IB Lab LAMA
by ImageBiopsy Lab
· Based in Austria →
— World's first AI software for fully automatic measurements on long leg radiographs with hip or knee implants.
Contact vendor for details
Regulatory Status Disclosed
Overview
IB Lab LAMA™ is an AI-powered software designed for fully automated and precise measurements on long leg radiographs. It utilizes deep learning technology to evaluate lower limb deformities, including leg length discrepancy and knee alignment parameters. The tool supports both pre- and post-surgery radiographs, including those with total hip and total knee implants. It aims to accelerate, standardize, and improve the accuracy of assessments in orthopedic and radiological workflows, reducing manual measurement time significantly. IB Lab LAMA provides comprehensive visual output reports with relevant clinical findings, which can be integrated into PACS and RIS systems for efficient reporting and monitoring of disease progression.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- Fully automated measurements on long leg radiographs.
- Supports radiographs with total hip and total knee implants.
- Deep learning technology for precise leg geometry analysis.
- Provides over 12 standardized radiological measurements (e.g., genu varum, genu valgum, HKA, MAD, femur/tibia length).
- Reduces reading and reporting time significantly (from 8 minutes to under 60 seconds).
- Generates visual output reports attached to original x-ray images.
- Integration with PACS and RIS systems for accelerated reporting.
- Aids in detecting genu varum/valgum and leg length discrepancy.
- Compares measurements to predetermined norm-ranges.
- Facilitates monitoring of disease progression over time.
Use Cases
- Pre- and post-operative assessment for hip and knee surgeries.
- Evaluation of lower limb deformities.
- Detection of genu varum/valgum.
- Measurement of leg length discrepancy.
- Surgical planning for interventions (e.g., OWHTO, TKA).
- Standardized and objective analysis of musculoskeletal imaging data.
What Physicians Need to Know
DICOM Support & Standards
IB Lab LAMA supports DICOM input and outputs results as DICOM Secondary Capture, PDF, and Structured Reports, ensuring compatibility with existing imaging infrastructure.
PACS Integration Method
The tool offers seamless, 'zero-click' integration into standard reading environments (PACS) and Radiological Information Systems (RIS). Results are automatically stored in PACS and are viewable in DICOM viewers as printable PDF reports. It also supports integration via AI marketplaces or distribution platforms.
Reading Room Workflow Impact
IB Lab LAMA significantly reduces reading and reporting time for lower limb deformity radiographs, cutting it from 3-8 minutes to under 1 minute (up to a 90% reduction). It automates measurements, standardizes results, and reduces inter-reader variability, allowing for pre-selection and triaging of cases.
AI Model Architecture (deep learning approach)
The software utilizes deep learning technology, including convolutional neural networks and classification technologies, to provide fully automated and precise geometric length and angle measurements of the lower limb.
Processing Speed (per study)
IB Lab LAMA delivers results rapidly, with calculations completed within seconds to under one minute per study.
FDA Clearance Pathway (510k/De Novo)
IB Lab LAMA received FDA 510(k) clearance, classifying it as a Class II medical device.
Supported Modalities (CT/MRI/X-ray/US)
The tool is specifically designed for X-ray images, particularly full-leg X-rays (long leg radiographs), and supports analysis of images both with and without hip or knee implants.
Sensitivity & Specificity Data
Clinical studies have shown high reliability, substantial agreement with expert radiologists, and high sensitivity and specificity in detecting arthroplasties. It achieves accurate and precise measurements of knee alignment within u22641u00b0 and leg-length discrepancy within u22642mm. Specific precision for HKA, JLCA, and MAD is within 0.3u00b0, 0.8u00b0, and 1.1 mm respectively, and leg length discrepancy is accurate to 0.2 cm compared to expert readers.
RSNA/ACR Validation
A study published in Skeletal Radiology (November 2021) demonstrated the software's human-reader grade accuracy and efficiency gains, utilizing extensive training data from multi-site locations including the US. ImageBiopsy Lab presented LAMA at RSNA 2021, and the ACR Data Science Institute (DSI) has identified leg length discrepancy measurement in radiographs as a key AI use case.
Physician Tip
IB Lab LAMA can significantly streamline the assessment of lower limb deformities and leg length discrepancies on X-rays, offering standardized and reproducible measurements. Physicians should leverage its automated reports for pre-operative planning and post-operative evaluation, especially in cases involving implants. While highly accurate, it's crucial to remember that the software is an aid and should complement, not replace, comprehensive patient evaluation and professional interpretation. The rapid processing speed allows for more efficient workflow and increased focus on patient consultation.
IB Lab LAMA is designed for flexible integration within existing radiology ecosystems. It seamlessly connects with PACS, RIS, and Clinical Information Systems (CIS), and can be deployed as a cloud-based, hybrid, or on-premise solution. Its output in standard DICOM formats (Secondary Capture, PDF, Structured Report) ensures compatibility with various medical viewers and reporting templates, facilitating a smooth transition into current clinical workflows.
Details
| Category | Radiology & Imaging AI, Surgical AI |
| Pricing | Contact vendor for details — Subscription-based; based on number of analyses (inferred from other IB Lab products) |
| Deployment | Cloud-based, Hybrid solution, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker). |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated IB Lab LAMA received FDA 510(k) clearance (K223646) on June 16, 2023, as a Class II medical device with product code QIH. It was determined to be substantially equivalent to predicate devices, intended to aid healthcare professionals in measuring limb-length discrepancy and quantitative knee alignment parameters. |
| Integrations | |
| EHR | Not specified |
| Specialties | Orthopedics, Radiology |
Ratings & Reviews
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Press & Coverage
Healthcare AI
ImageBiopsy Lab (IB Lab) expands its FDA-cleared musculoskeletal (MSK)-portfolio with the 510(k) clearance of its LAMA software.
