These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
42. Prognostic Value of Metabolic and Volumetric Parameters of Preoperative FDG-PET/CT in Patients With Resectable Pancreatic Cancer. Im HJ; Oo S; Jung W; Jang JY; Kim SW; Cheon GJ; Kang KW; Chung JK; Kim EE; Lee DS Medicine (Baltimore); 2016 May; 95(19):e3686. PubMed ID: 27175707 [TBL] [Abstract][Full Text] [Related]
43. Correlation between Zhao J; Wang H J Med Imaging Radiat Oncol; 2021 Apr; 65(2):188-194. PubMed ID: 33538120 [TBL] [Abstract][Full Text] [Related]
44. Prognostic significance of neutrophil/lymphocyte ratio (NLR) and correlation with PET-CT metabolic parameters in small cell lung cancer (SCLC). Mirili C; Guney IB; Paydas S; Seydaoglu G; Kapukaya TK; Ogul A; Gokcay S; Buyuksimsek M; Yetisir AE; Karaalioglu B; Tohumcuoglu M Int J Clin Oncol; 2019 Feb; 24(2):168-178. PubMed ID: 30109543 [TBL] [Abstract][Full Text] [Related]
45. Inter-observer and segmentation method variability of textural analysis in pre-therapeutic FDG PET/CT in head and neck cancer. Guezennec C; Bourhis D; Orlhac F; Robin P; Corre JB; Delcroix O; Gobel Y; Schick U; Salaün PY; Abgral R PLoS One; 2019; 14(3):e0214299. PubMed ID: 30921388 [TBL] [Abstract][Full Text] [Related]
46. Utility of Volumetric Metabolic Parameters on Preoperative FDG PET/CT for Predicting Tumor Lymphovascular Invasion in Non-Small Cell Lung Cancer. Li C; Tian Y; Shen Y; Wen B; He Y AJR Am J Roentgenol; 2021 Dec; 217(6):1433-1443. PubMed ID: 33978465 [No Abstract] [Full Text] [Related]
47. Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers. Xiong X; Smith BJ; Graves SA; Graham MM; Buatti JM; Beichel RR Tomography; 2023 Oct; 9(5):1933-1948. PubMed ID: 37888743 [TBL] [Abstract][Full Text] [Related]
48. [Prognostic value of pretreatment (18)F-FDG PET-CT for patients with advanced diffuse large B-cell lymphoma]. Ding CY; Guo Z; Sun J; Yang WP; Li TR Zhonghua Zhong Liu Za Zhi; 2018 Jul; 40(7):528-533. PubMed ID: 30060362 [No Abstract] [Full Text] [Related]
49. Semi-automated Keijzer K; Niezink AGH; de Boer JW; van Doesum JA; Noordzij W; van Meerten T; van Dijk LV Comput Struct Biotechnol J; 2023; 21():1102-1114. PubMed ID: 36789266 [TBL] [Abstract][Full Text] [Related]
51. Whole-body MRI, FDG-PET/CT, and bone marrow biopsy, for the assessment of bone marrow involvement in patients with newly diagnosed lymphoma. Albano D; Patti C; Lagalla R; Midiri M; Galia M J Magn Reson Imaging; 2017 Apr; 45(4):1082-1089. PubMed ID: 27603267 [TBL] [Abstract][Full Text] [Related]
52. Prognostic value of total lesion glycolysis of baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography in diffuse large B-cell lymphoma. Zhou M; Chen Y; Huang H; Zhou X; Liu J; Huang G Oncotarget; 2016 Dec; 7(50):83544-83553. PubMed ID: 27835875 [TBL] [Abstract][Full Text] [Related]
53. A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging. Bagci U; Foster B; Miller-Jaster K; Luna B; Dey B; Bishai WR; Jonsson CB; Jain S; Mollura DJ EJNMMI Res; 2013 Jul; 3(1):55. PubMed ID: 23879987 [TBL] [Abstract][Full Text] [Related]
54. Application of partial volume effect correction and 4D PET in the quantification of FDG avid lung lesions. Salavati A; Borofsky S; Boon-Keng TK; Houshmand S; Khiewvan B; Saboury B; Codreanu I; Torigian DA; Zaidi H; Alavi A Mol Imaging Biol; 2015 Feb; 17(1):140-8. PubMed ID: 25080325 [TBL] [Abstract][Full Text] [Related]
55. Interobserver agreement of qualitative analysis and tumor delineation of 18F-fluoromisonidazole and 3'-deoxy-3'-18F-fluorothymidine PET images in lung cancer. Thureau S; Chaumet-Riffaud P; Modzelewski R; Fernandez P; Tessonnier L; Vervueren L; Cachin F; Berriolo-Riedinger A; Olivier P; Kolesnikov-Gauthier H; Blagosklonov O; Bridji B; Devillers A; Collombier L; Courbon F; Gremillet E; Houzard C; Caignon JM; Roux J; Aide N; Brenot-Rossi I; Doyeux K; Dubray B; Vera P J Nucl Med; 2013 Sep; 54(9):1543-50. PubMed ID: 23918733 [TBL] [Abstract][Full Text] [Related]
56. More advantages in detecting bone and soft tissue metastases from prostate cancer using Pianou NK; Stavrou PZ; Vlontzou E; Rondogianni P; Exarhos DN; Datseris IE Hell J Nucl Med; 2019; 22(1):6-9. PubMed ID: 30843003 [TBL] [Abstract][Full Text] [Related]
57. Diffusion-weighted MRI and Xu X; Sun ZY; Wu HW; Zhang CP; Hu B; Rong L; Chen HY; Xie HY; Wang YM; Lin HP; Bai YR; Ye Q; Ma XM Radiat Oncol; 2021 Jul; 16(1):132. PubMed ID: 34281566 [TBL] [Abstract][Full Text] [Related]
58. Delineation of lung cancer with FDG PET/CT during radiation therapy. Ganem J; Thureau S; Gardin I; Modzelewski R; Hapdey S; Vera P Radiat Oncol; 2018 Nov; 13(1):219. PubMed ID: 30419929 [TBL] [Abstract][Full Text] [Related]
59. Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data. Beichel RR; Smith BJ; Bauer C; Ulrich EJ; Ahmadvand P; Budzevich MM; Gillies RJ; Goldgof D; Grkovski M; Hamarneh G; Huang Q; Kinahan PE; Laymon CM; Mountz JM; Muzi JP; Muzi M; Nehmeh S; Oborski MJ; Tan Y; Zhao B; Sunderland JJ; Buatti JM Med Phys; 2017 Feb; 44(2):479-496. PubMed ID: 28205306 [TBL] [Abstract][Full Text] [Related]
60. Prediction of Lymph Node Maximum Standardized Uptake Value in Patients With Cancer Using a 3D Convolutional Neural Network: A Proof-of-Concept Study. Shaish H; Mutasa S; Makkar J; Chang P; Schwartz L; Ahmed F AJR Am J Roentgenol; 2019 Feb; 212(2):238-244. PubMed ID: 30540209 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]