Skin lesion segmentation using object scale-oriented fully convolutional neural networks
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Skin lesion segmentation using object scale-oriented fully convolutional neural networks
Authors
Keywords
Skin lesion, Melanoma, Fully convolutional neural networks, Object scale-oriented, Image segmentation
Journal
Signal Image and Video Processing
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2019-01-28
DOI
10.1007/s11760-018-01410-3
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Cancer statistics, 2018
- (2018) Rebecca L. Siegel et al. CA-A CANCER JOURNAL FOR CLINICIANS
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- (2018) Liang-Chieh Chen et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A novel optimized neutrosophic k-means using genetic algorithm for skin lesion detection in dermoscopy images
- (2018) Amira S. Ashour et al. Signal Image and Video Processing
- A Survey of Feature Extraction in Dermoscopy Image Analysis of Skin Cancer
- (2018) Ana Catarina Fidalgo Barata et al. IEEE Journal of Biomedical and Health Informatics
- Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks
- (2017) Lei Bi et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks
- (2017) Lequan Yu et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks With Jaccard Distance
- (2017) Yading Yuan et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- A Novel Approach to Segment Skin Lesions in Dermoscopic Images Based on a Deformable Model
- (2016) Zhen Ma et al. IEEE Journal of Biomedical and Health Informatics
- ImageNet Large Scale Visual Recognition Challenge
- (2015) Olga Russakovsky et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Simpler, Faster, More Accurate Melanocytic Lesion Segmentation Through MEDS
- (2013) Francesco Peruch et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- Computer-aided diagnosis system for tissue characterization of brain tumor on magnetic resonance images
- (2013) Megha. P. Arakeri et al. Signal Image and Video Processing
- Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods
- (2012) M. Emre Celebi et al. SKIN RESEARCH AND TECHNOLOGY
- Color image segmentation using adaptive color quantization and multiresolution texture characterization
- (2012) Ning-Yu An et al. Signal Image and Video Processing
- Border detection in dermoscopy images using hybrid thresholding on optimized color channels
- (2010) Rahil Garnavi et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Lesion border detection in dermoscopy images
- (2009) M.Emre Celebi et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Anisotropic Mean Shift Based Fuzzy C-Means Segmentation of Dermoscopy Images
- (2009) Huiyu Zhou et al. IEEE Journal of Selected Topics in Signal Processing
- An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm
- (2008) Hitoshi Iyatomi et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- Border detection in dermoscopy images using statistical region merging
- (2008) M. Emre Celebi et al. SKIN RESEARCH AND TECHNOLOGY
- Independent Histogram Pursuit for Segmentation of Skin Lesions
- (2007) David Delgado Gomez et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search