131 related articles for article (PubMed ID: 38528694)
1. Automated Detection and Segmentation of Bone Metastases on Spine MRI Using U-Net: A Multicenter Study.
Kim DH; Seo J; Lee JH; Jeon ET; Jeong D; Chae HD; Lee E; Kang JH; Choi YH; Kim HJ; Chai JW
Korean J Radiol; 2024 Apr; 25(4):363-373. PubMed ID: 38528694
[TBL] [Abstract][Full Text] [Related]
2. Joint MRI T1 Unenhancing and Contrast-enhancing Multiple Sclerosis Lesion Segmentation with Deep Learning in OPERA Trials.
Krishnan AP; Song Z; Clayton D; Gaetano L; Jia X; de Crespigny A; Bengtsson T; Carano RAD
Radiology; 2022 Mar; 302(3):662-673. PubMed ID: 34904871
[TBL] [Abstract][Full Text] [Related]
3. Conspicuity of bone metastases on fast Dixon-based multisequence whole-body MRI: clinical utility per sequence.
Costelloe CM; Madewell JE; Kundra V; Harrell RK; Bassett RL; Ma J
Magn Reson Imaging; 2013 Jun; 31(5):669-75. PubMed ID: 23290478
[TBL] [Abstract][Full Text] [Related]
4. Whole-body 3D T1-weighted MR imaging in patients with prostate cancer: feasibility and evaluation in screening for metastatic disease.
Pasoglou V; Michoux N; Peeters F; Larbi A; Tombal B; Selleslagh T; Omoumi P; Vande Berg BC; Lecouvet FE
Radiology; 2015 Apr; 275(1):155-66. PubMed ID: 25513855
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. MRI-based two-stage deep learning model for automatic detection and segmentation of brain metastases.
Li R; Guo Y; Zhao Z; Chen M; Liu X; Gong G; Wang L
Eur Radiol; 2023 May; 33(5):3521-3531. PubMed ID: 36695903
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI.
Grøvik E; Yi D; Iv M; Tong E; Rubin D; Zaharchuk G
J Magn Reson Imaging; 2020 Jan; 51(1):175-182. PubMed ID: 31050074
[TBL] [Abstract][Full Text] [Related]
10. Automatic Vertebral Body Segmentation Based on Deep Learning of Dixon Images for Bone Marrow Fat Fraction Quantification.
Zhou J; Damasceno PF; Chachad R; Cheung JR; Ballatori A; Lotz JC; Lazar AA; Link TM; Fields AJ; Krug R
Front Endocrinol (Lausanne); 2020; 11():612. PubMed ID: 32982989
[No Abstract] [Full Text] [Related]
11. Detection of vertebral metastases: a comparison between the modified Dixon turbo spin echo T
Hahn S; Lee YH; Suh JS
Br J Radiol; 2018 May; 91(1085):20170782. PubMed ID: 29393668
[TBL] [Abstract][Full Text] [Related]
12. Deep Learning Model for Automated Detection and Classification of Central Canal, Lateral Recess, and Neural Foraminal Stenosis at Lumbar Spine MRI.
Hallinan JTPD; Zhu L; Yang K; Makmur A; Algazwi DAR; Thian YL; Lau S; Choo YS; Eide SE; Yap QV; Chan YH; Tan JH; Kumar N; Ooi BC; Yoshioka H; Quek ST
Radiology; 2021 Jul; 300(1):130-138. PubMed ID: 33973835
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet.
Bien N; Rajpurkar P; Ball RL; Irvin J; Park A; Jones E; Bereket M; Patel BN; Yeom KW; Shpanskaya K; Halabi S; Zucker E; Fanton G; Amanatullah DF; Beaulieu CF; Riley GM; Stewart RJ; Blankenberg FG; Larson DB; Jones RH; Langlotz CP; Ng AY; Lungren MP
PLoS Med; 2018 Nov; 15(11):e1002699. PubMed ID: 30481176
[TBL] [Abstract][Full Text] [Related]
15. Bone Marrow Metastases: T2-weighted Dixon Spin-Echo Fat Images Can Replace T1-weighted Spin-Echo Images.
Maeder Y; Dunet V; Richard R; Becce F; Omoumi P
Radiology; 2018 Mar; 286(3):948-959. PubMed ID: 29095674
[TBL] [Abstract][Full Text] [Related]
16. Quantifying U-Net uncertainty in multi-parametric MRI-based glioma segmentation by spherical image projection.
Yang Z; Lafata K; Vaios E; Hu Z; Mullikin T; Yin FF; Wang C
Med Phys; 2024 Mar; 51(3):1931-1943. PubMed ID: 37696029
[TBL] [Abstract][Full Text] [Related]
17. Automated Detection of Brain Metastases on T1-Weighted MRI Using a Convolutional Neural Network: Impact of Volume Aware Loss and Sampling Strategy.
Chartrand G; Emiliani RD; Pawlowski SA; Markel DA; Bahig H; Cengarle-Samak A; Rajakesari S; Lavoie J; Ducharme S; Roberge D
J Magn Reson Imaging; 2022 Dec; 56(6):1885-1898. PubMed ID: 35624544
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Detection and Segmentation of Pelvic Bones Metastases in MRI Images for Patients With Prostate Cancer Based on Deep Learning.
Liu X; Han C; Cui Y; Xie T; Zhang X; Wang X
Front Oncol; 2021; 11():773299. PubMed ID: 34912716
[TBL] [Abstract][Full Text] [Related]
20. Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.
Kang H; Witanto JN; Pratama K; Lee D; Choi KS; Choi SH; Kim KM; Kim MS; Kim JW; Kim YH; Park SJ; Park CK
J Magn Reson Imaging; 2023 Mar; 57(3):871-881. PubMed ID: 35775971
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]