AIMC Topic: Dermoscopy

Clear Filters Showing 81 to 90 of 198 articles

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

Journal of healthcare engineering
Skin cancer is one of the most common diseases that can be initially detected by visual observation and further with the help of dermoscopic analysis and other tests. As at an initial stage, visual observation gives the opportunity of utilizing artif...

A novel approach for skin lesion symmetry classification with a deep learning model.

Computers in biology and medicine
Skin cancer has become a public health problem due to its increasing incidence. However, the malignancy risk of the lesions can be reduced if diagnosed at an early stage. To do so, it is essential to identify particular characteristics such as the sy...

Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population.

International journal of environmental research and public health
(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, specificity, and accuracy of the quantusSKIN system, a new clinical tool based on deep learning, to distinguish between benign skin lesions and melanoma i...

Deep Learning-Based Classification for Melanoma Detection Using XceptionNet.

Journal of healthcare engineering
Skin cancer is one of the most common types of cancer in the world, accounting for at least 40% of all cancers. Melanoma is considered as the 19th most commonly occurring cancer among the other cancers in the human society, such that about 300,000 ne...

Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.

Scientific reports
In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and size of the skin lesion makes the segmentation task more challenging. Lesion segmentation is an initial step in CAD schemes as it leads to low error rat...

Deep learning-based diagnosis models for onychomycosis in dermoscopy.

Mycoses
BACKGROUND: Onychomycosis is a common disease. Emerging noninvasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of onychomycosis. However, deep learning application in dermoscop...

Multi-features extraction based on deep learning for skin lesion classification.

Tissue & cell
For various forms of skin lesion, many different feature extraction methods have been investigated so far. Indeed, feature extraction is a crucial step in machine learning processes. In general, we can distinct handcrafted and deep learning features....

Characteristics of publicly available skin cancer image datasets: a systematic review.

The Lancet. Digital health
Publicly available skin image datasets are increasingly used to develop machine learning algorithms for skin cancer diagnosis. However, the total number of datasets and their respective content is currently unclear. This systematic review aimed to id...

Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting.

PloS one
Skin cancer is currently the most common type of cancer among Caucasians. The increase in life expectancy, along with new diagnostic tools and treatments for skin cancer, has resulted in unprecedented changes in patient care and has generated a great...

Non-melanoma skin cancer diagnosis: a comparison between dermoscopic and smartphone images by unified visual and sonification deep learning algorithms.

Journal of cancer research and clinical oncology
PURPOSE: Non-melanoma skin cancer (NMSC) is the most frequent keratinocyte-origin skin tumor. It is confirmed that dermoscopy of NMSC confers a diagnostic advantage as compared to visual face-to-face assessment. COVID-19 restrictions diagnostics by t...