Explore chapters and articles related to this topic
Convolutional Neural Network for Classification of Skin Cancer Images
Published in K. Gayathri Devi, Kishore Balasubramanian, Le Anh Ngoc, Machine Learning and Deep Learning Techniques for Medical Science, 2022
Giang Son Tran, Quoc Viet Kieu, Thi Phuong Nghiem
It was reported by [2] that each day there are nearly 10,000 people having skin cancer in the United States, and two people die every hour. Moreover, the treatment cost of skin cancer is very high. For example, in the United States, around $8.1 billion is used each year for skin cancer treatment [2]. In 2021, more than 5,400 people worldwide are estimated to get death due to nonmelanoma skin cancer each month, in which around 7,180 people (64% men, 36% women) will die of melanoma [2]. With large numbers of deaths caused by skin cancer, early detection will save lives for many patients. The statistics show that if a melanoma patient is treated appropriately at an early stage, they can achieve up to a 99% 5-year survival rate [2]. Therefore, a patient's survival rate can be enhanced by early detection, and diagnosis of skin cancer can help enhance the survival rate of patients.
Introduction
Published in Venkatesan Rajinikanth, E. Priya, Hong Lin, Fuhua Lin, Hybrid Image Processing Methods for Medical Image Examination, 2021
Venkatesan Rajinikanth, E. Priya, Hong Lin, Fuhua Lin
The ABCDE rule helps to detect the skin cancer based on the following parameters:Asymmetric: Common moles are likely be round and balanced, but one side of the cancerous mole will probably be dissimilar to the other.Border: The outer surface is irregular rather than smooth and may appear tattered, uneven, or blurred.Colour: Skin cancer section may tend to have patchy shades and colors including black, brown, and tan.Diameter: Melanoma can cause a change in the size of a mole.Evolving: Variation in a mole’s exterior over weeks or months can be a symptom of melanoma.
IoT-Based Automated Skin Lesion Detection and Classification Using Gray Wolf Optimization with Deep Neural Network
Published in Mohamed Elhoseny, K. Shankar, Mohamed Abdel-Basset, Artificial Intelligence Techniques in IoT Sensor Networks, 2020
A. Daniel, S. Venkatraman, Srinath Doss, Bhanu Chander Balusa, Andino Maseleno, K. Shankar
In medical examination, dermatologists apply the dermoscopy for detecting the presence of melanoma. Dermoscopy is defined as the non-invasive image examination for pigmented skin lesions in dermatology [4]. The dermoscopy is performed by placing a gel on the affected skin area and using a magnifier, the infected region becomes more visible than seeing through the human eye. Such pigmented model as well as structures is applied for examining the melanoma under the application of diverse diagnosing systems like ABCD rule, 7-point checklist, and Menzies approach. Therefore, it is based on human vision, general training, and medical experience of dermatologist. As a result, dermoscopy can achieve maximum accuracy in melanoma diagnosis [5]. Therefore, in order to maximize the efficiency of melanoma analysis, programmed dermoscopic image investigation is applied [6]. Computer-based skin lesion prediction as well as classification is composed of various steps like preprocessing, segmentation, feature extraction, and classification. Some of the typical disadvantages in computer-aided detection (CAD) models are lesion area segmentation as well as continuous features selection (FS) from original data. Furthermore, it uses various methods of imaging modalities; hence, it suffers from demerits that make the process highly tedious.
ADTBO: Aquila driving training-based optimization with deep learning for skin cancer detection
Published in The Imaging Science Journal, 2023
Vadamodula Prasad, Emil Selvan G. S. R., Ramkumar M. P.
According to current advances in medical technology, skin cancer is the major type of disease in humans. Even though melanoma is considered a type of cancer, it is difficult to anticipate when it will occur. Melanoma and other skin conditions can be successfully treated if they are discovered in the early stages. To promptly and accurately identify these types of skin lesions, medical imaging technology is crucial [1]. Based on the report of cancer distributed by the American Cancer Society, skin cancer has the highest mortality rates at up to 75%, and the incidence of melanoma, which has the highest death rate, is still rising at 14%. Fortunately, the likelihood of survival is extremely high if the disease can be identified and treated quickly in the early stages [2]. Recent studies indicate that, in comparison to other cancer, the number of persons with skin cancer is rising each year. Melanoma is the prevalent category of skin cancer among many others. Melanocytes are the cells that affect the skin's surface. It has many cell types that contribute to the skin's aging process. It is more deadly and harmful because of its quick spread [3].
The effects of sport, setting, and demographics on sunscreen use and education in young athletes
Published in Research in Sports Medicine, 2023
Tracy Zaslow, Akash R. Patel, Rachel Coel, Mia J. Katzel, Tishya A.L. Wren
Sun exposure aids vitamin D absorption and improves bone health; however, overexposure may increase the risk of melanoma and other skin cancers (American Cancer Society, 2019b). Melanoma is a skin cancer caused by uncontrolled growth of melanocytes, which can result in metastatic disease (American Cancer Society, 2019a). In 2023 alone, an estimated 97,610 new melanoma diagnoses will be made in the United States (US), resulting in estimated 7,990 deaths (Siegel et al., 2023). Melanomas account for 3% of cancers identified in adolescents and 1% in children (Siegel et al., 2021) and increased by an average of 2% per year between 1973 and 2009 (Wong et al., 2013). While death from melanomas has been decreasing recently due to advances in treatment (Siegel et al., 2021; Ward et al., 2019), skin cancer from excessive UVR exposure early in life is one of the most preventable types of cancer due to the availability of chemical and physical barriers (De Castro-Maqueda et al., 2021).
Recent advances in nanotechnology based combination drug therapy for skin cancer
Published in Journal of Biomaterials Science, Polymer Edition, 2022
Shweta Kumari, Prabhat Kumar Choudhary, Rahul Shukla, Amirhossein Sahebkar, Prashant Kesharwani
Diagnoses of skin cancer starts with a medical history, local examination of skin, dermatoscopy, high frequency ultrasonography and histopathological examination with surgical biopsy (Figure 3). Dermatoscopy is a noninvasive method, it refers to the examination of skin using skin surface microscopy (lens system) and a strong light source which is useful in distinguishing typical skin cancerous changes and is also called as ‘epiluminoscopy’ and ‘epiluminescent microscopy’. Dermatoscopy is mainly used for the evaluation of pigmented skin lesions. In, experienced hands, it is easier to diagnose melanoma. Dermatoscopy is helpful in diagnosing basal cell cancer in addition to skin inspection [31]. With both melanoma and non melanoma skin cancer, the diagnostic confirmation of a suspected lesion is done with the help of skin biopsy and histopathological examinations. The biopsy of the lesion is done by doing excision of 2–5 mm of healthy skin and is accomplished either using punch or shave biopsy. The treatment is decided on the basis of size and the anatomical site of the tumour.