The Top 16 AI-Powered Medical Imaging Companies You Need to Know in 2024

As artificial intelligence continues its relentless march into healthcare, medical imaging stands out as one of the areas harnessing these technological capabilities most effectively. AI is transforming how radiologists analyze MRIs, CT scans, ultrasounds and other medical images to detect abnormalities and disease.

According to one estimate, the global AI medical imaging market will reach $4.6 billion by 2030, growing at an annual rate of 34%. With another report forecasting the market could top $2 billion by 2023, it‘s clear major growth lies ahead. You may be wondering: which companies are leading the charge in this space?

In this article, I‘ll provide a comprehensive overview of the top 16 AI medical imaging companies to keep an eye on in 2024. These innovative organizations are developing cutting-edge AI solutions to improve diagnosis, workflows, patient outcomes and more.

I‘ll summarize key facts about the companies in this table, then profile each in more detail:

Now let‘s look at each of these companies and their technologies more closely:

IBM Watson Health

With access to vast computing capabilities and AI expertise, it‘s no surprise that IBM Watson Health is advancing the frontiers of what‘s possible with AI medical imaging.

IBM is exploring how techniques like natural language processing can extract insights from radiology reports and patient medical records to provide more context to doctors reviewing medical images. This additional data empowers the AI to flag potential issues more accurately.

While not yet commercially available, IBM‘s research demonstrates the massive potential value AI can provide by combining image analysis with other data sources. As an AI pioneer with over $16 billion invested in R&D, IBM has the resources to push this technology forward.

Butterfly Network

Butterfly Network made waves with the world‘s first ultrasound-on-chip device in 2017. This innovative ultrasound wand uses semiconductor technology to create detailed ultrasound images, enabling whole-body imaging through a single handheld scanner.

Beyond advanced hardware, Butterfly iQ+ integrates AI to automate parts of the workflow like image optimization and quality analysis. The system provides real-time feedback to the user on how to capture better images.

Butterfly has raised over $350 million in funding to date, and recently went public through a SPAC merger at a $1.5 billion valuation. With growing adoption of its unique portable ultrasound device, Butterfly sits at the intersection of AI software and imaging hardware.

Arterys

Arterys made history by becoming the first company to gain FDA clearance of a deep learning medical imaging tool with its 4D Flow MRI solution.

Arterys‘ cloud-based platform leverages AI to automate the labeling and analysis of blood flow data from cardiac MRIs that previously took physicians 15 minutes per scan. The software cuts the time needed to just 15 seconds while improving accuracy.

The company has raised $43 million to pursue additional AI imaging products for other modalities like CT scans. As the first mover in commercial AI medical imaging, Arterys helped catalyze the industry.

Gauss Surgical

Gauss Surgical focuses on using computer vision and machine learning to monitor blood loss during surgery. Its FDA-approved Triton system calculates blood loss by analyzing surgical sponges and suction canisters in real-time.

This AI-powered imaging gives surgical teams greater transparency into blood levels so they can quickly adapt procedures when necessary to improve patient safety. Gauss has raised $20 million to develop and market its intelligent imaging solutions.

Zebra Medical Vision

Zebra-Med offers an AI1 Imaging Analytics Platform that automatically analyzes medical images and flags abnormalities. The algorithms "learn" to identify organs, tissue, fractures, lesions and other clinical signs.

The company has raised $90 million to analyze millions of images and identify patterns. Its radiology workflow tools help doctors prioritize cases, accelerate turnaround times, and minimize fatigue.

SigTuple

Focused on increasing access to quality healthcare, this Indian startup develops tools to analyze medical images for signs of diseases. Its AI solutions aim to address the country‘s shortage of highly-trained radiologists that leads to misdiagnosis.

SigTuple has raised $65 million to build an intelligent screening system at lower-cost. Its aided tools help doctors remotely evaluate tests and ensure patients get timely diagnoses.

Freenome

What‘s innovative about Freenome is it analyzes routine blood tests rather than images to detect early signs of cancer. It trains AI models to find patterns in blood cell images that serve as biomarkers for malignant tumors.

