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Automatic Skin Cancer Detection in Dermoscopy Images based on Ensemble Lightweight Deep Learning Network

Lisheng Wei, Kun Ding, Huosheng Hu
2020 IEEE Access  
, and migration training strategy, we build a lightweight semantic segmentation model of lesion area of dermoscopy image, which can achieve high precision lesion area segmentation end-to-end without complicated  ...  INDEX TERMS Dermoscopy images, skin cancer detection, lightweight deep learning network, fine-grained feature.  ...  ACKNOWLEDGMENT The authors would like to thank web of science for the help of literature search in the process of writing the article.  ... 
doi:10.1109/access.2020.2997710 fatcat:3xjmsc6eq5forbhler2q4jd4wy

Dermatologist Level Dermoscopy Skin Cancer Classification Using Different Deep Learning Convolutional Neural Networks Algorithms [article]

Amirreza Rezvantalab, Habib Safigholi, Somayeh Karimijeshni
2018 arXiv   pre-print
Different pre-trained state-of-the-art architectures (DenseNet 201, ResNet 152, Inception v3, InceptionResNet v2) were used and applied on 10135 dermoscopy skin images in total (HAM10000: 10015, PH2: 120  ...  In this paper, the effectiveness and capability of convolutional neural networks have been studied in the classification of 8 skin diseases.  ...  This study, presents a deep learning approach for fully automated analysis of dermatoscopic images of skin diseases.  ... 
arXiv:1810.10348v1 fatcat:gtkpede2ubey5gowselagvht2e

FCN-based DenseNet framework for automated detection and classification of skin lesions in dermoscopy images

Adekanmi A. Adegun, Serestina Viriri
2020 IEEE Access  
Finally, a deeply supervised multi-scale network [66] was utilized for the detection and segmentation of skin cancer from skin lesion images.  ...  The approach also utilized a fully convolutional network for the extraction of multi-scale features via the pooling-over of augmented feature space.  ...  Techniques Average Training Time/ epoch Test Time/Image Proposed model 800 8 ResNet152 950 12 InceptionV3 1050 15 VGG19 1600 23  ... 
doi:10.1109/access.2020.3016651 fatcat:ili33nftubhvfncpij4gulupra

Skin Lesions Classification and Segmentation: A Review

Marzuraikah Mohd Stofa, Mohd Asyraf Zulkifley, Muhammad Ammirrul Atiqi Mohd Zainuri
2021 International Journal of Advanced Computer Science and Applications  
An automated intelligent system based on imaging input for unbiased diagnosis of skin-related diseases is an essential screening tool nowadays.  ...  The review starts with the classification techniques used for skin lesion detection, followed by a concise review on lesions segmentation, also using the deep learning techniques.  ...  Image segmentation is needed in a large-scale approach to diagnosing skin lesions automatically.  ... 
doi:10.14569/ijacsa.2021.0121060 fatcat:xvliew62nvc6ldbq7z3f2nauta

Skin disease diagnosis with deep learning: a review [article]

Hongfeng Li, Yini Pan, Jie Zhao, Li Zhang
2020 arXiv   pre-print
We first present a brief introduction to skin diseases and image acquisition methods in dermatology, and list several publicly available skin datasets for training and testing algorithms.  ...  Particularly, they have been applied to the skin disease diagnosis tasks. In this paper, we present a review on deep learning methods and their applications in skin disease diagnosis.  ...  They first constructed a fully convolutional residual network (FCRN) which incorporated multi-scale feature representations for skin lesion segmentation.  ... 
arXiv:2011.05627v2 fatcat:dtdydy2orrd7tka4fpqml4znse

A multilevel features selection framework for skin lesion classification

Tallha Akram, Hafiz M. Junaid Lodhi, Syed Rameez Naqvi, Sidra Naeem, Majed Alhaisoni, Muhammad Ali, Sajjad Ali Haider, Nadia N. Qadri
2020 Human-Centric Computing and Information Sciences  
In the quest for the same, a few computer based methods, capable of diagnosing the skin lesion at initial stages, have been recently proposed.  ...  Initially, the dermoscopic images are segmented, and the lesion region is extracted, which is later subjected to retrain the selected deep models to generate fused feature vectors.  ...  Lesion/image segmentation Segmentation is one critical step that plays its primary role in classification of the skin lesion.  ... 
doi:10.1186/s13673-020-00216-y fatcat:dxom62b6gfaxbhoqqoy4x7hqhy

Artificial Intelligence in Cutaneous Oncology

Yu Seong Chu, Hong Gi An, Byung Ho Oh, Sejung Yang
2020 Frontiers in Medicine  
In addition, the universal use of dermoscopy, which allows for non-invasive inspection of the upper dermal level of skin lesions with a usual 10-fold magnification, adds to the image storage and analysis  ...  Skin cancer, previously known to be a common disease in Western countries, is becoming more common in Asian countries. Skin cancer differs from other carcinomas in that it is visible to our eyes.  ...  (42) Fully automated procedure to detect BCC in ex-vivo human skin from PS-OCT images AUC: 97.2% Sen: 95.4% Spe: 95.4% Extracting image features from the two complementary image contrasts  ... 
doi:10.3389/fmed.2020.00318 pmid:32754606 pmcid:PMC7366843 fatcat:557xllh2dzf5hbnrrmcdbg2kyi

