CHROMAskin | Design Projects

Summary

See every shade, save every life

CHROMAskin is a 2025-2026 UCI BioENGINE Senior Capstone Project in collaboration with the team at DermaVision Technologies and University of California, Irvine Biomedical Engineering Department.

Our Cause

Why skin cancer diagnostics?

1 in 5 Americans will be diagnosed with skin cancer by age 70. This looks like over 9,500 new cases a day. As for the 5-year survival and late stage diagnostic rates for skin cancer, these fluctuate greatly between different ethnic groups with African Americans being particularly marginalized.

Industry Standard

What is the current diagnostic process?

Initial skin cancer screening involves using a dermascopy tool, the primary non-invasive method,which is subjective and leads to less accurate diagnostics. This issue is further amplified for patients with darker skin tones. Even experienced physicians can spend over 15 minutes on skin checks when patients have multiple lesions of concern. After this process patients still have to undergo skin biopsies on suspicious lesions.

Technical Approach/Methodology

Our Solution

CHROMAskin is a portable, noninvasive device that healthcare providers can use in clinics and hospitals. By imaging and analyzing lesions using AI, our device eliminates the subjectivity of diagnosing skin cancer to help make decisions at the point of care.

Multispectral Imaging

Our device images near-infrared wavelengths that standard cameras can’t, capturing extra details to analyze.

AI Model

A machine learning model trained on a diverse set of training images analyzes skin lesions to classify them.

Three Tier Algorithm

For security, the algorithm includes three classification tiers: whether or not the lesion is cancer, what type of cancer it is, and a final confirmation.

Outcomes

Current skin cancer diagnostic tools are becoming faster and more portable, but many still fall short when it comes to equitability. Most rely on surface-level imaging or limited training datasets, which can make diagnosis less accurate for patients with darker skin tones.

Chromaskin is designed to close this equity gap by combining multispectral imaging with AI trained on diverse skin tone data. This allows physicians to quickly and noninvasively evaluate lesions while supporting more fair, consistent, and equitable skin cancer detection for all patients.

Most competitors focus on surface-level imaging, which miss important subsurface features linked to skin cancer.
Chromaskin stands out by combining portability, fast results, below-skin imaging, and diverse skin tone data to support more equitable diagnosis.

Our Plan

The demand for faster and more accessible skin cancer diagnostics continues to grow as skin cancer cases increase worldwide. Current workflows rely heavily on visual assessment and biopsies, creating delays, variability, and healthcare access challenges. CHROMAskin aims to support earlier and more objective lesion evaluation through portable multispectral imaging technology.