This non-invasive liquid biopsy technique requires only a standard blood draw. Freenome has raised over $240 million to develop and validate its technology, which achieved 99% accuracy in detecting colorectal cancer in a clinical study.

Enlitic

Enlitic utilizes deep learning to analyze medical images like x-rays, CTs, and MRIs to provide doctors with decision support. Its algorithms generate findings and recommendations from the scans to boost clinical workflow efficiency.

With $27 million in funding, the Bay Area startup has built one of the largest medical imaging datasets to train its models. Enlitic also creates full radiology reports summarizing scan findings rather than just highlighting potential issues.

Caption Health

Leveraging advanced AI, Caption Health provides real-time guidance and feedback during ultrasound image acquisition. This helps clinicians with less ultrasound experience capture diagnostic-quality images efficiently.

Caption aims to expand access to the benefits of ultrasound imaging globally. The technology received FDA clearance in 2020 and has raised $68 million to develop its Empower platform.

Behold.ai

Behold.ai assists radiologists by automatically prioritizing abnormal cases and analyzing scans using computer vision algorithms. Its focus is on improving radiology reporting turnaround times.

The startup has raised $22 million to develop its medical imaging assistance solutions. Based in Israel, Behold.ai represents the opportunities for intelligent workflow optimization in this space.

Viz.ai

Viz.ai centers its AI imaging solutions specifically on stroke care. Its software analyzes CT scans for early signs of a stroke, then automatically notifies a specialist to help expedite treatment.

Rapid stroke treatment is critical for minimizing brain damage and improving outcomes. Viz.ai provides hospitals with "synchronized care" coordination. With $71 million in funding, Viz.ai is leading the way in intelligent stroke diagnosis.

DiA Imaging Analysis

This startup from Israel uses AI to automate analysis of ultrasound images and videos. Its technology detects image borders, produces 3D vascular models, and identifies motion patterns.

By helping automate the interpretation process, DiA‘s solutions aim to improve clinical workflow efficiency and consistency. The company has raised $14 million to analyze ultrasound media.

RetinAi

RetinAi leverages AI and computer vision technology to help doctors diagnose eye diseases through retinal imaging scans. Its solutions identify signs of conditions like age-related macular degeneration.

Early detection of vision disorders can help preserve sight. RetinAi has raised $4.3 million to develop its cloud-based DiscoveryTM platform that screens retinal images for abnormalities.

Subtle Medical

A key obstacle in medical imaging is low-quality CT and MRI scans that lack clarity. Subtle Medical‘s solutions use AI to enhance these images, enabling better diagnoses.

By improving resolution and reducing noise, Subtle aims to increase imaging consistency and accuracy. The startup has raised $7 million to develop and validate its machine learning models.

BrainMiner

BrainMiner‘s software focuses specifically on MRI brain scans. Its automated AI platform analyzes the scans and generates reports to assist doctors in identifying abnormalities like tumors.

By flagging areas of concern in an easily interpreted report, BrainMiner simplifies the process of brain disease diagnosis. This facilitates earlier patient treatment.

Lunit

Based in South Korea, Lunit develops AI solutions for analyzing x-ray, CT, and MRI scans. Its software detects early signs of cancers and other diseases by pinpointing lesions, abnormal tissue, and more.

Lunit Insight, its chest x-ray analysis product, achieved 97% accuracy. With partnerships across the US, Europe, and Asia, Lunit has raised $73 million to drive global availability of its imaging platforms.

The Outlook for AI in Medical Imaging

Medical imaging seems primed for major leaps forward with AI. Radiology is facing surging demand, staff shortages, and a need for more accurate diagnoses. AI can help automate parts of the workflow, improve interoperability of data, and speed up turnaround times.

As the companies profiled here demonstrate, massive technological strides are already being made. We can expect AI medical imaging adoption to rapidly accelerate as more innovative solutions receive regulatory clearance. Values like improved patient outcomes and workflow efficiency are too compelling to ignore.

With inventive startups and tech giants alike pursuing advancements, the future is bright for AI in medical imaging. I‘m excited to see the many ways these technologies augment radiology in the years ahead. Diagnostic medicine may look very different in 2024 as intelligence systems take on a more active role!