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Skin Lesion Detection using Texture Based Segmentation and Classification by Convolutional Neural Networks (CNN)

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Skin lesion segmentation from dermoscopic images is a very challenging task nowadays because of the contrast of those images. there are various techniques for detecting the skin cancer base on the characteristics  ...  Nowadays Deep Learning technique is very popular for classification of images. CNN is one of the techniques of Deep Learning. The proposed work will help in classification of skin lesion.  ...  Skin Lesion In the segmentation step, they applied Grab-cut algorithm and K-means algorithm is used for clustering and learned features from colour dermoscopic images dataset to improve the boundary of  ... 
doi:10.35940/ijitee.b7085.129219 fatcat:7idyakj7ireipb4orxua5xti6a

A Novel Multi-task Deep Learning Model for Skin Lesion Segmentation and Classification [article]

Xulei Yang, Zeng Zeng, Si Yong Yeo, Colin Tan, Hong Liang Tey, Yi Su
2017 arXiv   pre-print
The proposed multi-task deep learning model is trained and evaluated on the dermoscopic image sets from the International Skin Imaging Collaboration (ISIC) 2017 Challenge - Skin Lesion Analysis towards  ...  The experimental results show that the proposed multi-task deep learning model achieves promising performances on skin lesion segmentation and classification.  ...  The segmentation of the lesion from dermoscopic images is an important aspect of melanoma detection, as some of the features which are used by clinicians in dermoscopy algorithms are based on the shape  ... 
arXiv:1703.01025v1 fatcat:sth5akf2hzfp5eopainabkvxsu

Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation

Dang N.H. Thanh, Nguyen Hoang Hai, Le Minh Hieu, Prayag Tiwari, V.B. Surya Prasath
2021 Computer Optics  
In this article, we propose a skin lesion segmentation method for dermoscopic images based on the U-Net architecture with VGG-16 encoder and the semantic segmentation.  ...  Base on the segmented skin lesion, diagnostic imaging systems can evaluate skin lesion features to classify them.  ...  To improve the diagnostic quality by ABCD rule, it is necessary to segment skin lesions from dermoscopic images.  ... 
doi:10.18287/2412-6179-co-748 fatcat:sljt6cepafgkbdf6asdpvssttq

Pattern Recognition in Macroscopic and Dermoscopic Images for Skin Lesion Diagnosis [chapter]

Roberta B. Oliveira, Aledir S. Pereira, João Manuel R. S. Tavares
2017 Lecture Notes in Computational Vision and Biomechanics  
Pattern recognition in macroscopic and dermoscopic images is a challenging task in skin lesion diagnosis.  ...  Hence, this work was particularly focused on skin lesion pattern recognition, especially in macroscopic and dermoscopic images.  ...  Ricardo Baccaro Rossetti, from Derm Clínica's Dermatologist of São José do Rio Preto, in Brazil, for his suggestions and for evaluating the results obtained.  ... 
doi:10.1007/978-3-319-68195-5_55 fatcat:tuhbeyqsrja35n25w5ivgabfte

SKIN LESION SEGMENTATION BY PIXEL BY PIXEL APPROACH USING DEEP LEARNING

Shekaina Justin, Manjula Pattnaik
2020 International journal of advances in signal and image sciences  
Skin lesion segmentation is an imperative step for image analysis and visualization task.  ...  The PbP approach has four stages; study the training images consists of skin lesions, construction of deep learning network followed by training it and finally evaluate the network with testing images.  ...  Optimal colour channel based skin lesion segmentation is discussed in [15] . Initially, the given dermoscopic images are resized uniformly and then de-noised.  ... 
doi:10.29284/ijasis.6.1.2020.12-20 fatcat:vnmrkrwpj5hl3dslra6cz6akxm

Multilevel feature extraction for skin lesion segmentation in dermoscopic images

Sina KhakAbi, Paul Wighton, Tim K. Lee, M. Stella Atkins, Bram van Ginneken, Carol L. Novak
2012 Medical Imaging 2012: Computer-Aided Diagnosis  
This paper presents a novel approach in computer aided skin lesion segmentation of dermoscopic images. We apply spatial and color features in order to model the lesion growth pattern.  ...  A dataset containing 116 challenging images from dermoscopic atlases is used to validate the method via a 10-fold cross validation procedure.  ...  walker algorithm 25 is also employed to segment the skin lesion in dermoscopic images.  ... 
doi:10.1117/12.911664 dblp:conf/micad/KhakAbiWLA12 fatcat:g2jym44dcvaclisi5okwrzgxl4

Preprocessing Effects on Performance of Skin Lesion Saliency Segmentation

Seena Joseph, Oludayo O. Olugbara
2022 Diagnostics  
Segmentation of skin lesions in dermoscopic images is an important requisite component of such a breakthrough innovation for an accurate melanoma diagnosis.  ...  Novel image segmentation methods are aimed to address these undesirable heterogeneous properties of skin lesions with the help of image preprocessing methods.  ...  clusters and efficacious segmentation of skin lesions in dermoscopic images  ... 
doi:10.3390/diagnostics12020344 pmid:35204435 pmcid:PMC8871329 fatcat:5l34hkerc5c6bdt3ucjn3v2s64

Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images [article]

Kumar Abhishek, Ghassan Hamarneh, Mark S. Drew
2020 arXiv   pre-print
The semantic segmentation of skin lesions is an important and common initial task in the computer aided diagnosis of dermoscopic images.  ...  Although deep learning-based approaches have considerably improved the segmentation accuracy, there is still room for improvement by addressing the major challenges, such as variations in lesion shape,  ...  Recent years have witnessed the successful applications of machine learning, particularly deep learning-based approaches, to the semantic segmentation of skin lesions.  ... 
arXiv:2003.10111v1 fatcat:ruelnx63gbclvdp3ping7pgcfa

