BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

636 related articles for article (PubMed ID: 34763810)

  • 1. PSA-Net: Deep learning-based physician style-aware segmentation network for postoperative prostate cancer clinical target volumes.
    Balagopal A; Morgan H; Dohopolski M; Timmerman R; Shan J; Heitjan DF; Liu W; Nguyen D; Hannan R; Garant A; Desai N; Jiang S
    Artif Intell Med; 2021 Nov; 121():102195. PubMed ID: 34763810
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy.
    Balagopal A; Nguyen D; Morgan H; Weng Y; Dohopolski M; Lin MH; Barkousaraie AS; Gonzalez Y; Garant A; Desai N; Hannan R; Jiang S
    Med Image Anal; 2021 Aug; 72():102101. PubMed ID: 34111573
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
    Kawula M; Hadi I; Nierer L; Vagni M; Cusumano D; Boldrini L; Placidi L; Corradini S; Belka C; Landry G; Kurz C
    Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.
    Orlando N; Gillies DJ; Gyacskov I; Romagnoli C; D'Souza D; Fenster A
    Med Phys; 2020 Jun; 47(6):2413-2426. PubMed ID: 32166768
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An uncertainty-aware deep learning architecture with outlier mitigation for prostate gland segmentation in radiotherapy treatment planning.
    Li X; Bagher-Ebadian H; Gardner S; Kim J; Elshaikh M; Movsas B; Zhu D; Chetty IJ
    Med Phys; 2023 Jan; 50(1):311-322. PubMed ID: 36112996
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic clinical target volume delineation for cervical cancer in CT images using deep learning.
    Shi J; Ding X; Liu X; Li Y; Liang W; Wu J
    Med Phys; 2021 Jul; 48(7):3968-3981. PubMed ID: 33905545
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.
    Men K; Dai J; Li Y
    Med Phys; 2017 Dec; 44(12):6377-6389. PubMed ID: 28963779
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Mutual enhancing learning-based automatic segmentation of CT cardiac substructure.
    Momin S; Lei Y; McCall NS; Zhang J; Roper J; Harms J; Tian S; Lloyd MS; Liu T; Bradley JD; Higgins K; Yang X
    Phys Med Biol; 2022 May; 67(10):. PubMed ID: 35447610
    [No Abstract]   [Full Text] [Related]  

  • 9. Fast interactive medical image segmentation with weakly supervised deep learning method.
    Girum KB; Créhange G; Hussain R; Lalande A
    Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1437-1444. PubMed ID: 32653985
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography.
    Abbani N; Baudier T; Rit S; Franco FD; Okoli F; Jaouen V; Tilquin F; Barateau A; Simon A; de Crevoisier R; Bert J; Sarrut D
    Med Phys; 2022 Nov; 49(11):6930-6944. PubMed ID: 36000762
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. ARPM-net: A novel CNN-based adversarial method with Markov random field enhancement for prostate and organs at risk segmentation in pelvic CT images.
    Zhang Z; Zhao T; Gay H; Zhang W; Sun B
    Med Phys; 2021 Jan; 48(1):227-237. PubMed ID: 33151620
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Deep learning-based ultrasound auto-segmentation of the prostate with brachytherapy implanted needles.
    Hampole P; Harding T; Gillies D; Orlando N; Edirisinghe C; Mendez LC; D'Souza D; Velker V; Correa R; Helou J; Xing S; Fenster A; Hoover DA
    Med Phys; 2024 Apr; 51(4):2665-2677. PubMed ID: 37888789
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Fully automatic segmentation on prostate MR images based on cascaded fully convolution network.
    Zhu Y; Wei R; Gao G; Ding L; Zhang X; Wang X; Zhang J
    J Magn Reson Imaging; 2019 Apr; 49(4):1149-1156. PubMed ID: 30350434
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.
    Liu Y; Zhang M; Zhong Z; Zeng X
    Med Phys; 2023 Mar; 50(3):1528-1538. PubMed ID: 36057788
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.
    Ye LY; Miao XY; Cai WS; Xu WJ
    Comput Methods Programs Biomed; 2022 Jun; 221():106770. PubMed ID: 35640389
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Effect of dataset size, image quality, and image type on deep learning-based automatic prostate segmentation in 3D ultrasound.
    Orlando N; Gyacskov I; Gillies DJ; Guo F; Romagnoli C; D'Souza D; Cool DW; Hoover DA; Fenster A
    Phys Med Biol; 2022 Mar; 67(7):. PubMed ID: 35240585
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.
    da Silva GLF; Diniz PS; Ferreira JL; França JVF; Silva AC; de Paiva AC; de Cavalcanti EAA
    Med Biol Eng Comput; 2020 Sep; 58(9):1947-1964. PubMed ID: 32566988
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 32.