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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 36574537)

  • 1. Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning.
    Phan AC; Cao HP; Le TN; Trieu TN; Phan TC
    Gene Expr Patterns; 2023 Mar; 47():119289. PubMed ID: 36574537
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Hounsfield Unit Variations-Based Liver Lesions Detection and Classification Using Deep Learning.
    Phan AC; Ngoan Trieu T; Cang Phan T
    Curr Med Imaging; 2023 Apr; ():. PubMed ID: 37132318
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.
    Gong H; Yu L; Leng S; Dilger SK; Ren L; Zhou W; Fletcher JG; McCollough CH
    Med Phys; 2019 May; 46(5):2052-2063. PubMed ID: 30889282
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
    Fu J; Yang Y; Singhrao K; Ruan D; Chu FI; Low DA; Lewis JH
    Med Phys; 2019 Sep; 46(9):3788-3798. PubMed ID: 31220353
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.
    Hamm CA; Wang CJ; Savic LJ; Ferrante M; Schobert I; Schlachter T; Lin M; Duncan JS; Weinreb JC; Chapiro J; Letzen B
    Eur Radiol; 2019 Jul; 29(7):3338-3347. PubMed ID: 31016442
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation.
    Lee H; Lee H; Hong H; Bae H; Lim JS; Kim J
    Med Phys; 2021 Sep; 48(9):5029-5046. PubMed ID: 34287951
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Segmentation of liver tumors with abdominal computed tomography using fully convolutional networks.
    Chen CI; Lu NH; Huang YH; Liu KY; Hsu SY; Matsushima A; Wang YM; Chen TB
    J Xray Sci Technol; 2022; 30(5):953-966. PubMed ID: 35754254
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automatic volumetric diagnosis of hepatocellular carcinoma based on four-phase CT scans with minimum extra information.
    Ling Y; Ying S; Xu L; Peng Z; Mao X; Chen Z; Ni J; Liu Q; Gong S; Kong D
    Front Oncol; 2022; 12():960178. PubMed ID: 36313647
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Liver tissue segmentation in multiphase CT scans using cascaded convolutional neural networks.
    Ouhmich F; Agnus V; Noblet V; Heitz F; Pessaux P
    Int J Comput Assist Radiol Surg; 2019 Aug; 14(8):1275-1284. PubMed ID: 31041697
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Shading artifact correction in breast CT using an interleaved deep learning segmentation and maximum-likelihood polynomial fitting approach.
    Ghazi P; Hernandez AM; Abbey C; Yang K; Boone JM
    Med Phys; 2019 Aug; 46(8):3414-3430. PubMed ID: 31102462
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Clinical application of mask region-based convolutional neural network for the automatic detection and segmentation of abnormal liver density based on hepatocellular carcinoma computed tomography datasets.
    Yang CJ; Wang CK; Fang YD; Wang JY; Su FC; Tsai HM; Lin YJ; Tsai HW; Yeh LR
    PLoS One; 2021; 16(8):e0255605. PubMed ID: 34375365
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Multiphase convolutional dense network for the classification of focal liver lesions on dynamic contrast-enhanced computed tomography.
    Cao SE; Zhang LQ; Kuang SC; Shi WQ; Hu B; Xie SD; Chen YN; Liu H; Chen SM; Jiang T; Ye M; Zhang HX; Wang J
    World J Gastroenterol; 2020 Jul; 26(25):3660-3672. PubMed ID: 32742134
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multichannel three-dimensional fully convolutional residual network-based focal liver lesion detection and classification in Gd-EOB-DTPA-enhanced MRI.
    Takenaga T; Hanaoka S; Nomura Y; Nakao T; Shibata H; Miki S; Yoshikawa T; Hayashi N; Abe O
    Int J Comput Assist Radiol Surg; 2021 Sep; 16(9):1527-1536. PubMed ID: 34075548
    [TBL] [Abstract][Full Text] [Related]  

  • 14. MR-based synthetic CT generation using a deep convolutional neural network method.
    Han X
    Med Phys; 2017 Apr; 44(4):1408-1419. PubMed ID: 28192624
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Non-invasive multi-channel deep learning convolutional neural networks for localization and classification of common hepatic lesions.
    Shah S; Mishra R; Szczurowska A; Guziński M
    Pol J Radiol; 2021; 86():e440-e448. PubMed ID: 34429791
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis.
    Ma H; Liu ZX; Zhang JJ; Wu FT; Xu CF; Shen Z; Yu CH; Li YM
    World J Gastroenterol; 2020 Sep; 26(34):5156-5168. PubMed ID: 32982116
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automatic Segmentation of Multiple Organs on 3D CT Images by Using Deep Learning Approaches.
    Zhou X
    Adv Exp Med Biol; 2020; 1213():135-147. PubMed ID: 32030668
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation.
    Budak Ü; Guo Y; Tanyildizi E; Şengür A
    Med Hypotheses; 2020 Jan; 134():109431. PubMed ID: 31669758
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Polycystic liver: automatic segmentation using deep learning on CT is faster and as accurate compared to manual segmentation.
    Cayot B; Milot L; Nempont O; Vlachomitrou AS; Langlois-Jacques C; Dumortier J; Boillot O; Arnaud K; Barten TRM; Drenth JPH; Valette PJ
    Eur Radiol; 2022 Jul; 32(7):4780-4790. PubMed ID: 35142898
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0.
    Agarwal M; Agarwal S; Saba L; Chabert GL; Gupta S; Carriero A; Pasche A; Danna P; Mehmedovic A; Faa G; Shrivastava S; Jain K; Jain H; Jujaray T; Singh IM; Turk M; Chadha PS; Johri AM; Khanna NN; Mavrogeni S; Laird JR; Sobel DW; Miner M; Balestrieri A; Sfikakis PP; Tsoulfas G; Misra DP; Agarwal V; Kitas GD; Teji JS; Al-Maini M; Dhanjil SK; Nicolaides A; Sharma A; Rathore V; Fatemi M; Alizad A; Krishnan PR; Yadav RR; Nagy F; Kincses ZT; Ruzsa Z; Naidu S; Viskovic K; Kalra MK; Suri JS
    Comput Biol Med; 2022 Jul; 146():105571. PubMed ID: 35751196
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.