BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

124 related articles for article (PubMed ID: 37201475)

  • 21. 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]  

  • 22. Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.
    Savenije MHF; Maspero M; Sikkes GG; van der Voort van Zyp JRN; T J Kotte AN; Bol GH; T van den Berg CA
    Radiat Oncol; 2020 May; 15(1):104. PubMed ID: 32393280
    [TBL] [Abstract][Full Text] [Related]  

  • 23. CAN3D: Fast 3D medical image segmentation via compact context aggregation.
    Dai W; Woo B; Liu S; Marques M; Engstrom C; Greer PB; Crozier S; Dowling JA; Chandra SS
    Med Image Anal; 2022 Nov; 82():102562. PubMed ID: 36049450
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Lung tumor segmentation in 4D CT images using motion convolutional neural networks.
    Momin S; Lei Y; Tian Z; Wang T; Roper J; Kesarwala AH; Higgins K; Bradley JD; Liu T; Yang X
    Med Phys; 2021 Nov; 48(11):7141-7153. PubMed ID: 34469001
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.
    Guo Y; Gao Y; Shao Y; Price T; Oto A; Shen D
    Med Phys; 2014 Jul; 41(7):072303. PubMed ID: 24989402
    [TBL] [Abstract][Full Text] [Related]  

  • 26. 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]  

  • 27. Learning image context for segmentation of the prostate in CT-guided radiotherapy.
    Li W; Liao S; Feng Q; Chen W; Shen D
    Phys Med Biol; 2012 Mar; 57(5):1283-308. PubMed ID: 22343071
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net.
    Aldoj N; Biavati F; Michallek F; Stober S; Dewey M
    Sci Rep; 2020 Aug; 10(1):14315. PubMed ID: 32868836
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Multi-eXpert fusion: An ensemble learning framework to segment 3D TRUS prostate images.
    Beitone C; Troccaz J
    Med Phys; 2022 Aug; 49(8):5138-5148. PubMed ID: 35443086
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Fully automated segmentation of prostatic urethra for MR-guided radiation therapy.
    Xu D; Ma TM; Savjani R; Pham J; Cao M; Yang Y; Kishan AU; Scalzo F; Sheng K
    Med Phys; 2023 Jan; 50(1):354-364. PubMed ID: 36106703
    [TBL] [Abstract][Full Text] [Related]  

  • 31. 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]  

  • 32. Pelvic Organ Segmentation Using Distinctive Curve Guided Fully Convolutional Networks.
    He K; Cao X; Shi Y; Nie D; Gao Y; Shen D
    IEEE Trans Med Imaging; 2019 Feb; 38(2):585-595. PubMed ID: 30176583
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI.
    Khan Z; Yahya N; Alsaih K; Ali SSA; Meriaudeau F
    Sensors (Basel); 2020 Jun; 20(11):. PubMed ID: 32503330
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Automated segmentation of prostate zonal anatomy on T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U-Nets.
    Zabihollahy F; Schieda N; Krishna Jeyaraj S; Ukwatta E
    Med Phys; 2019 Jul; 46(7):3078-3090. PubMed ID: 31002381
    [TBL] [Abstract][Full Text] [Related]  

  • 35. 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; BĂ©nard 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]  

  • 36. Prostate lesion segmentation based on a 3D end-to-end convolution neural network with deep multi-scale attention.
    Song E; Long J; Ma G; Liu H; Hung CC; Jin R; Wang P; Wang W
    Magn Reson Imaging; 2023 Jun; 99():98-109. PubMed ID: 36681311
    [TBL] [Abstract][Full Text] [Related]  

  • 37. ParaCM-PNet: A CNN-tokenized MLP combined parallel dual pyramid network for prostate and prostate cancer segmentation in MRI.
    Wang W; Pan B; Ai Y; Li G; Fu Y; Liu Y
    Comput Biol Med; 2024 Mar; 170():107999. PubMed ID: 38244470
    [TBL] [Abstract][Full Text] [Related]  

  • 38. MR to ultrasound image registration with segmentation-based learning for HDR prostate brachytherapy.
    Chen Y; Xing L; Yu L; Liu W; Pooya Fahimian B; Niedermayr T; Bagshaw HP; Buyyounouski M; Han B
    Med Phys; 2021 Jun; 48(6):3074-3083. PubMed ID: 33905566
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Accuracy Validation of an Automated Method for Prostate Segmentation in Magnetic Resonance Imaging.
    Shahedi M; Cool DW; Bauman GS; Bastian-Jordan M; Fenster A; Ward AD
    J Digit Imaging; 2017 Dec; 30(6):782-795. PubMed ID: 28342043
    [TBL] [Abstract][Full Text] [Related]  

  • 40. HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation in CT Images.
    He K; Lian C; Zhang B; Zhang X; Cao X; Nie D; Gao Y; Zhang J; Shen D
    IEEE Trans Med Imaging; 2021 Aug; 40(8):2118-2128. PubMed ID: 33848243
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.