Skin Lesion Analysis Using Ensemble of CNN with Dermoscopic Images and Metadata

Sergey Milantev, Vyacheslav Olyunin, Ilya Bykov, Natalya Milanteva, Igor Bessmertny
2020 Majorov International Conference on Software Engineering and Computer Systems  
In this paper, there was considered the use of deep learning for skin lesions with advanced data preprocessing. There was decided to classify skin lesions using convolutional neural networks.  ...  Each image was segmented using R2U-Net and and black areas were removed from it before being fed into the convolutional network for classification.  ...  for technical research toward automated skin lesion analysis.  ... 
dblp:conf/micsecs/MilantevOBMB20 fatcat:n2walkxhrbh35fbdpwbjscaobe

Semantic Segmentation of Lesions from Dermoscopic Images using Yolo-DeepLab Networks

2021 International Journal of Engineering  
In this study, a two-stage method is presented for the segmentation of skin lesions using Deep Learning.  ...  A B S T R A C T Accurate segmentation of lesions from dermoscopic images is very important for timely diagnosis and treatment of skin cancers.  ...  ., in 2017 prersented a twostage method to segment and classify skin lesions using fully convolutional residual network (FCRN).  ... 
doi:10.5829/ije.2021.34.02b.18 fatcat:hyickriorvhrdmfutjjoyv37im

CU-Net: A New Improved Multi-Input Color U-Net Model for Skin Lesion Semantic Segmentation

Rania Ramadan, Saleh Aly
2022 IEEE Access  
Most deep CNNs and particularly U-Net model utilize a single input RGB color image for skin lesion semantic segmentation.  ...  Automatic skin lesion segmentation is an essential step to build a successful skin disease classification system.  ...  [48] extended their previous works and proposed a fully automated approach for multi-class skin lesion segmentation and classification that used the most discriminant deep features.  ... 
doi:10.1109/access.2022.3148402 fatcat:fruybcht6falpkhn6qzqieuywu

Classification of Skin cancer using deep learning, Convolutional Neural Networks - Opportunities and vulnerabilities- A systematic Review

Ravi Manne, Snigdha Kantheti and Sneha Kantheti
2020 International journal of modern trends in science and technology  
Skin cancer classificationusing convolutional neural networks (CNNs) proved better results in classifying skin lesions compared with dermatologists which is lifesaving in terms of diagnosing.  ...  Objective: This study represents review of many research articles on classifying skin lesions using CNNs.  ...  Skin Lesion Classification Using Convolutional Neural Network as a Feature Extractor [9]The author has used U-net algorithm of CNN for segmentation process.  ... 
doi:10.46501/ijmtst061118 fatcat:dhd6xmdvsnfu5hjfw6fb2kvjwy

Visual saliency based global-local feature representation for skin cancer classification

Feng Xiao, Qiuxia Wu
2020 IET Image Processing  
With the rapid increase in the cases of deadly skin cancer, the classification on different types of skin cancer has been emerging as one of the most significant issues in the field of medical image.  ...  for skin cancer classification.  ...  [33] achieve feature extraction and classification for skin cancer images at different scales with ResNet.  ... 
doi:10.1049/iet-ipr.2019.1018 fatcat:mhhqn6nsuzhstkn5qp4rcxxcae

Risk-Aware Machine Learning Classifier for Skin Lesion Diagnosis

Aryan Mobiny, Aditi Singh, Hien Van Nguyen
2019 Journal of Clinical Medicine  
In this paper, we investigate how Bayesian deep learning can improve the performance of the machine–physician team in the skin lesion classification task.  ...  We used the publicly available HAM10000 dataset, which includes samples from seven common skin lesion categories: Melanoma (MEL), Melanocytic Nevi (NV), Basal Cell Carcinoma (BCC), Actinic Keratoses and  ...  [50] demonstrated that such uncertainty estimates can be exploited for predicting the segmentation quality of the skin lesions.  ... 
doi:10.3390/jcm8081241 pmid:31426482 pmcid:PMC6723257 fatcat:itharxpxpnfihfosmdkhsmf22u

Skin Cancer Classification With Deep Learning: A Systematic Review

Yinhao Wu, Bin Chen, An Zeng, Dan Pan, Ruixuan Wang, Shen Zhao
2022 Frontiers in Oncology  
After that, we review the successful applications of typical convolutional neural networks for skin cancer classification.  ...  However, achieving automatic skin cancer classification is difficult because the majority of skin disease images used for training are imbalanced and in short supply; meanwhile, the model's cross-domain  ...  Automatic Skin Lesion Segmentation by Coupling Deep Fully Convolutional Networks and Shallow Network With Textons.  ... 
doi:10.3389/fonc.2022.893972 pmid:35912265 pmcid:PMC9327733 doaj:6f795cde08d545fa9c700f54fb7f5ded fatcat:ssycu6bgn5errlie36male76uu

Computer Vision with Machine Learning Enabled Skin Lesion Classification Model

Romany F. Mansour, Sara A. Althubiti, Fayadh Alenezi
2022 Computers Materials & Continua  
Moreover, naïve bayes (NB) classifier is utilized for the skin lesion detection and classification model.  ...  At the same time, deep learning (DL) and machine learning (ML) models play a vital role in the healthcare sector for the effectual recognition of diseases using medical imaging tools.  ...  Skin lesion localization and detection in the image are essential to estimate image features for lesion diagnoses [4] .  ... 
doi:10.32604/cmc.2022.029265 fatcat:jtm5plgpbfccllcxhjqewzpaou
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