ImageBiopsy Lab received 510(k) clearance from the FDA for IB Lab LAMA, a fully-automated radiological image processing software for geometric length and angle measurements of the lower limb on full leg X-rays. This clearance is a significant step for the company to make its solution available to surgeons and healthcare providers in the United States.
2023-06
Medical Device Network
ImageBiopsy Lab obtains FDA approval for image processing software
ImageBiopsy Lab secured FDA approval for its AI-powered software, IB Lab LAMA, designed for automated geometric length and angle measurements of the lower limb on full-leg X-rays. The company aims to expand its musculoskeletal-focused software solutions in the US.
2023-06
PR Newswire
FDA clears ImageBiopsy Labs' latest AI-powered Software for a comprehensive Set of Automated Measurements on Long Leg Radiographs
ImageBiopsy Lab announced FDA clearance for IB Lab LAMA, the first fully-automated radiological image processing software for geometric length and angle measurements of the lower limb on full leg X-rays. This software aims to expedite and standardize image-based workflows for surgeons and radiologists.
2023-06
Medium (Tarek Roustom, MD)
An exciting week for ImageBiopsy Lab u2014 2 regulatory approvals
ImageBiopsy Lab received 510K FDA clearance for its AI software, IB Lab LAMA, which automates geometric length and angle measurements of the lower limb on full-leg X-rays, providing 71 different radiological findings and measurements.
2023-08
ImageBiopsy Lab Blog
OUT NOW: IB Lab LAMA 2.0
ImageBiopsy Lab launched IB Lab LAMA 2.0, a major upgrade to its AI solution for lower limb alignment and leg length discrepancy assessment. This new version offers enhanced performance for pre- and post-operative workflows, including complex cases with implants, osteotomies, and pediatric patients.
2025-08
Health AI Register
IB Lab LAMA - Health AI Register
IB Lab LAMA is a diagnostic support tool that uses deep learning technology for automated measurement of leg geometry to evaluate lower limb deformities. It has CE and FDA certifications and is supported by several peer-reviewed papers.
2026-05
ImageBiopsy Lab Blog
IB Lab LAMAu2122 - World's first AI Software for fully automatic Measurements on Long Leg Radiographs with Hip or Knee Implants
IB Lab LAMAu2122 now supports radiographs with total hip and total knee implants, offering 12 standardized measurements for both pre- and post-surgery radiographs. This advancement aims to reduce workload and improve workflow for medical professionals by automating radiological measurements.
2025-01
Journal of Clinical Medicine (via PMC)
The Role and Efficiency of an AI-Powered Software in the Evaluation of Lower Limb Radiographs before and after Total Knee Arthroplasty
A study assessed the concordance between IB Lab LAMA software and orthopedic specialists in evaluating lower extremity metrics, finding good to excellent agreement and superior time efficiency for the software. The LAMA software could measure one radiograph in 20 seconds, more than twice as fast as orthopedics' measurements.
2023-08
Videos
Product demos, reviews, and walkthroughs for IB Lab LAMA.
Automated Assessment of Long Leg Radiographs - IB Lab LAMA V.2 - PACS Demo
ImageBiopsy Lab
Frequently Asked Questions
IB Lab LAMA seamlessly integrates into existing PACS and RIS workflows, providing fully automated, standardized, and precise measurements of lower limb alignment and leg length discrepancy from X-ray images. This integration significantly reduces reading times and minimizes inter-observer variability, offering valuable decision support for pre- and post-operative planning in orthopedics.
IB Lab LAMA has received FDA 510(k) clearance in the United States and CE certification in Europe, classifying it as a Class II medical device. ImageBiopsy Lab's privacy policy indicates that personal data processing adheres to statutory provisions like GDPR, and the software itself does not directly interact with patients, focusing on image analysis.
IB Lab LAMA is intended as an aid for healthcare professionals and should not be used in lieu of full patient evaluation or as the sole basis for diagnosis. It is not indicated for use on radiographs that include ankle arthroplasties or unicompartmental knee arthroplasties.
Current alternatives typically involve manual measurements using traditional rulers or digital calipers, as well as other interactive software applications. However, these methods are often time-consuming, can exhibit high intra- and inter-observer variability, and may have lower reproducibility compared to automated AI solutions.
Specific pricing models for IB Lab LAMA are not publicly available; interested parties are generally advised to contact ImageBiopsy Lab directly for a demo and detailed pricing information. The cost is typically based on licensing agreements, which may consider factors such as the volume of analyses or institutional size.
Clinical studies have demonstrated that IB Lab LAMA provides highly reliable and accurate measurements, performing comparably to expert human readers while significantly reducing analysis time. The software aims to mitigate the high variability and poor reproducibility often associated with manual radiographic assessments.
No, IB Lab LAMA is designed as a diagnostic support tool to assist healthcare professionals, not to replace their clinical expertise. Physicians remain essential for comprehensive patient evaluation, making the final diagnosis, developing treatment plans, and interpreting the AI-generated reports within the broader clinical context.
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| Last Verified: 2026-04-18 | First Added: 2026-04-18