C O R P O R A T E P A R T I C I P A N T S Mark Stolper, Executive Vice President and Chief Financial Officer Dr. Howard Berger, Co-Founder, Chairman, President and Chief Executive Officer Dr. Gregory Sorensen, Co-Founder

C O R P O R A T E P A R T I

Mark Stolper, Executive Vice President

and Chief Financial Officer

Dr. Howard Berger, Co-Founder, Chairman,

President and Chief Executive Officer

Dr. Gregory Sorensen, Co-Founder and

Chief Executive Officer, DeepHealth, and President AI Division, RadNet. Inc.

Mark-Jan Harte, Co-Founder and Chief

Executive Officer, Aidence B.V.

Arthur Post Uiterweer, Chief Executive

Officer, Quantib B.V.

C O N F E R E N C E C A L L

P A R T I C I P A N T S

Brian Tanquilut, Jefferies & Company

Sarah James, Barclays

Mitra Ramgopal, Sidoti & Co., LLC

P R E S E N T A T I O N

Good day, everyone, and welcome to today's

call to discuss RadNet's recently announced acquisitions of Aidence and Quantib, and RadNet's strategy for artificial intelligence.

As a reminder, today's conference is being

At this time, I'd like to turn the call

over to Mr. Mark Stolper, Executive Vice President and Chief Financial Officer of RadNet. Please go ahead, sir.

Thank you. Good morning, ladies and gentlemen,

and thank you for joining us today to discuss our recently announced artificial intelligence acquisitions and our AI strategy.

Participants in today's call include Dr.

Howard Berger, RadNet's Chairman and Chief Executive Officer, Dr. Greg Sorensen, CEO and Co-Founder of DeepHealth and President

of RadNet's AI efforts, Mark-Jan Harte, Co-Founder and CEO of Aidence, and Arthur Post Uiterweer, CEO of Quantib.

Before we begin, we'd like to remind everyone

of the Safe Harbor statement under the Private Securities Litigation Reform Act of 1995. Today's prepared remarks and discussion

contain forward-looking statements within the meaning of the Safe Harbor provisions of the U.S. Private Securities Litigation Reform Act

of 1995. Forward-looking statements are expressions of our current beliefs, expectations and assumptions regarding the future of our business,

future plans and strategies, projections and anticipated future conditions, events and trends.

Forward-looking statements in this discussion

include, among others, statements or inferences we make regarding: whether Quantib's and Aidence's existing or any future

products will receive European CE and U.S. FDA 510(k) clearance or other regulatory clearance and/or approval necessary for commercialization;

whether Aidence's and Quantib's existing and any future solutions will prove effective and whether RadNet's development

and deployment of AI solutions will prove effective for improving the care and health of patients; expected market acceptance for Aidence's

and Quantib's products and the willingness of customers to use or continue to use Aidence and Quantib products in the future; Aidence's,

Quantib's and RadNet's ability to develop, maintain and increase their market positions in a competitive environment; and

economic benefits and cost savings anticipated to be derived from AI products and solutions, as well as the anticipated importance of

and impact of AI solutions to RadNet's future business operations.

Forward-looking statements are neither historical

facts nor assurances of future performance. Because forward-looking statements relate to the future, they are inherently subject to uncertainties,

risks and changes in circumstances that are difficult to predict and many of which are outside of our control. Our actual results and

financial condition may differ materially from those indicated in the forward-looking statements. Therefore, you should not place undue

reliance on any of these forward-looking statements. Important factors that could cause our actual results and financial condition to

differ materially from those indicated or implied in the forward-looking statements include those factors identified in the Annual Report

on Form 10-K, Quarterly Report on Form on 10-Q, and other reports that RadNet, Inc. files from time to time with the Securities and Exchange

Any forward-looking statement contained in this

press release is based on information currently available to us and speaks only as of the date on which it is made. We undertake no obligation

to publicly update any forward-looking statement, whether written or oral, that we make from time to time, whether as a result of change

of circumstances, new information, future developments, or otherwise, except as required by applicable law.

