Medinnoscan Company Brochure

Brief

MedInnoScan exhibition materials

Company introduction

MedInnoScan is a Hungarian startup developing artificial intelligence-based solutions for various
medical diagnostics purposes. MedInnoScan works with medical specialists, AI experts, and
developers to identify various diagnostical areas where its leading-edge AI technology can be utilized
to create innovative and pragmatic solutions to health issues affecting millions of patients
worldwide.

Visual appearance

MedInnoScan is a high-tech R&D company in the medical field. Its visual appearance should combine
the leading-edge technology image with the professionalism and competence expected from
companies dealing with human health. MedInnoScan does have a logo (attached), of which the
graphical part (the brain and numbers) is universally used, whereas the company name and the font
thereof is not a compulsory element and often is included in the font of the generic text.

The typing of the company name includes capitalization of the fourth and eight letters, thus yielding
MedInnoScan.

As for colors, MedInnoScan mostly uses light-medium blues, greys and blacks, but other colors
(mostly pastel versions of cool colors) are also appearing on company materials.

Purpose of the exhibition materials

MedInnoScan is an exhibitor at one of the biggest medical technology trade shows in Hungary. The
goal of the attendance is to attract potential partners, investors and prospective customers alike. As
the company does not have a marketable product yet, the focus should be on the technology and
methods used, as well as the corporate image as a coveted investment target/partner/supplier.

Description of exhibition materials

The rollup (1000 x 2000 mm) should be a generic presentation of the company, concentrating on the
name, activity and main features. As the rollup is prominently displayed on the booth and is normally
the first encounter of the visitor with MedInnoScan, it is essential that it should only convey the most
important pieces of information in a format visible from a distance too.

The banner (2000 x 2000 mm) should be a display of the company’s research areas (prospective
products). In addition to repeating the main messages already featured on the rollup (these will be
exhibited on very different locations) about the company, it should present the three research fields
(knee cartilage donor matching, lung cancer diagnostics and chronic wound classification) with a
uniform structure. The banner can contain more detailed information and fine print, as the
assumption is that interested visitors will get a closer look anyway.

The brochure card (100 x 150 mm) is replacing the paper brochure and the main element of it is a
link to the website featuring the actual brochure in form of a QR code. As

Rollup

Logo + “MedInnoScan” as text, or the whole logo with text
Powering diagnostics with artificial intelligence - tagline

Diagnostic excellence
Classification and AI training based on cooperation with top health institutes
Training sets of more than 5,000 patients

Image processing
Computer vision algorithms adapted for 3D images
CT, MRI or photogrammetrically reconstructed 3D images based on photos

End-to-end solutions
Mobile applications for photo processing and data capture
Integrated databases and versatile EMR interfaces for patient data/donor matching
Automatic processing of CT/MRI images

Application areas
Knee cartilage matching
Chronic wound classification and therapy suggestion
Lung cancer diagnostics

The mock is as follows:

The idea is to use icons for the text blocks (should be some uniform style,
detailed ones) and connecting those with both chip welding and neuron-
style connections. However, any other idea is acceptable. Blocks can be
separated from the background by any means (solid line, color
difference, whatever fits into the artistic concept) The application area
block can be a different style, icon is optional and the connection should
be something other than in case of the other three. If there is a nice and
subtle background image, that is welcome.

Banner

The banner is consisting of three blocks for each MedInnoScan solution. The solution descriptions are
given in the same format: Diagnostic problem/Image and AI processing/Application. Icons should be
added to these categories, probably monochromatic black ones). The three application blocks can be
separated by any means (borders, colors, etc.), but a uniform graphic design is required with some
drawing elements extended to the whole banner. Each block should feature two pictures, one
anatomic drawing of the body part targeted (e.g. knee, skin, lung) and one typical picture of the given
area (knee MRI, lung CT, scar picture). The pictures should be in the same layout, but can be
transformed, blurred, recolored, as the design requires). Important: the wound picture should be one
that is not disturbing, but acceptable for viewing for general audiences. If no suitable image can be
found, the wound picture should also be replaced by a drawing.
Mock:

Logo + “MedInnoScan” as text, or the whole logo with text
Powering diagnostics with artificial intelligence – tagline
Research and application areas – title
Knee cartilage matching
Diagnostic problem
Knee cartilage degradation is symptomatic for 15% of the population over 55 in North America and
Europe. While smaller damages (< 3 cm2) can be cured with numerous therapeutic methods, medium
and extensive (> 15 cm2) damages are typically treated with prosthetics. Allografts – despite being
considered the best solution for medium and extensive damages – are rarely used because the
geometric matching needs to be done manually, using the whole donor tissue, even when the
recipient only needs a part of it.

