BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 31108468)

  • 1. Impact of intensity discretization on textural indices of [
    Forgács A; Béresová M; Garai I; Lassen ML; Beyer T; DiFranco MD; Berényi E; Balkay L
    Phys Med Biol; 2019 Jun; 64(12):125016. PubMed ID: 31108468
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Effect of grey-level discretization on texture feature on different weighted MRI images of diverse disease groups.
    Veres G; Vas NF; Lyngby Lassen M; Béresová M; K Krizsan A; Forgács A; Berényi E; Balkay L
    PLoS One; 2021; 16(6):e0253419. PubMed ID: 34143830
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. The Impact of Optimal Respiratory Gating and Image Noise on Evaluation of Intratumor Heterogeneity on 18F-FDG PET Imaging of Lung Cancer.
    Grootjans W; Tixier F; van der Vos CS; Vriens D; Le Rest CC; Bussink J; Oyen WJ; de Geus-Oei LF; Visvikis D; Visser EP
    J Nucl Med; 2016 Nov; 57(11):1692-1698. PubMed ID: 27283931
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Significance of the impact of motion compensation on the variability of PET image features.
    Carles M; Bach T; Torres-Espallardo I; Baltas D; Nestle U; Martí-Bonmatí L
    Phys Med Biol; 2018 Mar; 63(6):065013. PubMed ID: 29469054
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The precision of textural analysis in (18)F-FDG-PET scans of oesophageal cancer.
    Doumou G; Siddique M; Tsoumpas C; Goh V; Cook GJ
    Eur Radiol; 2015 Sep; 25(9):2805-12. PubMed ID: 25994189
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Robustness of [
    Palomino-Fernández D; Seiffert AP; Gómez-Grande A; Jiménez López-Guarch C; Moreno G; Bueno H; Gómez EJ; Sánchez-González P
    Comput Methods Programs Biomed; 2024 Feb; 244():107981. PubMed ID: 38154326
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Robustness of Radiomic Features in [
    Lu L; Lv W; Jiang J; Ma J; Feng Q; Rahmim A; Chen W
    Mol Imaging Biol; 2016 Dec; 18(6):935-945. PubMed ID: 27324369
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer.
    Orlhac F; Soussan M; Chouahnia K; Martinod E; Buvat I
    PLoS One; 2015; 10(12):e0145063. PubMed ID: 26669541
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Intra-tumour 18F-FDG uptake heterogeneity decreases the reliability on target volume definition with positron emission tomography/computed tomography imaging.
    Dong X; Wu P; Sun X; Li W; Wan H; Yu J; Xing L
    J Med Imaging Radiat Oncol; 2015 Jun; 59(3):338-45. PubMed ID: 25708154
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Effects of Tracer Uptake Time in Non-Small Cell Lung Cancer
    Kolinger GD; García DV; Kramer GM; Frings V; Zwezerijnen GJC; Smit EF; de Langen AJ; Buvat I; Boellaard R
    J Nucl Med; 2022 Jun; 63(6):919-924. PubMed ID: 34933890
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Impact of acquisition count statistics reduction and SUV discretization on PET radiomic features in pediatric 18F-FDG-PET/MRI examinations.
    Branchini M; Zorz A; Zucchetta P; Bettinelli A; De Monte F; Cecchin D; Paiusco M
    Phys Med; 2019 Mar; 59():117-126. PubMed ID: 30928060
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Interchangeability of radiomic features between [18F]-FDG PET/CT and [18F]-FDG PET/MR.
    Vuong D; Tanadini-Lang S; Huellner MW; Veit-Haibach P; Unkelbach J; Andratschke N; Kraft J; Guckenberger M; Bogowicz M
    Med Phys; 2019 Apr; 46(4):1677-1685. PubMed ID: 30714158
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC?
    Karacavus S; Yılmaz B; Tasdemir A; Kayaaltı Ö; Kaya E; İçer S; Ayyıldız O
    J Digit Imaging; 2018 Apr; 31(2):210-223. PubMed ID: 28685320
    [TBL] [Abstract][Full Text] [Related]  

  • 15.
    Lasnon C; Majdoub M; Lavigne B; Do P; Madelaine J; Visvikis D; Hatt M; Aide N
    Eur J Nucl Med Mol Imaging; 2016 Dec; 43(13):2324-2335. PubMed ID: 27325312
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Influence of image preprocessing on the segmentation-based reproducibility of radiomic features:
    Koçak B; Yüzkan S; Mutlu S; Karagülle M; Kala A; Kadıoğlu M; Solak S; Sunman Ş; Temiz ZH; Ganiyusufoğlu AK
    Diagn Interv Radiol; 2024 May; 30(3):152-162. PubMed ID: 38073244
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.
    Leijenaar RT; Nalbantov G; Carvalho S; van Elmpt WJ; Troost EG; Boellaard R; Aerts HJ; Gillies RJ; Lambin P
    Sci Rep; 2015 Aug; 5():11075. PubMed ID: 26242464
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Quantitative radiomics: Validating image textural features for oncological PET in lung cancer.
    Yang F; Young LA; Johnson PB
    Radiother Oncol; 2018 Nov; 129(2):209-217. PubMed ID: 30279049
    [TBL] [Abstract][Full Text] [Related]  

  • 19. FDG-PET-based differential uptake volume histograms: a possible approach towards definition of biological target volumes.
    Devic S; Mohammed H; Tomic N; Aldelaijan S; De Blois F; Seuntjens J; Lehnert S; Faria S
    Br J Radiol; 2016 Jun; 89(1062):20150388. PubMed ID: 27007269
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 6.