Impact of chromophores on colour appearance in a computational skin model

Early diagnosis of skin cancer offers the patient more favorable treatment options. Color fidelity of skin images is a major concern for dermatologists as adoption of digital dermatoscopes is increasing rapidly. Accurate color depiction of the lesion and surrounding skin are vital in diagnostic evaluation of a lesion. We previously introduced VCT-Derma, a pipeline for dermatological Virtual Clinical Trials (VCTs) including detailed and flexible models of human skin and lesions, which represent the patient in the entire dermatoscopy-based diagnostic process. However, those initial models of skin and lesions did not properly account for tissue colors. Our new skin model accounts for tissue color appearance by incorporating chromophores (e.g., melanin, blood) into the tissue model, and simulating the optical properties of the various skin layers. The physical properties of the skin and lesion were selected from clinically plausible values. The model and simulated dermatoscope images were created in open modelling software, assuming a linear camera model. We have assumed ambient white lighting, with a 6mm distance to the camera. Our model of color appearance was characterised by comparing the brightness of the lesion to its depth. The brightness of the lesion is compared through the variability of the mean gray values of a cropped region around the lesion. We compare two skin models, one without extensive chromophore content and one with. Our preliminary evaluation of increasing chromophore content shows promise based on the results presented here. Further refinement and validation of the model is ongoing

Effects of smartphone sensor characteristics on dermatoscopic images : a simulation study

Dermatoscopes are commonly used to evaluate skin lesions. The rising incidence of skin cancer has led to a wide array of medical imaging devices entering the market, some of which provide the patient the ability to analyze skin lesions themselves. They usually come in the form of smartphone attachments or mobile applications that leverage the optics of the smartphone to acquire the image; and in some cases, even give a preliminary diagnosis. In this digital age these devices look to ease the burden of having to visit a dermatologist multiple times. While these attachments are no doubt very useful, the image sensors used within smartphones are limited in terms of how much information they can process and effectively output to the user. Smartphone sensors are also very small which can result in a less detailed image as opposed to one from a professional camera. Our work is focused on the analysis of the information lost due to the known limitations of smartphone sensors, and its effect on the image appearance. This analysis has been performed using a virtual simulation pipeline for dermatology called VCT-Derma, which contains a module for a proprietary dermatoscope whose optical stack parameters will be adapted to the smartphone sensor specifications mentioned in this manuscript. This manuscript also describes the necessary sensor parameters required for adapting the simulation model, the software used along with any assumptions made, perceived differences in the resulting images, as well as the direction of the ongoing work

Solution for Nonuniformities and Spatial Noise in Medical LCD

This paper describes a method 23 to characterize the spatial noise present in high-resolution 24 medical displays and a technique to solve the problem. A 25 medical display with built-in compensation for the spatial 26 noise at pixel level was developed and improved image 27 quality is demonstrate

Solution for Nonuniformities and Spatial Noise in Medical LCD Displays by Using Pixel-Based Correction

Liquid crystal displays (LCD) are rapidly replacing cathode ray tube displays (CRT) for medical imaging. LCD technology has improved significantly in the last few years and has important advantages over CRT. However, there are still some aspects of LCD that raise questions as to the usefulness of liquid crystal displays for very subtle clinical diagnosis such as mammography. One drawback of modern LCD displays is the existence of spatial noise expressed as measurable stationary differences in the behavior of individual pixels. This type of noise can be described as a random stationary image superposed on top of the medical image being displayed. It is obvious that this noise image can make subtle structures invisible or add nonexistent patterns to the medical image. In the first case, subtle abnormalities in the medical image could remain undetected, whereas in the second case, it could result into a false positive. This paper describes a method to characterize the spatial noise present in high-resolution medical displays and a technique to solve the problem. A medical display with built-in compensation for the spatial noise at pixel level was developed and improved image quality is demonstrated