Imaging and AI processing

MedInnoScan processes MRI images and uses various AI methods to train a neural network that can
identify cartilage tissues. Following a successful prototype with 300 MRI images, the training set will
include 5 000 segmented cartilage MRIs, as a result of which the AI engine is able to distinguish
cartilage tissue on any knee MRI image.

Application

MedInnoScan is building a matching engine for donors and recipients to allow a successful allograft
for the patients in need. The trained AI engine identifies the recipients’ cartilage and defines a
mathematical approximation of its surface. Based on donors’ images, matching is then performed by
a heuristic combinatorial geometric algorithm, to the specified tolerance, taking factors like patient’s
needs, time on waiting list, etc. into consideration. The application is provided on a pay-per-use
basis, in SaaS form.

Chronic wound classification

Diagnostic problem

A chronic wound is a wound that does not heal in an orderly set of stages and in a predictable
amount of time; wounds that do not heal within six weeks are considered chronic. These wounds
significantly degrade the quality of life for patients and create a risk for severe complications such as
limb amputation and create a large financial burden for the healthcare system. Up to 40-60 % of the
patients with chronic wounds are not treated with the most efficient bandage and/or medical
therapy available.

Imaging and AI processing

MedInnoScan aims to create a 3D model of patient wounds using photogrammetry processes on a
set of high resolution photos. The reconstructed three-dimensional images are controlled by a
precision 3D scanner for accuracy. With the help of an experienced team of surgeons and nurses we
classify the various wound types and treatment options and match them with the 3D images of real-
life wounds. More than 200,000 images of 5,000 wounds are used as a training set for the AI engine
that will be able to automatically determine wound types and suggest the best bandage and therapy
options.

Application

A mobile application is developed that can be used by skilled nurses to make photos and enter data
about the patient being treated. Images and other information are then uploaded to a central server
operated as an SaaS service on a subscription basis. The 3D reconstruction and the classification by
the AI engine is performed by this central service over the web and therapeutic recommendations
and bandage suggestions are sent back to the application along with the classification results.

Lung cancer diagnostics

Diagnostic problem

Lung carcinoma is one of the most widespread tumor type in the world. Lung cancer occurred in 1.8
million people and resulted in 1.6 million deaths last year. This makes it the most common cause of
cancer-related death in men and second most common in women after breast cancer. As the vast
majority (85 %) of discovered non-small-cell lung carcinoma cases can be associated with smoking,
thus the risk groups can easily be identified, and the treatment chances are much better with an

early discovery, lung carcinoma is a very promising candidate for screening. However, X-rays often
fail to reveal the early stage lung cancer, whereas CT scans (generally between 80 and 500 slices)
require a tedious and time consuming manual evaluation, with the positive cases only amounting to
1-2 % of the cases.
Imaging and AI processing
MedInnoScan uses CT images and builds a 3D representation of the lung based on CT scans. Using
segmented results and a basic training set of 5,000 positive and 5,000 negative CT images, the AI
engine’s accuracy is expected to reach more than 95% in binary classification (carcinoma/not
carcinoma).
Application
MedInnoScan will build an SaaS solution to be used as a plug-in for teleradiology applications and
standalone application scenarios. The AI engine receives and processes the CT images and returns
the detailed classification results, including probability of carcinoma and the location(s) of suspected
malignant tissue(s). A licensed embedded version of the engine (to be used in computerized CT
scanners and other modern diagnostic equipment) is also foreseen.

Card

The card is a postcard-sized paper substituting a paper brochure with a weblink. The design can be a
bit fancier than the other materials, but it needs to be minimalistic with the QR code in the center.
Mock:

It might contain images used on the banner, but that's not a must.
Logo + “MedInnoScan” as text, or the whole logo with text
Powering diagnostics with artificial intelligence – tagline
Learn more about MedInnoScan solutions at
<QR code>
www.MedInnoScan.com/brochure