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.
105 related articles for article (PubMed ID: 35204515)
1. Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas. Revailler W; Cottereau AS; Rossi C; Noyelle R; Trouillard T; Morschhauser F; Casasnovas O; Thieblemont C; Gouill SL; André M; Ghesquieres H; Ricci R; Meignan M; Kanoun S Diagnostics (Basel); 2022 Feb; 12(2):. PubMed ID: 35204515 [TBL] [Abstract][Full Text] [Related]
2. Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network. Blanc-Durand P; Jégou S; Kanoun S; Berriolo-Riedinger A; Bodet-Milin C; Kraeber-Bodéré F; Carlier T; Le Gouill S; Casasnovas RO; Meignan M; Itti E Eur J Nucl Med Mol Imaging; 2021 May; 48(5):1362-1370. PubMed ID: 33097974 [TBL] [Abstract][Full Text] [Related]
3. TMTV-Net: fully automated total metabolic tumor volume segmentation in lymphoma PET/CT images - a multi-center generalizability analysis. Yousefirizi F; Klyuzhin IS; O JH; Harsini S; Tie X; Shiri I; Shin M; Lee C; Cho SY; Bradshaw TJ; Zaidi H; Bénard F; Sehn LH; Savage KJ; Steidl C; Uribe CF; Rahmim A Eur J Nucl Med Mol Imaging; 2024 Jun; 51(7):1937-1954. PubMed ID: 38326655 [TBL] [Abstract][Full Text] [Related]
5. Deep learning-based tumour segmentation and total metabolic tumour volume prediction in the prognosis of diffuse large B-cell lymphoma patients in 3D FDG-PET images. Jiang C; Chen K; Teng Y; Ding C; Zhou Z; Gao Y; Wu J; He J; He K; Zhang J Eur Radiol; 2022 Jul; 32(7):4801-4812. PubMed ID: 35166895 [TBL] [Abstract][Full Text] [Related]
6. Whole liver segmentation based on deep learning and manual adjustment for clinical use in SIRT. Tang X; Jafargholi Rangraz E; Coudyzer W; Bertels J; Robben D; Schramm G; Deckers W; Maleux G; Baete K; Verslype C; Gooding MJ; Deroose CM; Nuyts J Eur J Nucl Med Mol Imaging; 2020 Nov; 47(12):2742-2752. PubMed ID: 32314026 [TBL] [Abstract][Full Text] [Related]
7. A 3D deep convolutional neural network approach for the automated measurement of cerebellum tracer uptake in FDG PET-CT scans. Xiong X; Linhardt TJ; Liu W; Smith BJ; Sun W; Bauer C; Sunderland JJ; Graham MM; Buatti JM; Beichel RR Med Phys; 2020 Mar; 47(3):1058-1066. PubMed ID: 31855287 [TBL] [Abstract][Full Text] [Related]
8. Prognostic value of metabolic tumour volume on baseline Shagera QA; Cheon GJ; Koh Y; Yoo MY; Kang KW; Lee DS; Kim EE; Yoon SS; Chung JK Eur J Nucl Med Mol Imaging; 2019 Jul; 46(7):1417-1427. PubMed ID: 30941463 [TBL] [Abstract][Full Text] [Related]
9. Deep learning for segmentation of 49 selected bones in CT scans: First step in automated PET/CT-based 3D quantification of skeletal metastases. Lindgren Belal S; Sadik M; Kaboteh R; Enqvist O; Ulén J; Poulsen MH; Simonsen J; Høilund-Carlsen PF; Edenbrandt L; Trägårdh E Eur J Radiol; 2019 Apr; 113():89-95. PubMed ID: 30927965 [TBL] [Abstract][Full Text] [Related]
10. Metabolic tumour volume in Hodgkin lymphoma-A comparison between manual and AI-based analysis. Sadik M; Barrington SF; Trägårdh E; Saboury B; Nielsen AL; Jakobsen AL; Gongora JLL; Urdaneta JL; Kumar R; Edenbrandt L Clin Physiol Funct Imaging; 2024 May; 44(3):220-227. PubMed ID: 38011940 [TBL] [Abstract][Full Text] [Related]
11. Tumor fragmentation estimated by volume surface ratio of tumors measured on 18F-FDG PET/CT is an independent prognostic factor of diffuse large B-cell lymphoma. Decazes P; Becker S; Toledano MN; Vera P; Desbordes P; Jardin F; Tilly H; Gardin I Eur J Nucl Med Mol Imaging; 2018 Sep; 45(10):1672-1679. PubMed ID: 29705879 [TBL] [Abstract][Full Text] [Related]
12. An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images. Boehringer AS; Sanaat A; Arabi H; Zaidi H Insights Imaging; 2023 Aug; 14(1):141. PubMed ID: 37620554 [TBL] [Abstract][Full Text] [Related]
13. Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation. Laukamp KR; Pennig L; Thiele F; Reimer R; Görtz L; Shakirin G; Zopfs D; Timmer M; Perkuhn M; Borggrefe J Clin Neuroradiol; 2021 Jun; 31(2):357-366. PubMed ID: 32060575 [TBL] [Abstract][Full Text] [Related]
14. Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT. Bruns S; Wolterink JM; Takx RAP; van Hamersvelt RW; Suchá D; Viergever MA; Leiner T; Išgum I Med Phys; 2020 Oct; 47(10):5048-5060. PubMed ID: 32786071 [TBL] [Abstract][Full Text] [Related]
15. Weakly supervised segmentation of tumor lesions in PET-CT hybrid imaging. Früh M; Fischer M; Schilling A; Gatidis S; Hepp T J Med Imaging (Bellingham); 2021 Sep; 8(5):054003. PubMed ID: 34660843 [No Abstract] [Full Text] [Related]
16. Two-stage deep learning model for fully automated pancreas segmentation on computed tomography: Comparison with intra-reader and inter-reader reliability at full and reduced radiation dose on an external dataset. Panda A; Korfiatis P; Suman G; Garg SK; Polley EC; Singh DP; Chari ST; Goenka AH Med Phys; 2021 May; 48(5):2468-2481. PubMed ID: 33595105 [TBL] [Abstract][Full Text] [Related]
17. Deep convolutional neural networks for the automated segmentation of malignant pleural mesothelioma on computed tomography scans. Gudmundsson E; Straus CM; Armato SG J Med Imaging (Bellingham); 2018 Jul; 5(3):034503. PubMed ID: 30840717 [TBL] [Abstract][Full Text] [Related]
18. Baseline total metabolic tumor volume combined with international peripheral T-cell lymphoma project may improve prognostic stratification for patients with peripheral T-cell lymphoma (PTCL). Jiang C; Teng Y; Chen J; Wang Z; Zhou Z; Ding C; Xu J EJNMMI Res; 2020 Sep; 10(1):110. PubMed ID: 32965554 [TBL] [Abstract][Full Text] [Related]
19. Prognostic value of baseline total metabolic tumour volume of Gong H; Li T; Li J; Tang L; Ding C EJNMMI Res; 2021 Jul; 11(1):64. PubMed ID: 34264417 [TBL] [Abstract][Full Text] [Related]
20. Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning. Berhane H; Scott M; Elbaz M; Jarvis K; McCarthy P; Carr J; Malaisrie C; Avery R; Barker AJ; Robinson JD; Rigsby CK; Markl M Magn Reson Med; 2020 Oct; 84(4):2204-2218. PubMed ID: 32167203 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]