BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

306 related articles for article (PubMed ID: 36516579)

  • 1. ASE-Net: A tumor segmentation method based on image pseudo enhancement and adaptive-scale attention supervision module.
    Zhang J; Jiang H; Shi T
    Comput Biol Med; 2023 Jan; 152():106363. PubMed ID: 36516579
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automated lung tumor delineation on positron emission tomography/computed tomography via a hybrid regional network.
    Lei Y; Wang T; Jeong JJ; Janopaul-Naylor J; Kesarwala AH; Roper J; Tian S; Bradley JD; Liu T; Higgins K; Yang X
    Med Phys; 2023 Jan; 50(1):274-283. PubMed ID: 36203393
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MSRA-Net: Tumor segmentation network based on Multi-scale Residual Attention.
    Wu Y; Jiang H; Pang W
    Comput Biol Med; 2023 May; 158():106818. PubMed ID: 36966557
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A transformer-guided cross-modality adaptive feature fusion framework for esophageal gross tumor volume segmentation.
    Yue Y; Li N; Zhang G; Xing W; Zhu Z; Liu X; Song S; Ta D
    Comput Methods Programs Biomed; 2024 Jun; 251():108216. PubMed ID: 38761412
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation.
    Fu X; Bi L; Kumar A; Fulham M; Kim J
    IEEE J Biomed Health Inform; 2021 Sep; 25(9):3507-3516. PubMed ID: 33591922
    [TBL] [Abstract][Full Text] [Related]  

  • 6. DGCBG-Net: A dual-branch network with global cross-modal interaction and boundary guidance for tumor segmentation in PET/CT images.
    Zou Z; Zou B; Kui X; Chen Z; Li Y
    Comput Methods Programs Biomed; 2024 Jun; 250():108125. PubMed ID: 38631130
    [TBL] [Abstract][Full Text] [Related]  

  • 7. DENSE-INception U-net for medical image segmentation.
    Zhang Z; Wu C; Coleman S; Kerr D
    Comput Methods Programs Biomed; 2020 Aug; 192():105395. PubMed ID: 32163817
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MFCNet: A multi-modal fusion and calibration networks for 3D pancreas tumor segmentation on PET-CT images.
    Wang F; Cheng C; Cao W; Wu Z; Wang H; Wei W; Yan Z; Liu Z
    Comput Biol Med; 2023 Mar; 155():106657. PubMed ID: 36791551
    [TBL] [Abstract][Full Text] [Related]  

  • 9. MRLA-Net: A tumor segmentation network embedded with a multiple receptive-field lesion attention module in PET-CT images.
    Zhou Y; Jiang H; Diao Z; Tong G; Luan Q; Li Y; Li X
    Comput Biol Med; 2023 Feb; 153():106538. PubMed ID: 36646023
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Diffuse large B-cell lymphoma segmentation in PET-CT images via hybrid learning for feature fusion.
    Yuan C; Zhang M; Huang X; Xie W; Lin X; Zhao W; Li B; Qian D
    Med Phys; 2021 Jul; 48(7):3665-3678. PubMed ID: 33735451
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multi-scale feature similarity-based weakly supervised lymphoma segmentation in PET/CT images.
    Huang Z; Guo Y; Zhang N; Huang X; Decazes P; Becker S; Ruan S
    Comput Biol Med; 2022 Dec; 151(Pt A):106230. PubMed ID: 36306574
    [TBL] [Abstract][Full Text] [Related]  

  • 12. DMCT-Net: dual modules convolution transformer network for head and neck tumor segmentation in PET/CT.
    Wang J; Peng Y; Guo Y
    Phys Med Biol; 2023 May; 68(11):. PubMed ID: 37141902
    [No Abstract]   [Full Text] [Related]  

  • 13. A comparison of methods for fully automatic segmentation of tumors and involved nodes in PET/CT of head and neck cancers.
    Groendahl AR; Skjei Knudtsen I; Huynh BN; Mulstad M; Moe YM; Knuth F; Tomic O; Indahl UG; Torheim T; Dale E; Malinen E; Futsaether CM
    Phys Med Biol; 2021 Mar; 66(6):065012. PubMed ID: 33666176
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Recurrent feature fusion learning for multi-modality pet-ct tumor segmentation.
    Bi L; Fulham M; Li N; Liu Q; Song S; Dagan Feng D; Kim J
    Comput Methods Programs Biomed; 2021 May; 203():106043. PubMed ID: 33744750
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PST-Radiomics: a PET/CT lymphoma classification method based on pseudo spatial-temporal radiomic features and structured atrous recurrent convolutional neural network.
    Wang M; Jiang H
    Phys Med Biol; 2023 Dec; 68(23):. PubMed ID: 37956448
    [No Abstract]   [Full Text] [Related]  

  • 16. CLCU-Net: Cross-level connected U-shaped network with selective feature aggregation attention module for brain tumor segmentation.
    Wang YL; Zhao ZJ; Hu SY; Chang FL
    Comput Methods Programs Biomed; 2021 Aug; 207():106154. PubMed ID: 34034031
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Head and neck tumor segmentation convolutional neural network robust to missing PET/CT modalities using channel dropout.
    Zhao LM; Zhang H; Kim DD; Ghimire K; Hu R; Kargilis DC; Tang L; Meng S; Chen Q; Liao WH; Bai H; Jiao Z; Feng X
    Phys Med Biol; 2023 Apr; 68(9):. PubMed ID: 37019119
    [No Abstract]   [Full Text] [Related]  

  • 18. [Breast cancer lesion segmentation based on co-learning feature fusion and Transformer].
    Zhai Y; Chen Z; Shao D
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2024 Apr; 41(2):237-245. PubMed ID: 38686403
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Tumor co-segmentation in PET/CT using multi-modality fully convolutional neural network.
    Zhao X; Li L; Lu W; Tan S
    Phys Med Biol; 2018 Dec; 64(1):015011. PubMed ID: 30523964
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation.
    Xuan P; Jiang B; Cui H; Jin Q; Cheng P; Nakaguchi T; Zhang T; Li C; Ning Z; Guo M; Wang L
    Comput Methods Programs Biomed; 2022 Nov; 226():107147. PubMed ID: 36206688
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.