272 related articles for article (PubMed ID: 31855287)
1. 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]
2. Automated measurement of uptake in cerebellum, liver, and aortic arch in full-body FDG PET/CT scans.
Bauer C; Sun S; Sun W; Otis J; Wallace A; Smith BJ; Sunderland JJ; Graham MM; Sonka M; Buatti JM; Beichel RR
Med Phys; 2012 Jun; 39(6):3112-23. PubMed ID: 22755696
[TBL] [Abstract][Full Text] [Related]
3. A convolutional neural network for fully automated blood SUV determination to facilitate SUR computation in oncological FDG-PET.
Nikulin P; Hofheinz F; Maus J; Li Y; Bütof R; Lange C; Furth C; Zschaeck S; Kreissl MC; Kotzerke J; van den Hoff J
Eur J Nucl Med Mol Imaging; 2021 Apr; 48(4):995-1004. PubMed ID: 33006022
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. A convolutional neural network with self-attention for fully automated metabolic tumor volume delineation of head and neck cancer in [Formula: see text]F]FDG PET/CT.
Nikulin P; Zschaeck S; Maus J; Cegla P; Lombardo E; Furth C; Kaźmierska J; Rogasch JMM; Holzgreve A; Albert NL; Ferentinos K; Strouthos I; Hajiyianni M; Marschner SN; Belka C; Landry G; Cholewinski W; Kotzerke J; Hofheinz F; van den Hoff J
Eur J Nucl Med Mol Imaging; 2023 Jul; 50(9):2751-2766. PubMed ID: 37079128
[TBL] [Abstract][Full Text] [Related]
6. Automatic segmentation of prostate cancer metastases in PSMA PET/CT images using deep neural networks with weighted batch-wise dice loss.
Xu Y; Klyuzhin I; Harsini S; Ortiz A; Zhang S; Bénard F; Dodhia R; Uribe CF; Rahmim A; Lavista Ferres J
Comput Biol Med; 2023 May; 158():106882. PubMed ID: 37037147
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.
Lee YS; Hong N; Witanto JN; Choi YR; Park J; Decazes P; Eude F; Kim CO; Chang Kim H; Goo JM; Rhee Y; Yoon SH
Clin Nutr; 2021 Aug; 40(8):5038-5046. PubMed ID: 34365038
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Quantification of uptake in pelvis F-18 FLT PET-CT images using a 3D localization and segmentation CNN.
Xiong X; Smith BJ; Graves SA; Sunderland JJ; Graham MM; Gross BA; Buatti JM; Beichel RR
Med Phys; 2022 Mar; 49(3):1585-1598. PubMed ID: 34982836
[TBL] [Abstract][Full Text] [Related]
11.
Sibille L; Seifert R; Avramovic N; Vehren T; Spottiswoode B; Zuehlsdorff S; Schäfers M
Radiology; 2020 Feb; 294(2):445-452. PubMed ID: 31821122
[TBL] [Abstract][Full Text] [Related]
12. Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG-PET/CT in Hodgkin and non-Hodgkin lymphomas.
Sadik M; Lind E; Polymeri E; Enqvist O; Ulén J; Trägårdh E
Clin Physiol Funct Imaging; 2019 Jan; 39(1):78-84. PubMed ID: 30284376
[TBL] [Abstract][Full Text] [Related]
13. Direct inference of Patlak parametric images in whole-body PET/CT imaging using convolutional neural networks.
Zaker N; Haddad K; Faghihi R; Arabi H; Zaidi H
Eur J Nucl Med Mol Imaging; 2022 Oct; 49(12):4048-4063. PubMed ID: 35716176
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT-SEQUOIA.
van Praagh GD; Nienhuis PH; Reijrink M; Davidse MEJ; Duff LM; Spottiswoode BS; Mulder DJ; Prakken NHJ; Scarsbrook AF; Morgan AW; Tsoumpas C; Wolterink JM; Mouridsen KB; Borra RJH; Sinha B; Slart RHJA
Med Phys; 2024 Feb; ():. PubMed ID: 38323867
[TBL] [Abstract][Full Text] [Related]
16. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
17. Automated segmentation of the human supraclavicular fat depot via deep neural network in water-fat separated magnetic resonance images.
Zhao Y; Tang C; Cui B; Somasundaram A; Raspe J; Hu X; Holzapfel C; Junker D; Hauner H; Menze B; Wu M; Karampinos D
Quant Imaging Med Surg; 2023 Jul; 13(7):4699-4715. PubMed ID: 37456284
[TBL] [Abstract][Full Text] [Related]
18. Comparison of 11 automated PET segmentation methods in lymphoma.
Weisman AJ; Kieler MW; Perlman S; Hutchings M; Jeraj R; Kostakoglu L; Bradshaw TJ
Phys Med Biol; 2020 Nov; 65(23):235019. PubMed ID: 32906088
[TBL] [Abstract][Full Text] [Related]
19. Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision.
Kearney V; Chan JW; Wang T; Perry A; Yom SS; Solberg TD
Phys Med Biol; 2019 Jul; 64(13):135001. PubMed ID: 31181561
[TBL] [Abstract][Full Text] [Related]
20. Abdominal multi-organ auto-segmentation using 3D-patch-based deep convolutional neural network.
Kim H; Jung J; Kim J; Cho B; Kwak J; Jang JY; Lee SW; Lee JG; Yoon SM
Sci Rep; 2020 Apr; 10(1):6204. PubMed ID: 32277135
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
