BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

2022 related articles for article (PubMed ID: 32484086)

  • 1. Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.
    Baig R; Bibi M; Hamid A; Kausar S; Khalid S
    Curr Med Imaging; 2020; 16(5):513-533. PubMed ID: 32484086
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images.
    Kaur R; GholamHosseini H; Sinha R; Lindén M
    BMC Med Imaging; 2022 May; 22(1):103. PubMed ID: 35644612
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis.
    Song L; Lin J; Wang ZJ; Wang H
    IEEE J Biomed Health Inform; 2020 Oct; 24(10):2912-2921. PubMed ID: 32071016
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Digital hair segmentation using hybrid convolutional and recurrent neural networks architecture.
    Attia M; Hossny M; Zhou H; Nahavandi S; Asadi H; Yazdabadi A
    Comput Methods Programs Biomed; 2019 Aug; 177():17-30. PubMed ID: 31319945
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks.
    Al-Masni MA; Al-Antari MA; Choi MT; Han SM; Kim TS
    Comput Methods Programs Biomed; 2018 Aug; 162():221-231. PubMed ID: 29903489
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A comparative study of deep learning architectures on melanoma detection.
    Hosseinzadeh Kassani S; Hosseinzadeh Kassani P
    Tissue Cell; 2019 Jun; 58():76-83. PubMed ID: 31133249
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Efficient skin lesion segmentation using separable-Unet with stochastic weight averaging.
    Tang P; Liang Q; Yan X; Xiang S; Sun W; Zhang D; Coppola G
    Comput Methods Programs Biomed; 2019 Sep; 178():289-301. PubMed ID: 31416556
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Segmentation of dermoscopy images based on deformable 3D convolution and ResU-NeXt +.
    Zhao C; Shuai R; Ma L; Liu W; Wu M
    Med Biol Eng Comput; 2021 Sep; 59(9):1815-1832. PubMed ID: 34304370
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks.
    Yuan Y; Lo YC
    IEEE J Biomed Health Inform; 2019 Mar; 23(2):519-526. PubMed ID: 29990146
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Melanoma lesion detection and segmentation using deep region based convolutional neural network and fuzzy C-means clustering.
    Nida N; Irtaza A; Javed A; Yousaf MH; Mahmood MT
    Int J Med Inform; 2019 Apr; 124():37-48. PubMed ID: 30784425
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Segmentation of skin lesions in dermoscopy images using fuzzy classification of pixels and histogram thresholding.
    Garcia-Arroyo JL; Garcia-Zapirain B
    Comput Methods Programs Biomed; 2019 Jan; 168():11-19. PubMed ID: 30527129
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Melanoma diagnosis using deep learning techniques on dermatoscopic images.
    Jojoa Acosta MF; Caballero Tovar LY; Garcia-Zapirain MB; Percybrooks WS
    BMC Med Imaging; 2021 Jan; 21(1):6. PubMed ID: 33407213
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.
    Marchetti MA; Liopyris K; Dusza SW; Codella NCF; Gutman DA; Helba B; Kalloo A; Halpern AC;
    J Am Acad Dermatol; 2020 Mar; 82(3):622-627. PubMed ID: 31306724
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Developing a Recognition System for Diagnosing Melanoma Skin Lesions Using Artificial Intelligence Algorithms.
    Alsaade FW; Aldhyani THH; Al-Adhaileh MH
    Comput Math Methods Med; 2021; 2021():9998379. PubMed ID: 34055044
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Skin lesion image segmentation using Delaunay Triangulation for melanoma detection.
    Pennisi A; Bloisi DD; Nardi D; Giampetruzzi AR; Mondino C; Facchiano A
    Comput Med Imaging Graph; 2016 Sep; 52():89-103. PubMed ID: 27215953
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Skin lesion classification with ensembles of deep convolutional neural networks.
    Harangi B
    J Biomed Inform; 2018 Oct; 86():25-32. PubMed ID: 30103029
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification.
    Al-Masni MA; Kim DH; Kim TS
    Comput Methods Programs Biomed; 2020 Jul; 190():105351. PubMed ID: 32028084
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.
    Ashraf H; Waris A; Ghafoor MF; Gilani SO; Niazi IK
    Sci Rep; 2022 Mar; 12(1):3948. PubMed ID: 35273282
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.
    Maqsood S; Damaševičius R
    Neural Netw; 2023 Mar; 160():238-258. PubMed ID: 36701878
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 102.