With that, I'd like to turn the call over

to Dr. Berger, who will make some opening remarks.

Thank you, Mark, and welcome, everyone.

Today, I would like to describe to you not only

the rational behind the recent announcement, Monday this week, in the acquisition of two additional artificial intelligence companies,

but also expand on what the potential overarching opportunities are for this investment. Monday's announcement marks a seminal event

for RadNet, and perhaps imaging, but not limited to just the specialty of radiology imaging, but perhaps also for the healthcare market.

Artificial intelligence has been a term that has been used for quite some period of time and it has yet to develop a coherent strategy.

Today's conference call is an attempt to

explain some of the factors which led RadNet to make this investment, and my remarks will focused on three themes that I would like to

expand on: number one, consolidation of artificial intelligence around cancer screening; number two, technological advances in equipment;

and, number three, response to the needs for these tools heightened by the recent pandemic.

Let me start with the first, and perhaps the most

important. When RadNet first made is entrance into the artificial intelligence world almost two years ago with its acquisition of DeepHealth

and the leadership of Dr. Gregory Sorensen, who heads that division, we have, for the last several quarters, been talking about expanding

screening tools for cancer.

Our first entrance into this market was out of

our own needs internally for RadNet, given the fact that RadNet does almost 1.6 million mammograms a year, which represents about 4% of

the entire U.S. market, and which we felt was a good investment that would improve both diagnostic accuracy, as well as earlier detection

of breast cancer. Since that time, we have been diligently searching for other partners whose products and whose strategy would complement

that of DeepHealth and breast cancer screening. We were fortunate to find two such companies, both in the Netherlands, which have been

doing artificial intelligence work, primarily around Quantib's efforts in prostate cancer and Aidence's efforts primarily

I'm pleased to report that after our own

extensive due diligence, we believe that combining these two best-of-breed companies for these two cancer screening tools, along with

DeepHealth in breast cancer, gives us the platform to start a more focused strategy on cancer screening not just as a diagnostic tool,

but for population health, much similar to what has already been established for the use of mammography in breast cancer and which is

now something that women do on an annual or biannual basis as part of their routine health and wellness. (Audio interference) efforts

in the way of prostate and lung cancer are here today and need to be availed. With what we will do internally with these three outstanding

teams, meaning DeepHealth, Quantib and Aidence, is internally develop our own colon cancer AI screening tools.

Putting the four of those cancers together, we

believe that the screening for almost 70% of all cancers-solid tumor cancers, that is-can be detectable earlier with not only

artificial intelligence, but new technological advances in equipment. We believe that the opportunity for this is not limited to RadNet,

but limited to payors, health systems and to governmental agencies that formulate public health policy, and that all of these at some

point in time should be tools that, much like mammography for breast cancer, can be accessed directly and routinely by the general public.

The second tenet that I believe is important here

is that this is only possible because of additional advances that have occurred, principally, in the last five years, on the equipment

side. In mammography, we've had advances for digital imaging, as well as better resolution on detectors that allow every radiologist

to see the cancers earlier, and with CT scanning and MRI scanning, the recent advances have allowed for greater flexibility in the patient

experience by significantly shortening scanning times, primarily in MRI, which now makes the adoption of artificial intelligence and screening

tools more accessible and at a lower cost, and I can't emphasize enough how important that is in marrying the artificial intelligence,

which is the reading part, with the technological advances in the equipment which actually performs the scan.

The third, and maybe even the most important part

that I want to emphasize here, is that the response by us and the equipment is magnified by what the pandemic itself has exposed in the

way of challenges to make certain that as these tools become adopted that we can accommodate the needs of the public to provide these

invaluable tools, and I'm particularly referring to the staffing shortages, whether it's on the professional side or on the

technological side, that I believe are a fact of life that we will be living for the foreseeable future. The tools that we're developing,

and, hopefully, that others are working on, will allow the access to equipment and the reliability of these tools to be formed with less

dependency on the staffing that traditionally has been necessary to produce these images and their reports.