# CT Read vs Lunit

CT Read records 103,157 monthly visits with -5.8% month-over-month growth and Paid pricing. Lunit records 29,181 monthly visits with -12.8% growth and Contact for Pricing pricing.

| Metric | [CT Read](https://openaitools.app/tool/ct-read) | [Lunit](https://openaitools.app/tool/lunit) |
| :--- | :--- | :--- |
| Website URL | https://ctread.com | https://www.lunit.io/en |
| Categories | AI Medical Diagnosis, AI Healthcare, AI Report Generator | AI Healthcare, AI Medical Diagnosis, AI Image Recognition |
| Pricing Model | Paid | Contact for Pricing |
| Monthly Visits | 103,157 | 29,181 |
| MoM Growth Rate | -5.8% | -12.8% |
| Primary Market | United States | South Korea |
| Direct Visits | 19,489 | 8,314 |
| Review Score | 3.8 | 4.6 |
| Saved Count | 0 | 1 |
| Supported Platforms | Website | Website |

## CT Read

CT Read is a web platform that uses AI to help people understand medical imaging. Rather than reading raw radiology output, users upload their scans and receive a structured report written in accessible language, covering key findings, likely areas of concern and suggested next steps. The service targets non-medical users such as patients and their families, while also offering a summary-first workflow that clinicians can use as a starting point.

The tool supports multiple imaging modalities — X-ray, CT, MRI, PET and ultrasound — and can analyse many body regions including brain, chest, abdomen and bones. Uploads accept DICOM files as well as JPG, JPEG and PNG images, so users can work with whatever their imaging centre provided. Alongside the analysis engine, CT Read runs a set of free DICOM utilities: an online DICOM viewer, a DICOM-to-JPG converter, a DICOM-to-PDF converter and a DICOM anonymiser.

The interface is translated into many languages including English, German, French, Spanish, Portuguese, Dutch, Turkish, Indonesian, Japanese, Korean, Traditional Chinese and Arabic, and the site runs on a credit-based model. CT Read clearly positions itself as an aid for understanding images rather than a replacement for professional diagnosis.

**Pricing & Plans:** Paid, credit-based. The site uses a credit balance for analyses and offers a free first analysis; specific credit bundles and prices are listed on the Pricing page.

- **Multi-modality analysis:** Interpret X-rays, CT scans, MRI, PET and ultrasound images with a single tool rather than separate services.
- **DICOM and image format support:** Upload DICOM files directly or use common formats such as JPG, JPEG and PNG.
- **Plain-language reports:** Receive structured findings, recommendations and an easy-to-understand summary instead of raw radiology jargon.
- **Free DICOM utilities:** Use the built-in online DICOM viewer, DICOM-to-JPG converter, DICOM-to-PDF converter and DICOM anonymiser at no cost.
- **Full-body coverage:** Analyse scans from the brain, chest, abdomen, bones and other regions for a broad health overview.

**Strengths:** Handles DICOM plus everyday image formats in one place; Reports are written for non-medical readers; Includes free DICOM tools such as a viewer and anonymiser; Interface available in many languages

**Limitations:** Not a substitute for a qualified medical professional's diagnosis; Credit-based pricing requires purchases for ongoing use; AI interpretation of medical images can never guarantee full accuracy

[Profile (Markdown)](https://openaitools.app/tool/ct-read.md)

## Lunit

Lunit is a medical AI company headquartered in Seoul, South Korea, spun out of deep-learning research and focused squarely on oncology. Rather than chasing general-purpose healthcare AI, it has built two connected product families: one that helps clinicians find cancer earlier in imaging, and one that extracts quantitative biology from tissue to guide treatment and drug development. Its technology is used across a large international footprint spanning more than 10,000 customer sites in over 70 countries, with hundreds of peer-reviewed publications and industry partnerships behind the deployments.

On the screening side, the Lunit INSIGHT family analyzes mammograms and chest radiographs. Lunit INSIGHT MMG handles 2D mammography while Lunit INSIGHT DBT covers 3D breast tomosynthesis, both designed to flag suspicious regions so radiologists can prioritize the studies that need attention most. Lunit INSIGHT CXR does the same for chest X-rays. Around these detection engines Lunit has assembled program-level tooling: density assessment, risk assessment and risk pathways, live mammography reporting, quality management, analytics, and a patient hub, so a screening service can run AI as part of its routine rather than as an isolated experiment.

On the precision oncology side, the Lunit SCOPE portfolio analyzes pathology images. Lunit SCOPE IO quantifies the tumor microenvironment and immune cell infiltration, which matters for immunotherapy strategy, while the Lunit SCOPE IHC Suite supports immunohistochemistry quantification across markers such as HER2 and PD-L1, alongside a genotype prediction tool. These products are aimed at biopharma partners, clinical trial teams, and companion diagnostic development, where reproducible quantitative readouts are the bottleneck. Because Lunit sells to hospitals, screening programs, and pharmaceutical companies, pricing is quoted directly rather than published, and regulatory status differs by market.

