gardin I; Hapdey S
Q J Nucl Med Mol Imaging; 2017 Sep; 61(3):301-313. PubMed ID: 26407135
[TBL] [Abstract][Full Text] [Related]
13. Contourlet-based active contour model for PET image segmentation.
Abdoli M; Dierckx RA; Zaidi H
Med Phys; 2013 Aug; 40(8):082507. PubMed ID: 23927352
[TBL] [Abstract][Full Text] [Related]
14. Rapid Contour-based Segmentation for
Besson FL; Henry T; Meyer C; Chevance V; Roblot V; Blanchet E; Arnould V; Grimon G; Chekroun M; Mabille L; Parent F; Seferian A; Bulifon S; Montani D; Humbert M; Chaumet-Riffaud P; Lebon V; Durand E
Radiology; 2018 Jul; 288(1):277-284. PubMed ID: 29613842
[TBL] [Abstract][Full Text] [Related]
15. Comparison of 3 methods of automated internal carotid segmentation in human brain PET studies: application to the estimation of arterial input function.
Zanotti-Fregonara P; Maroy R; Comtat C; Jan S; Gaura V; Bar-Hen A; Ribeiro MJ; Trébossen R
J Nucl Med; 2009 Mar; 50(3):461-7. PubMed ID: 19223421
[TBL] [Abstract][Full Text] [Related]
16. A novel fuzzy C-means algorithm for unsupervised heterogeneous tumor quantification in PET.
Belhassen S; Zaidi H
Med Phys; 2010 Mar; 37(3):1309-24. PubMed ID: 20384268
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of the Accuracy of Standardized Uptake Values of
Tlostanova MS; Chipiga LA
Sovrem Tekhnologii Med; 2021; 13(3):15-23. PubMed ID: 34603751
[TBL] [Abstract][Full Text] [Related]
18. A Novel Framework for Automated Segmentation and Labeling of Homogeneous Versus Heterogeneous Lung Tumors in [
Soufi M; Kamali-Asl A; Geramifar P; Rahmim A
Mol Imaging Biol; 2017 Jun; 19(3):456-468. PubMed ID: 27770402
[TBL] [Abstract][Full Text] [Related]
19. Accuracy and Precision of Partial-Volume Correction in Oncological PET/CT Studies.
Cysouw MCF; Kramer GM; Hoekstra OS; Frings V; de Langen AJ; Smit EF; van den Eertwegh AJ; Oprea-Lager DE; Boellaard R
J Nucl Med; 2016 Oct; 57(10):1642-1649. PubMed ID: 27230933
[TBL] [Abstract][Full Text] [Related]
20. Tumor delineation using PET in head and neck cancers: threshold contouring and lesion volumes.
Ford EC; Kinahan PE; Hanlon L; Alessio A; Rajendran J; Schwartz DL; Phillips M
Med Phys; 2006 Nov; 33(11):4280-8. PubMed ID: 17153406
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
