Reconstruction Principles of Localized Non-melanoma Skin Cancer and Cutaneous Melanoma

Pallua, Norbert; Kim, Bong-Sung

doi:10.1007/978-3-030-18797-2_7

Cited by 1 publication

(1 citation statement)

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“…While metastatic melanoma, which invades blood vessels and spreads to distant parts of the body, develops deep within the skin. This might transmit malignancy to several organs, including the blood, liver, lungs, and brain [9]. feature selection, as well as categorization, shared by all artificial vision system proposals [16].…”

Section: A Skin Cancer and Its Typesmentioning

confidence: 99%

A Review on Skin Disease Classification and Detection Using Deep Learning Techniques

Kavitha,

Prasanna

2023

IJRITCC

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Skin cancer ranks among the most dangerous cancers. Skin cancers are commonly referred to as Melanoma. Melanoma is brought on by genetic faults or mutations on the skin, which are caused by Unrepaired Deoxyribonucleic Acid (DNA) in skin cells. It is essential to detect skin cancer in its infancy phase since it is more curable in its initial phases. Skin cancer typically progresses to other regions of the body. Owing to the disease's increased frequency, high mortality rate, and prohibitively high cost of medical treatments, early diagnosis of skin cancer signs is crucial. Due to the fact that how hazardous these disorders are, scholars have developed a number of early-detection techniques for melanoma. Lesion characteristics such as symmetry, colour, size, shape, and others are often utilised to detect skin cancer and distinguish benign skin cancer from melanoma. An in-depth investigation of deep learning techniques for melanoma's early detection is provided in this study. This study discusses the traditional feature extraction-based machine learning approaches for the segmentation and classification of skin lesions. Comparison-oriented research has been conducted to demonstrate the significance of various deep learning-based segmentation and classification approaches.

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Section: A Skin Cancer and Its Typesmentioning

confidence: 99%