Skin Diseases and Skin Cancer Recognition Dataset

Published: 22 November 2023| Version 1 | DOI: 10.17632/xr8fw85n65.1
Md Mafiul Hasan Matin Mafi,


• Skin diseases encompass a broad spectrum of conditions affecting the largest organ of the human body, ranging from common dermatological issues to more severe and potentially life-threatening disorders. Skin cancers, a subset of skin diseases, specifically involve the abnormal and uncontrolled growth of skin cells, often triggered by exposure to ultraviolet (UV) radiation, genetic factors, or environmental influences. Skin cancers, including melanoma, basal cell carcinoma, and squamous cell carcinoma, pose a significant health concern globally due to their prevalence and potential for metastasis. On the other hand, non-cancerous skin diseases, such as eczema, psoriasis, and acne, impact millions, affecting quality of life and sometimes leading to complications if left untreated. Research in this field is vital for understanding the complexities of skin diseases and cancers, developing effective detection methods, advancing treatment options, and ultimately improving outcomes for individuals affected by these conditions. • Early detection, accurate diagnosis, and targeted interventions are key elements in the ongoing efforts to mitigate the impact of skin diseases and cancers on public health. • In recent times, computer vision has shown great promise in conducting the classification and identification tasks of this kind. • Fifty seven distinct kinds of skin diseases and skin cancer are shown in this large dataset, which can be used to develop machine vision-based techniques. • In this dataset, there are 978 (primary source 90, secondary source 888) original images of skin diseases and skin cancer. Then, in order to increase the number of data points, shifting, flipping, zooming, shearing, brightness enhancement, and rotation techniques are used to create a total of 630 augmented images from these original images (primary source).



Daffodil International University, Jahangirnagar University


Computer Vision, Image Processing, Machine Learning, Deep Learning