BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

169 related articles for article (PubMed ID: 35724474)

  • 1. An EfficientNet-based modified sigmoid transform for enhancing dermatological macro-images of melanoma and nevi skin lesions.
    Venugopal V; Joseph J; Vipin Das M; Kumar Nath M
    Comput Methods Programs Biomed; 2022 Jul; 222():106935. PubMed ID: 35724474
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DTP-Net: A convolutional neural network model to predict threshold for localizing the lesions on dermatological macro-images.
    Venugopal V; Joseph J; Das MV; Nath MK
    Comput Biol Med; 2022 Sep; 148():105852. PubMed ID: 35853397
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Skin Lesion Segmentation in Dermoscopic Images with Noisy Data.
    Lama N; Hagerty J; Nambisan A; Stanley RJ; Van Stoecker W
    J Digit Imaging; 2023 Aug; 36(4):1712-1722. PubMed ID: 37020149
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. 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]  

  • 6. Integration of morphological preprocessing and fractal based feature extraction with recursive feature elimination for skin lesion types classification.
    Chatterjee S; Dey D; Munshi S
    Comput Methods Programs Biomed; 2019 Sep; 178():201-218. PubMed ID: 31416550
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Deep Hybrid Convolutional Neural Network for Segmentation of Melanoma Skin Lesion.
    Yang CH; Ren JH; Huang HC; Chuang LY; Chang PY
    Comput Intell Neurosci; 2021; 2021():9409508. PubMed ID: 34790232
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Melanoma detection by analysis of clinical images using convolutional neural network.
    Nasr-Esfahani E; Samavi S; Karimi N; Soroushmehr SM; Jafari MH; Ward K; Najarian K
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():1373-1376. PubMed ID: 28268581
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Classification of skin lesions using transfer learning and augmentation with Alex-net.
    Hosny KM; Kassem MA; Foaud MM
    PLoS One; 2019; 14(5):e0217293. PubMed ID: 31112591
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Generation of a Melanoma and Nevus Data Set From Unstandardized Clinical Photographs on the Internet.
    Cho SI; Navarrete-Dechent C; Daneshjou R; Cho HS; Chang SE; Kim SH; Na JI; Han SS
    JAMA Dermatol; 2023 Nov; 159(11):1223-1231. PubMed ID: 37792351
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Convolutional neural network-based skin image segmentation model to improve classification of skin diseases in conventional and non-standardized picture images.
    Yanagisawa Y; Shido K; Kojima K; Yamasaki K
    J Dermatol Sci; 2023 Jan; 109(1):30-36. PubMed ID: 36658056
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Automated Detection of Nonmelanoma Skin Cancer Based on Deep Convolutional Neural Network.
    Arif M; Philip FM; Ajesh F; Izdrui D; Craciun MD; Geman O
    J Healthc Eng; 2022; 2022():6952304. PubMed ID: 35186235
    [TBL] [Abstract][Full Text] [Related]  

  • 17. ChimeraNet: U-Net for Hair Detection in Dermoscopic Skin Lesion Images.
    Lama N; Kasmi R; Hagerty JR; Stanley RJ; Young R; Miinch J; Nepal J; Nambisan A; Stoecker WV
    J Digit Imaging; 2023 Apr; 36(2):526-535. PubMed ID: 36385676
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A deep bag-of-features model for the classification of melanomas in dermoscopy images.
    Sabbaghi S; Aldeen M; Garnavi R
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():1369-1372. PubMed ID: 28268580
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM).
    R D S; A S
    Asian Pac J Cancer Prev; 2019 May; 20(5):1555-1561. PubMed ID: 31128062
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An Evolutionary Approach for the Enhancement of Dermatological Images and Their Classification Using Deep Learning Models.
    Chaahat ; Kumar Gondhi N; Kumar Lehana P
    J Healthc Eng; 2021; 2021():8113403. PubMed ID: 34326979
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.