Image Quality Assessment of Digital Image Capturing Devices for Melanoma Detection

Abstract

The fast-growing incidence of skin cancer, especially melanoma, is the guiding principle for intense development of various digital image-capturing devices providing easier recognition of melanoma by dermatologists. Handheld and digital dermoscopy, following of mole changes with smartphones and digital analysing of mole images, is based on evaluation of the colours, shape and deep structures in the skin moles. Incorrect colour information of an image, under- or overexposed images, lack of sharpness and low resolution of the images, can lead to melanoma misdiagnosis. The purpose of our study was to determine the colour error in the image according to the given lighting conditions and different camera settings. We focused on measuring the image quality parameters of smartphones and high-resolution cameras to compare them with the results of state-of-the-art dermoscopy device systems. We applied standardised measuring methods. The spatial frequency response method was applied for measuring the sharpness and resolution of the tested camera systems. Colour images with known reference values were captured from the test target, to evaluate colour error as a CIELAB (Commission Internationale de l’Eclairage) ΔE*ab colour difference as seen by a human observer. The results of our measurements yielded two significant findings. First, all tested cameras produced inaccurate colours when operating in automatic mode, and second, the amount of sharpening was too intensive. These deficiencies can be eliminated through adjusting the camera parameters manually or by image post-production. The presented two-step camera calibration procedure improves the colour accuracy of captured clinical and dermoscopy images significantly.

Teledermatology During COVID-19: An Updated Review

“…Store-and-forward TD relies on the transmission and storage of photos, and a review written during COVID-19 showed that smartphones are a widespread method of taking clinical photos [ 54 ]. Another 2020 study revealed that smartphones with automatic camera settings produce oversaturated photos, making it difficult to determine possible malignancy based on color of lesions [ 55 ]. In addition to the implied risk of misdiagnosis, taking and storing photos on personal smartphones is not considered a secure way of storing patient information and can lead to Health Insurance Portability and Accountability Act (HIPAA) violations [ 54 ].…”

No-Reference Image Quality Assessment Based on the Fusion of Statistical and Perceptual Features

“…Visual signals (digital images or videos) undergo a wide variety of distortions during acquisition, compression, transmission, and storage. Thus, image quality assessment (IQA) is crucial to predict the quality of digital images in many applications, such as compression, communication, printing, display, analysis, registration, restoration, and enhancement [ 1 , 2 , 3 , 4 ]. Generally, it can be used in benchmarking any image processing algorithms.…”

Development and Narrow Validation of Computer Vision Approach to Facilitate Assessment of Change in Pigmented Cutaneous Lesions

“…There has been considerable interest in the use of smartphone applications to facilitate computer-aided diagnosis and monitoring of suspicious skin lesions, although the results generated by the software have so far not been shown to be of clinical utility ( Freeman et al., 2020 ; Matin and Dinnes, 2021 ). A recent study showed that the parameters of commercial digital cameras and smartphones could be modified to increase the accuracy of the images, generally by disabling some automatic settings that were intended to produce more visually appealing images for consumers but can reduce accuracy ( Dugonik et al., 2020 ). For optimal results with DermaViz analysis of smartphone images, it will be important to specify acquisition protocols to promote accuracy and consistency between images acquired over time.…”