BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

375 related articles for article (PubMed ID: 35273282)

  • 61. Early gastric cancer segmentation in gastroscopic images using a co-spatial attention and channel attention based triple-branch ResUnet.
    Du W; Rao N; Yong J; Adjei PE; Hu X; Wang X; Gan T; Zhu L; Zeng B; Liu M; Xu Y
    Comput Methods Programs Biomed; 2023 Apr; 231():107397. PubMed ID: 36753915
    [TBL] [Abstract][Full Text] [Related]  

  • 62. Computer-Aided Diagnosis Algorithm for Classification of Malignant Melanoma Using Deep Neural Networks.
    Kim CI; Hwang SM; Park EB; Won CH; Lee JH
    Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34450993
    [TBL] [Abstract][Full Text] [Related]  

  • 63. Melanoma recognition in dermoscopy images using lesion's peripheral region information.
    Tajeddin NZ; Asl BM
    Comput Methods Programs Biomed; 2018 Sep; 163():143-153. PubMed ID: 30119849
    [TBL] [Abstract][Full Text] [Related]  

  • 64. Skin Lesion Analysis By Multi-Target Deep Neural Networks.
    Yang X; Li H; Wang L; Yeo SY; Su Y; Zeng Z
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():1263-1266. PubMed ID: 30440620
    [TBL] [Abstract][Full Text] [Related]  

  • 65. Transfer learning using a multi-scale and multi-network ensemble for skin lesion classification.
    Mahbod A; Schaefer G; Wang C; Dorffner G; Ecker R; Ellinger I
    Comput Methods Programs Biomed; 2020 Sep; 193():105475. PubMed ID: 32268255
    [TBL] [Abstract][Full Text] [Related]  

  • 66. Lesion Border Detection of Skin Cancer Images Using Deep Fully Convolutional Neural Network with Customized Weights.
    Kaur R; Hosseini HG; Sinha R
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3035-3038. PubMed ID: 34891883
    [TBL] [Abstract][Full Text] [Related]  

  • 67. Encoding Deep Residual Features into Fisher Vector for Skin Lesion Classification.
    Hu H; Chen Z; Xia Y
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():1843-1846. PubMed ID: 36086502
    [TBL] [Abstract][Full Text] [Related]  

  • 68. Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.
    He X; Yu Z; Wang T; Lei B; Shi Y
    Technol Health Care; 2018; 26(S1):307-316. PubMed ID: 29758959
    [TBL] [Abstract][Full Text] [Related]  

  • 69. Ensemble Method of Convolutional Neural Networks with Directed Acyclic Graph Using Dermoscopic Images: Melanoma Detection Application.
    Foahom Gouabou AC; Damoiseaux JL; Monnier J; Iguernaissi R; Moudafi A; Merad D
    Sensors (Basel); 2021 Jun; 21(12):. PubMed ID: 34200521
    [TBL] [Abstract][Full Text] [Related]  

  • 70. Skin lesion classification using HG-PSO and YOLOv7 based convolutional network in real time.
    Shaheen H; Singh MP
    Proc Inst Mech Eng H; 2023 Oct; 237(10):1228-1239. PubMed ID: 37840254
    [TBL] [Abstract][Full Text] [Related]  

  • 71. MSeg-Net: A Melanoma Mole Segmentation Network Using CornerNet and Fuzzy
    Nawaz M; Nazir T; Khan MA; Alhaisoni M; Kim JY; Nam Y
    Comput Math Methods Med; 2022; 2022():7502504. PubMed ID: 36276999
    [TBL] [Abstract][Full Text] [Related]  

  • 72. Fast fully automatic skin lesions segmentation probabilistic with Parzen window.
    Chagas JVSD; Ivo RF; Guimarães MT; de A Rodrigues D; de S Rebouças E; Rebouças Filho PP
    Comput Med Imaging Graph; 2020 Oct; 85():101774. PubMed ID: 32835893
    [TBL] [Abstract][Full Text] [Related]  

  • 73. LSCS-Net: A lightweight skin cancer segmentation network with densely connected multi-rate atrous convolution.
    Din S; Mourad O; Serpedin E
    Comput Biol Med; 2024 May; 173():108303. PubMed ID: 38547653
    [TBL] [Abstract][Full Text] [Related]  

  • 74. Supervised Saliency Map Driven Segmentation of Lesions in Dermoscopic Images.
    Jahanifar M; Zamani Tajeddin N; Mohammadzadeh Asl B; Gooya A
    IEEE J Biomed Health Inform; 2019 Mar; 23(2):509-518. PubMed ID: 29994323
    [TBL] [Abstract][Full Text] [Related]  

  • 75. SEACU-Net: Attentive ConvLSTM U-Net with squeeze-and-excitation layer for skin lesion segmentation.
    Jiang X; Jiang J; Wang B; Yu J; Wang J
    Comput Methods Programs Biomed; 2022 Oct; 225():107076. PubMed ID: 36027859
    [TBL] [Abstract][Full Text] [Related]  

  • 76. Modified U-NET Architecture for Segmentation of Skin Lesion.
    Anand V; Gupta S; Koundal D; Nayak SR; Barsocchi P; Bhoi AK
    Sensors (Basel); 2022 Jan; 22(3):. PubMed ID: 35161613
    [TBL] [Abstract][Full Text] [Related]  

  • 77. A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity.
    Montaha S; Azam S; Rafid AKMRH; Islam S; Ghosh P; Jonkman M
    PLoS One; 2022; 17(8):e0269826. PubMed ID: 35925956
    [TBL] [Abstract][Full Text] [Related]  

  • 78. EIU-Net: Enhanced feature extraction and improved skip connections in U-Net for skin lesion segmentation.
    Yu Z; Yu L; Zheng W; Wang S
    Comput Biol Med; 2023 Aug; 162():107081. PubMed ID: 37301097
    [TBL] [Abstract][Full Text] [Related]  

  • 79. Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion.
    Khan MA; Akram T; Sharif M; Saba T; Javed K; Lali IU; Tanik UJ; Rehman A
    Microsc Res Tech; 2019 Jun; 82(6):741-763. PubMed ID: 30768826
    [TBL] [Abstract][Full Text] [Related]  

  • 80. Applying an adaptive Otsu-based initialization algorithm to optimize active contour models for skin lesion segmentation.
    Malik YS; Tamoor M; Naseer A; Wali A; Khan A
    J Xray Sci Technol; 2022; 30(6):1169-1184. PubMed ID: 36093674
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 19.