Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in developing computer-aided diagnosis …
researchers have shown an increasing interest in developing computer-aided diagnosis …
[HTML][HTML] A survey, review, and future trends of skin lesion segmentation and classification
Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …
analysis is an emerging field of research that has the potential to alleviate the burden and …
Skin lesion classification of dermoscopic images using machine learning and convolutional neural network
B Shetty, R Fernandes, AP Rodrigues… - Scientific Reports, 2022 - nature.com
Detecting dangerous illnesses connected to the skin organ, particularly malignancy,
requires the identification of pigmented skin lesions. Image detection techniques and …
requires the identification of pigmented skin lesions. Image detection techniques and …
Skin-Net: a novel deep residual network for skin lesions classification using multilevel feature extraction and cross-channel correlation with detection of outlier
Human Skin cancer is commonly detected visually through clinical screening followed by a
dermoscopic examination. However, automated skin lesion classification remains …
dermoscopic examination. However, automated skin lesion classification remains …
Pixels to classes: intelligent learning framework for multiclass skin lesion localization and classification
A novel deep learning framework is proposed for lesion segmentation and classification.
The proposed technique incorporates two primary phases. For lesion segmentation, Mask …
The proposed technique incorporates two primary phases. For lesion segmentation, Mask …
Machine learning and deep learning algorithms for skin cancer classification from dermoscopic images
S Bechelli, J Delhommelle - Bioengineering, 2022 - mdpi.com
We carry out a critical assessment of machine learning and deep learning models for the
classification of skin tumors. Machine learning (ML) algorithms tested in this work include …
classification of skin tumors. Machine learning (ML) algorithms tested in this work include …
[HTML][HTML] DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Abstract Background and Objective: Although automated Skin Lesion Classification (SLC) is
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
MSRNet: multiclass skin lesion recognition using additional residual block based fine-tuned deep models information fusion and best feature selection
Cancer is one of the leading significant causes of illness and chronic disease worldwide.
Skin cancer, particularly melanoma, is becoming a severe health problem due to its rising …
Skin cancer, particularly melanoma, is becoming a severe health problem due to its rising …
Towards effective classification of brain hemorrhagic and ischemic stroke using CNN
Brain stroke is one of the most leading causes of worldwide death and requires proper
medical treatment. Therefore, in this paper, our aim is to classify brain computed tomography …
medical treatment. Therefore, in this paper, our aim is to classify brain computed tomography …
Refined residual deep convolutional network for skin lesion classification
Skin cancer is the most common type of cancer that affects humans and is usually
diagnosed by initial clinical screening, which is followed by dermoscopic analysis …
diagnosed by initial clinical screening, which is followed by dermoscopic analysis …