133 related articles for article (PubMed ID: 36442609)
1. Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study.
Buchner JA; Kofler F; Etzel L; Mayinger M; Christ SM; Brunner TB; Wittig A; Menze B; Zimmer C; Meyer B; Guckenberger M; Andratschke N; El Shafie RA; Debus J; Rogers S; Riesterer O; Schulze K; Feldmann HJ; Blanck O; Zamboglou C; Ferentinos K; Wolff R; Eitz KA; Combs SE; Bernhardt D; Wiestler B; Peeken JC
Radiother Oncol; 2023 Jan; 178():109425. PubMed ID: 36442609
[TBL] [Abstract][Full Text] [Related]
2. A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.
Rundo L; Stefano A; Militello C; Russo G; Sabini MG; D'Arrigo C; Marletta F; Ippolito M; Mauri G; Vitabile S; Gilardi MC
Comput Methods Programs Biomed; 2017 Jun; 144():77-96. PubMed ID: 28495008
[TBL] [Abstract][Full Text] [Related]
3. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs.
Tang F; Liang S; Zhong T; Huang X; Deng X; Zhang Y; Zhou L
Eur Radiol; 2020 Feb; 30(2):823-832. PubMed ID: 31650265
[TBL] [Abstract][Full Text] [Related]
4. Identifying core MRI sequences for reliable automatic brain metastasis segmentation.
Buchner JA; Peeken JC; Etzel L; Ezhov I; Mayinger M; Christ SM; Brunner TB; Wittig A; Menze BH; Zimmer C; Meyer B; Guckenberger M; Andratschke N; El Shafie RA; Debus J; Rogers S; Riesterer O; Schulze K; Feldmann HJ; Blanck O; Zamboglou C; Ferentinos K; Bilger A; Grosu AL; Wolff R; Kirschke JS; Eitz KA; Combs SE; Bernhardt D; Rueckert D; Piraud M; Wiestler B; Kofler F
Radiother Oncol; 2023 Nov; 188():109901. PubMed ID: 37678623
[TBL] [Abstract][Full Text] [Related]
5. Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data.
Bousabarah K; Ruge M; Brand JS; Hoevels M; Rueß D; Borggrefe J; Große Hokamp N; Visser-Vandewalle V; Maintz D; Treuer H; Kocher M
Radiat Oncol; 2020 Apr; 15(1):87. PubMed ID: 32312276
[TBL] [Abstract][Full Text] [Related]
6. Evaluating contouring accuracy and dosimetry impact of current MRI-guided adaptive radiation therapy for brain metastases: a retrospective study.
Wang B; Liu Y; Zhang J; Yin S; Liu B; Ding S; Qiu B; Deng X
J Neurooncol; 2024 Mar; 167(1):123-132. PubMed ID: 38300388
[TBL] [Abstract][Full Text] [Related]
7. Machine Segmentation of Pelvic Anatomy in MRI-Assisted Radiosurgery (MARS) for Prostate Cancer Brachytherapy.
Sanders JW; Lewis GD; Thames HD; Kudchadker RJ; Venkatesan AM; Bruno TL; Ma J; Pagel MD; Frank SJ
Int J Radiat Oncol Biol Phys; 2020 Dec; 108(5):1292-1303. PubMed ID: 32634543
[TBL] [Abstract][Full Text] [Related]
8. MetNet: Computer-aided segmentation of brain metastases in post-contrast T1-weighted magnetic resonance imaging.
Zhou Z; Sanders JW; Johnson JM; Gule-Monroe M; Chen M; Briere TM; Wang Y; Son JB; Pagel MD; Ma J; Li J
Radiother Oncol; 2020 Dec; 153():189-196. PubMed ID: 32937104
[TBL] [Abstract][Full Text] [Related]
9. Auto-segmentation of pancreatic tumor in multi-parametric MRI using deep convolutional neural networks.
Liang Y; Schott D; Zhang Y; Wang Z; Nasief H; Paulson E; Hall W; Knechtges P; Erickson B; Li XA
Radiother Oncol; 2020 Apr; 145():193-200. PubMed ID: 32045787
[TBL] [Abstract][Full Text] [Related]
10. Automatic segmentation of vestibular schwannomas from T1-weighted MRI with a deep neural network.
Wang H; Qu T; Bernstein K; Barbee D; Kondziolka D
Radiat Oncol; 2023 May; 18(1):78. PubMed ID: 37158968
[TBL] [Abstract][Full Text] [Related]
11. A potential field segmentation based method for tumor segmentation on multi-parametric MRI of glioma cancer patients.
