209 related articles for article (PubMed ID: 31437709)
1. Kernel sparse representation based model for skin lesions segmentation and classification.
Moradi N; Mahdavi-Amiri N
Comput Methods Programs Biomed; 2019 Dec; 182():105038. PubMed ID: 31437709
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
5. Rethinking Skin Lesion Segmentation in a Convolutional Classifier.
Burdick J; Marques O; Weinthal J; Furht B
J Digit Imaging; 2018 Aug; 31(4):435-440. PubMed ID: 29047032
[TBL] [Abstract][Full Text] [Related]
6. Saliency-Based Lesion Segmentation Via Background Detection in Dermoscopic Images.
Ahn E; Kim J; Bi L; Kumar A; Li C; Fulham M; Feng DD
IEEE J Biomed Health Inform; 2017 Nov; 21(6):1685-1693. PubMed ID: 28092585
[TBL] [Abstract][Full Text] [Related]
7. Brain tumor image segmentation using kernel dictionary learning.
Jeon Lee ; Seung-Jun Kim ; Rong Chen ; Herskovits EH
Annu Int Conf IEEE Eng Med Biol Soc; 2015 Aug; 2015():658-61. PubMed ID: 26736348
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. 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]
10. 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]
11. 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]
12. 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]
13. Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks.
Bi L; Kim J; Ahn E; Kumar A; Fulham M; Feng D
IEEE Trans Biomed Eng; 2017 Sep; 64(9):2065-2074. PubMed ID: 28600236
[TBL] [Abstract][Full Text] [Related]
14. Fusing fine-tuned deep features for skin lesion classification.
Mahbod A; Schaefer G; Ellinger I; Ecker R; Pitiot A; Wang C
Comput Med Imaging Graph; 2019 Jan; 71():19-29. PubMed ID: 30458354
[TBL] [Abstract][Full Text] [Related]
15. Feature selection and multi-kernel learning for sparse representation on a manifold.
Wang JJ; Bensmail H; Gao X
Neural Netw; 2014 Mar; 51():9-16. PubMed ID: 24333479
[TBL] [Abstract][Full Text] [Related]
16. Sparse representation with kernels.
Gao S; Tsang IW; Chia LT
IEEE Trans Image Process; 2013 Feb; 22(2):423-34. PubMed ID: 23014744
[TBL] [Abstract][Full Text] [Related]
17. An implementation of normal distribution based segmentation and entropy controlled features selection for skin lesion detection and classification.
Khan MA; Akram T; Sharif M; Shahzad A; Aurangzeb K; Alhussein M; Haider SI; Altamrah A
BMC Cancer; 2018 Jun; 18(1):638. PubMed ID: 29871593
[TBL] [Abstract][Full Text] [Related]
18. Role of In Vivo Reflectance Confocal Microscopy in the Analysis of Melanocytic Lesions.
Serban ED; Farnetani F; Pellacani G; Constantin MM
Acta Dermatovenerol Croat; 2018 Apr; 26(1):64-67. PubMed ID: 29782304
[TBL] [Abstract][Full Text] [Related]
19. A hierarchical three-step superpixels and deep learning framework for skin lesion classification.
Afza F; Sharif M; Mittal M; Khan MA; Jude Hemanth D
Methods; 2022 Jun; 202():88-102. PubMed ID: 33610692
[TBL] [Abstract][Full Text] [Related]
20. Segmentation of skin lesions from digital images using joint statistical texture distinctiveness.
Glaister J; Wong A; Clausi DA
IEEE Trans Biomed Eng; 2014 Apr; 61(4):1220-30. PubMed ID: 24658246
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]