**Pricing & Plans:** Contact for pricing. Lunit sells enterprise software and platform licenses to hospitals, screening programs, and biopharma partners, so commercial terms and deployment costs are quoted directly through its sales team. No public price list is offered.

- **Lunit INSIGHT MMG and DBT:** Deep-learning analysis of 2D and 3D mammography that marks suspicious lesions to help radiologists detect breast cancer earlier and reduce missed findings.
- **Lunit INSIGHT CXR:** Chest X-ray analysis that highlights potential abnormalities such as nodules and other findings, supporting faster triage in high-volume radiology workflows.
- **Lunit SCOPE IO:** Tumor microenvironment analysis that quantifies tumor-infiltrating lymphocytes and immune phenotypes from pathology slides, informing immunotherapy research.
- **Lunit SCOPE IHC Suite:** AI-assisted immunohistochemistry quantification covering HER2, PD-L1, and other markers, including uIHC and a gene-expression prediction tool for standardized scoring.
- **Screening analytics and workflow tools:** Live mammography reporting, risk assessment, risk pathways, quality management, and patient-facing tools that embed AI into the wider screening program.

**Strengths:** Clinically validated radiology AI with documented regulatory clearances and published evidence; Covers two ends of the cancer pathway — screening detection and precision oncology biomarkers — in one vendor relationship; Wide real-world adoption across many countries, which means integrations and workflow lessons already exist; Strong research output and biopharma partnerships support credibility for trial and CDx work

[Profile (Markdown)](https://openaitools.app/tool/lunit.md)

## Frequently Asked Questions

### How do CT Read and Lunit compare in monthly traffic?

CT Read has 103,157 monthly visits, while Lunit has 29,181. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

CT Read has a month-over-month growth rate of -5.8%; Lunit has -12.8%.

### How does pricing compare?

CT Read: Paid. Paid, credit-based. The site uses a credit balance for analyses and offers a free first analysis; specific credit bundles and prices are listed on the Pricing page. Lunit: Contact for Pricing. Contact for pricing. Lunit sells enterprise software and platform licenses to hospitals, screening programs, and biopharma partners, so commercial terms and deployment costs are quoted directly through its sales team. No public price list is offered.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Ubie](https://openaitools.app/tool/ubie) | 2,941,054 | -23.2% | Free | Free AI symptom checker developed by doctors | [.md](https://openaitools.app/tool/ubie.md) |
| 2 | [Doctronic AI Doctors + Human Doctors](https://openaitools.app/tool/doctronic-ai-doctors-human-doctors) | 1,131,516 | -24.8% | Freemium | AI health guidance with licensed doctors on demand | [.md](https://openaitools.app/tool/doctronic-ai-doctors-human-doctors.md) |
| 3 | [ScanSkinAI](https://openaitools.app/tool/scanskinai) | 265,770 | -10.9% | Freemium, Paid | Free AI skin and mole scanning with optional dermatologist review | [.md](https://openaitools.app/tool/scanskinai.md) |
| 4 | [Overjet](https://openaitools.app/tool/overjet-ai) | 256,150 | +12.6% | Contact for Pricing | FDA-cleared dental AI for diagnostics, imaging, and insurance workflow | [.md](https://openaitools.app/tool/overjet-ai.md) |
| 5 | [Pearl](https://openaitools.app/tool/hellopearl-com) | 221,155 | -7.6% | Contact for Pricing | FDA-cleared dental AI for sharper diagnosis and a smoother front office | [.md](https://openaitools.app/tool/hellopearl-com.md) |
| 6 | [0xmd](https://openaitools.app/tool/0xmd-com) | 128,262 | -2.2% | Freemium | Generative AI for medical and everyday health questions | [.md](https://openaitools.app/tool/0xmd-com.md) |
| 7 | [Docus.ai](https://openaitools.app/tool/docus-ai) | 92,972 | -14.4% | Freemium | AI that reads your lab results and explains what they actually mean | [.md](https://openaitools.app/tool/docus-ai.md) |
| 8 | [Glass Health](https://openaitools.app/tool/glass-health) | 41,068 | -52.2% | Contact for Pricing | Frontier clinical AI grounded in leading medical evidence | [.md](https://openaitools.app/tool/glass-health.md) |
| 9 | [Oatmeal Health](https://openaitools.app/tool/oatmeal-health) | 40,264 | -44.9% | Contact for Pricing | AI lung cancer screening that finds eligible patients and scores every nodule | [.md](https://openaitools.app/tool/oatmeal-health.md) |
| 10 | [RapidAI](https://openaitools.app/tool/rapidai-com) | 20,172 | -27.9% | Contact for Pricing | Enterprise clinical AI that turns medical imaging into faster, more confident care decisions. | [.md](https://openaitools.app/tool/rapidai-com.md) |

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Source: https://openaitools.app/compare/ct-read-vs-lunit

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