top of page
Abstract Background

Meet AI Medi Scan

Sunshine, beach and surfing… – these are all natural environments that Australia prides itself on, but with them comes one of the highest rates of skin cancer susceptibility in the world.


Busy schedules, costly evaluations, and lockdown... – these are amongst many reasons that Australian delayed their regular mole monitoring and assessment in the clinic.


Reliable, accurate and affordable – these are all the features of AI Medi Scan. We are here to take care of your problems without compromising your right to enjoy the sunshine.


AI Medi Scan is an Australian company providing advanced solutions for at-home skin cancer imagine, detection, monitoring and diagnosis. The innovative product solution offers improved accuracy rates, reduced ‘false-negative results and skin cancer diagnosis effectiveness by utilising lighting imaging and AI technology.

Abstract Futuristic Background

Meet the team


Rell, Founder


AI Medi Scan was founded by Rell, who is an entrepreneur enjoys helping people and making a difference in their life.


After her studies at the University of Sydney, Rell went on to complete a Diploma of Leadership and Management at the Australian Academy of Commerce so that she can pursue her dream to establish an AU-based health company as an entrepreneur.


While Rell is new to entrepreneurship, she has an open mind and a demonstrated ability to learn quickly. Moreover, she is a leader that others want to follow as she possesses good communication and relationship building skills, perseverance and a kind heart.


After realizing that many Australians adopted the lovely Australian outdoor culture without proper awareness of the risk of skin cancer from UV. The idea of a reasonably priced device that can monitor and check for skin cancer at the comfort of home came to her mind.


Rell brought her idea to her family business, Guangdong High Rate Communication Technology Co., Ltd, which is an advanced manufacturing and research facility in China that focus on light and laser diodes. The company, which is not new to innovation with 13 full-time research and development employees and 26 patents and provisional patents, expressed high interest and full support to help with Rell’s idea. Guangdong High Rate Communication Technology will play a key role in the design and manufacture of the image capturing device in collaboration with AI Medi Scan’s research and development partner.

Connecting Dots
  1. Lighting Imaging Technology

Lighting Imaging Technology offers an automated multi-point analysis of the skin through visual and lighting imaging which provides skin cancer diagnosis from molecular level cell function attributes.


In recent years, this technology has been increasingly used and proven in the field of MediTech.


Recent research about the “Understanding Real-Time special lights signals from Bacteria and Wound Tissues Observed with the MolecuLight ” shows that a special lighting imaging device can detect the bacteria in wounds in a real time based on the intrinsic lighting characteristics, which is different from the background tissues.


By filtering and displaying the endogenous characteristic special lights signals produced from the tissues and bacteria through illuminating the wound with violet light, the resulting images are able to keep recording, assessing and monitoring the lighting bacteria’s presence, location and extent of moderate to heavy load.


AI Medi Scan applies the lighting imaging technology to its advanced light-based sensing device that can image deep into biological tissue and observe molecular scale activity to identify and diagnose skin cancers.

Meet the technology

Connecting Dots

  2. Automated AI platforms for          diagnosis

Automated AI and deep learning platforms have shown scientific evidence of the ability to perform medical diagnosis of skin cancers to the equivalent dermatologist visual accuracy.

In 2017, Stanford University published a study on deep learning of skin tumour machines in Nature. They trained convolutional neural networks (CNN) using a dataset of 129,450 clinical images consisting of 2,032 different diseases and proved AI technology can match or outperform trained dermatologists when it comes to diagnosing skin cancer from images. This research was further supported by additional studies on CNNs trained to detect melanoma in clinical photographs verses that of trained dermatologists. The study supported the findings that a greater level of accuracy can be achieved via AI technology than traditional visual inspection.

Currently, AI skin cancer diagnosis technologies use image recognition algorithms based on visual cues (asymmetry, border diameter, colour, irregularities etc.). AI Medi Scan adopts the superior methodologies, which analysis skin cancer based on cell function by using the special lighting imaging algorithms.

bottom of page