Sun R; Wang K; Guo L; Yang C; Chen J; Ti Y; Sa Y
BMC Med Imaging; 2019 Jun; 19(1):48. PubMed ID: 31208349
[TBL] [Abstract][Full Text] [Related]
12. Automatic segmentation of brain metastases using T1 magnetic resonance and computed tomography images.
Hsu DG; Ballangrud Å; Shamseddine A; Deasy JO; Veeraraghavan H; Cervino L; Beal K; Aristophanous M
Phys Med Biol; 2021 Aug; 66(17):. PubMed ID: 34315148
[TBL] [Abstract][Full Text] [Related]
13. Fully Automated MR Detection and Segmentation of Brain Metastases in Non-small Cell Lung Cancer Using Deep Learning.
Jünger ST; Hoyer UCI; Schaufler D; Laukamp KR; Goertz L; Thiele F; Grunz JP; Schlamann M; Perkuhn M; Kabbasch C; Persigehl T; Grau S; Borggrefe J; Scheffler M; Shahzad R; Pennig L
J Magn Reson Imaging; 2021 Nov; 54(5):1608-1622. PubMed ID: 34032344
[TBL] [Abstract][Full Text] [Related]
14. Brain tumor segmentation using holistically nested neural networks in MRI images.
Zhuge Y; Krauze AV; Ning H; Cheng JY; Arora BC; Camphausen K; Miller RW
Med Phys; 2017 Oct; 44(10):5234-5243. PubMed ID: 28736864
[TBL] [Abstract][Full Text] [Related]
15. Deep Learning for Per-Fraction Automatic Segmentation of Gross Tumor Volume (GTV) and Organs at Risk (OARs) in Adaptive Radiotherapy of Cervical Cancer.
Breto AL; Spieler B; Zavala-Romero O; Alhusseini M; Patel NV; Asher DA; Xu IR; Baikovitz JB; Mellon EA; Ford JC; Stoyanova R; Portelance L
Front Oncol; 2022; 12():854349. PubMed ID: 35664789
[TBL] [Abstract][Full Text] [Related]
16. Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis.
Brugnara G; Isensee F; Neuberger U; Bonekamp D; Petersen J; Diem R; Wildemann B; Heiland S; Wick W; Bendszus M; Maier-Hein K; Kickingereder P
Eur Radiol; 2020 Apr; 30(4):2356-2364. PubMed ID: 31900702
[TBL] [Abstract][Full Text] [Related]
17. An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.
Fashandi H; Kuling G; Lu Y; Wu H; Martel AL
Med Phys; 2019 Mar; 46(3):1230-1244. PubMed ID: 30609062
[TBL] [Abstract][Full Text] [Related]
18. Fast, light, and scalable: harnessing data-mined line annotations for automated tumor segmentation on brain MRI.
Swinburne NC; Yadav V; Murthy KNK; Elnajjar P; Shih HH; Panyam PK; Santilli A; Gutman DC; Pike L; Moss NS; Stone J; Hatzoglou V; Shah A; Juluru K; Shah SP; Holodny AI; Young RJ;
Eur Radiol; 2023 Sep; 33(9):6582-6591. PubMed ID: 37042979
[TBL] [Abstract][Full Text] [Related]
19. Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network.
Charron O; Lallement A; Jarnet D; Noblet V; Clavier JB; Meyer P
Comput Biol Med; 2018 Apr; 95():43-54. PubMed ID: 29455079
[TBL] [Abstract][Full Text] [Related]
20. Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.
Perkuhn M; Stavrinou P; Thiele F; Shakirin G; Mohan M; Garmpis D; Kabbasch C; Borggrefe J
Invest Radiol; 2018 Nov; 53(11):647-654. PubMed ID: 29863600
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]