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What is ReadYourLab?

ReadYourLab offers a complimentary DICOM viewer that adeptly manages raw CT and MRI scan files with remarkable efficiency. Leveraging AI-enhanced features, it quickly assesses these scans and demystifies medical terminology for users. Users have the opportunity to ask questions about their scans, and ReadYourLab endeavors to provide insights that deepen their understanding of health matters while preparing them with pertinent queries for their healthcare professionals. The analysis of CT and MRI scans is performed by MedGemma 1.5, an innovative medical AI system created by Google Research, which incorporates 4 billion parameters and is founded on the Gemma 3 architecture. This sophisticated technology employs a medically-optimized vision encoder called MedSigLIP, trained on anonymized medical imaging datasets, which carefully scrutinizes each scan slice in a detailed 3D format, mirroring the meticulous methods of radiologists. Key features include the capability for comprehensive 3D volumetric analysis of DICOM series across both CT and MRI modalities. Furthermore, it adeptly interprets a variety of MRI sequences such as T1, T2, FLAIR, DWI, and enhanced contrast images. The training of MedGemma involved a wide array of medical imaging datasets like MIMIC-CXR and ChestImaGenome, reinforcing its proficiency in understanding intricate medical visuals. Additionally, with a context window of 128K tokens, it effectively manages the processing of extensive scan series, ensuring no detail is overlooked in the evaluation.

What is MedGemma?

MedGemma is a groundbreaking collection of Gemma 3 variants tailored specifically for superior analysis of medical texts and images. This tool equips developers with the means to swiftly create AI applications that are focused on healthcare solutions. At present, MedGemma features two unique variants: a multimodal version boasting 4 billion parameters and a text-only variant that has an impressive 27 billion parameters. The 4B model utilizes a SigLIP image encoder, which has been thoroughly pre-trained on a diverse set of anonymized medical data, including chest X-rays, dermatological visuals, ophthalmological images, and histopathological slides. Additionally, its language model is trained on a broad spectrum of medical datasets, encompassing radiological images and various pathology-related visuals. MedGemma 4B is available in both pre-trained formats, identified with the suffix -pt, and instruction-tuned variants, indicated by the suffix -it. For the majority of use cases, the instruction-tuned version is the preferred starting point, adding significant value for developers. This advancement not only enhances the capability of AI in the healthcare sector but also paves the way for new innovations in medical technology. Ultimately, MedGemma marks a transformative step forward in the application of artificial intelligence in medicine.

Media

Media

Integrations Supported

Dr7.ai
Gemini Enterprise Agent Platform
Gemma 2
Gemma 3
Gemma 4
Hugging Face

Integrations Supported

Dr7.ai
Gemini Enterprise Agent Platform
Gemma 2
Gemma 3
Gemma 4
Hugging Face

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

ReadYourLab

Date Founded

2026

Company Location

Hungary

Company Website

readyourlab.com

Company Facts

Organization Name

Google DeepMind

Date Founded

2010

Company Location

United Kingdom

Company Website

deepmind.google/models/gemma/medgemma/

Categories and Features

Categories and Features

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