Guest Editorial Skin Lesion Image Analysis for Melanoma Detection

M. Emre Celebi, Noel Codella, Allan Halpern, Dinggang Shen
2019 IEEE journal of biomedical and health informatics  
ACKNOWLEDGMENT The guest editors thank all those who helped make this special issue possible, especially the Editor-in-Chief, editorial staff, and the authors and reviewers of the contributions. M.  ...  In Accurate Segmentation and Registration of Skin Lesion Images to Evaluate Lesion Change, Navarro et al. describe a superpixel based segmentation algorithm.  ...  In Active Contours Based Segmentation and Lesion Periphery Analysis for Characterization of Skin Lesions in Dermoscopy Images, Riaz et al. propose an active contour based segmentation approach.  ... 
doi:10.1109/jbhi.2019.2897338 fatcat:3cszhtjw6zc5thl4abzeaukq3q

Bi-directional Dermoscopic Feature Learning and Multi-scale Consistent Decision Fusion for Skin Lesion Segmentation

Xiaohong Wang, Xudong Jiang, Henghui Ding, Jun Liu
2019 IEEE Transactions on Image Processing  
Accurate segmentation of skin lesion from dermoscopic images is a crucial part of computer-aided diagnosis of melanoma.  ...  It is challenging due to the fact that dermoscopic images from different patients have non-negligible lesion variation, which causes difficulties in anatomical structure learning and consistent skin lesion  ...  ACKNOWLEDGMENT The authors would like to thank the organizers of International Symposium on Biomedical Imaing 2016 and 2017 for kindly providing benchmark databases and annotations.  ... 
doi:10.1109/tip.2019.2955297 fatcat:tclk22buhzdufnymgbt7tm5zpq

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network

Yuexiang Li, Linlin Shen
2018 Sensors  
Zhou developed several mean-shift-based approaches for segmenting skin lesions in dermoscopic images [14] [15] [16] .  ...  In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction  ...  of skin lesion image processing, i.e., lesion segmentation, dermoscopic feature extraction and lesion classification.  ... 
doi:10.3390/s18020556 pmid:29439500 pmcid:PMC5855504 fatcat:juvmkzufnjcybopxo6v4plppfy

Data Augmentation Using Adversarial Image-to-Image Translation for the Segmentation of Mobile-Acquired Dermatological Images

Catarina Andrade, Luís F. Teixeira, Maria João M. Vasconcelos, Luís Rosado
2020 Journal of Imaging  
In this work, we present a technique to efficiently utilize the sizable number of dermoscopic images to improve the segmentation capacity of macroscopic skin lesion images.  ...  Dermoscopic images allow the detailed examination of subsurface characteristics of the skin, which led to creating several substantial databases of diverse skin lesions.  ...  Illustrative examples of macroscopic (row above) and dermoscopic (below) skin lesions.  ... 
doi:10.3390/jimaging7010002 pmid:34460573 pmcid:PMC8321267 fatcat:zaj6phc4cjhrpfvuiox6o6qyti

A Novel Hybrid Deep Learning Approach for Skin Lesion Segmentation and Classification

Puneet Thapar, Manik Rakhra, Gerardo Cazzato, Md Shamim Hossain, Deepak Garg
2022 Journal of Healthcare Engineering  
The swarm intelligence (SI) algorithms were used for skin lesion region of interest (RoI) segmentation from dermoscopy images, and the speeded-up robust features (SURF) was used for feature extraction  ...  As at an initial stage, visual observation gives the opportunity of utilizing artificial intelligence to intercept the different skin images, so several skin lesion classification methods using deep learning  ...  the exact skin lesion region from the preprocessed dermoscopic images known as the region of lesion (ROL).  ... 
doi:10.1155/2022/1709842 pmid:35480147 pmcid:PMC9038388 fatcat:jy5k3tworncwhnna6xbethhp5u

PH2 - A dermoscopic image database for research and benchmarking

Teresa Mendonca, Pedro M. Ferreira, Jorge S. Marques, Andre R. S. Marcal, Jorge Rozeira
2013 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
The PH 2 database includes the manual segmentation, the clinical diagnosis, and the identification of several dermoscopic structures, performed by expert dermatologists, in a set of 200 dermoscopic images  ...  The increasing incidence of melanoma has recently promoted the development of computer-aided diagnosis systems for the classification of dermoscopic images.  ...  Marta Pereira, both Dermatologists of the Hospital Pedro Hispano, for evaluating the dermoscopic images. We also thank to Catarina Barata and Bárbara Amorim from ADDI project.  ... 
doi:10.1109/embc.2013.6610779 pmid:24110966 dblp:conf/embc/MendoncaFMMR13 fatcat:aejlfc4gircffm6zt3gkuoccoy

(De)Constructing Bias on Skin Lesion Datasets [article]

Alceu Bissoto and Michel Fornaciali and Eduardo Valle and Sandra Avila
2019 arXiv   pre-print
Nowadays, the ISIC Archive and the Atlas of Dermoscopy dataset are the most employed skin lesion sources to benchmark deep-learning based tools.  ...  Our results show that models can correctly classify skin lesion images without clinically-meaningful information: disturbingly, the machine-learning model learned over images where no information about  ...  When exploring reproducible works on lesion segmentation [8, 24] , dermoscopic attribute segmentation [14] , skin lesion classification [7, 19, 23] , or skin lesion synthesis [6] those two datasets  ... 
arXiv:1904.08818v1 fatcat:smsadebuf5bfvfve5tjdqu2n2e
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