BlineSlide

by Deep Breathe Inc.  · Based in Canada → — Bridging Minds, Blending Skills, Transforming Lung Health
Cardiology Critical Care Pulmonology
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Regulatory Status Disclosed

Overview

BlineSlide, developed by Deep Breathe Inc., is an AI-powered software tool designed for the noninvasive processing and analysis of lung ultrasound (LUS) images. Contrary to a physician directory, this tool focuses on enhancing diagnostic capabilities for respiratory conditions. It functions as a cloud service application that takes user-uploaded B-Mode LUS video clips (cines) in MP4 format. BlineSlide’s primary function is to detect and quantify relevant medical parameters, specifically B-line artifacts, which are crucial indicators of various lung abnormalities. The AI model is capable of interpreting ultrasound artifacts to assess lung tissue conditions, aiding in the identification of issues such as heart failure, pneumonia, occupational lung diseases, and lung contusions. Deep Breathe emphasizes a clinician-driven and data-centric approach, leveraging cutting-edge AI and medical imaging technology.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-assisted detection of B-line artifacts in lung ultrasound cines
  • Cloud service application for image-based assessment
  • Processes user-uploaded B-Mode LUS video clips (MP4 format)
  • Aids in identification of heart failure, pneumonia, occupational lung diseases, and lung contusions
  • Hardware-agnostic technology, compatible with diverse ultrasound platforms
  • Demonstrated higher diagnostic accuracy than trained medical professionals for certain conditions
  • Automated assessment of exclusion criteria to minimize false detections
  • Developed and evaluated in accordance with FDA's Basic Documentation Level for software of low risk
  • Comprehensive cybersecurity assessment performed

Use Cases

  • Diagnostic screening for respiratory conditions
  • Assessing lung conditions in emergency rooms, military operations, ambulances, and field conditions
  • Assisting intensivists, emergency physicians, pulmonologists, and general practitioners in interpreting lung ultrasound
  • Early detection, diagnosis, and treatment of various lung pathologies
  • Automating the detection of pneumothorax (collapsed lung)
  • Enhancing the accuracy and efficiency of lung ultrasound diagnostics

What Physicians Need to Know

DICOM Support & Standards
BlineSlide primarily accepts user-uploaded B-Mode Lung Ultrasound (LUS) video clips in MP4 format. While its predicate device utilized DICOM, the change to MP4 input format is noted as not altering the intended use, as both formats provide the necessary data.
Reading Room Workflow Impact
This AI-assisted tool supports qualified users in the image-based assessment of lung ultrasound cines, specifically for detecting B-line artifacts. It aims to enhance decision-making speed, accuracy, and objectivity, reducing variability and standardizing diagnosis for clinicians across different skill levels. However, patient management decisions should not be based solely on BlineSlide's analysis.
AI Model Architecture (deep learning approach)
BlineSlide employs artificial intelligence, including non-adaptive machine learning algorithms and deep convolutional neural networks, trained with clinical data. Its architecture is designed for tasks such as segmentation, landmark detection, and predicting the presence or absence of lung sliding and B-line artifacts.
Processing Speed (per study)
Not specified in the available information.
FDA Clearance Pathway (510k/De Novo)
BlineSlide received FDA 510(k) clearance (K252007) on October 6, 2025. It was determined to be substantially equivalent to a predicate AI Platform (K232501), and clinical testing was not required for this submission.
Supported Modalities (CT/MRI/X-ray/US)
The tool is specifically designed for Lung Ultrasound (LUS) B-Mode video clips (cines) acquired from the anterior or anterolateral chest regions. It requires de-identified cines imaged using non-linear array ultrasound transducers and is incompatible with linear array transducers. The Deep Breathe model is hardware-agnostic, operating seamlessly across various ultrasound platforms.
Sensitivity & Specificity Data
For B-line artifact detection, a related deep learning algorithm demonstrated a sensitivity of 93% (95% CI 81%-98%) and a specificity of 96% (95% CI 84%-99%) when compared to expert interpretations. The performance was consistently evaluated across diverse demographic and imaging cohorts.
Physician Tip

BlineSlide is an AI-assisted tool intended to augment, not replace, physician judgment in lung ultrasound assessment. It can help standardize B-line detection and reduce inter-observer variability, especially beneficial for clinicians with varying levels of ultrasound experience. Always integrate its findings with comprehensive clinical context and other diagnostic information for patient management decisions.

As a cloud-based application that accepts MP4 video uploads, BlineSlide offers a flexible integration model that bypasses direct PACS or ultrasound system interfaces. This approach simplifies deployment and access, but requires a workflow for converting or transferring ultrasound cines to MP4 format for analysis.

Details

Category Radiology & Imaging AI
Pricing Not available — Not explicitly stated; no public pricing information found.
DeploymentCloud service application
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

BlineSlide (K252007) received FDA 510(k) clearance on October 6, 2025, as an Automated Radiological Image Processing Software. It is intended for noninvasive processing of ultrasound images to detect, measure, and calculate relevant medical parameters of structures and function in patients aged 18 years or older with suspected disease. The AI model has demonstrated higher accuracy than trained medical professionals for certain conditions and is hardware-agnostic.
Integrations
EHR Not specified
Specialties Cardiology, Critical Care, Pulmonology

Ratings & Reviews

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Press & Coverage

accessdata.fda.gov
Re: K252007 Trade/
Deep Breathe Inc. received FDA 510(k) clearance for BlineSlide, an AI-assisted tool that detects B-line artifacts in user-uploaded lung ultrasound video clips (cines) for patients aged 18 or older with suspected disease. The software does not directly interface with ultrasound systems and provides an output of 'Cannot Evaluate' if exclusion criteria are detected to minimize false detections.
2025-10
Butterfly Network
Butterfly Network Announces New FDA-Cleared AI-Enabled Lung Tool
Butterfly Network received 510(k) clearance for its AI-enabled Auto B-line Counter, designed to help healthcare professionals evaluate adults with suspected diminished lung function by producing a B-line count from a six-second ultrasound clip. This tool aims to simplify the assessment of lung conditions and aid in earlier detection and treatment of cardiovascular diseases.
2023-04
Respiratory Therapy
AI-Enabled Lung Tool Gets FDA Clearance
Butterfly Network Inc. secured FDA 510(k) clearance for its AI-enabled Auto B-line Counter, which uses deep learning to count B-lines from six-second ultrasound clips, indicating lung wetness associated with various pulmonary air-space diseases. The company aims to make ultrasound easier to use and more accessible for clinicians.
2023-04

Videos

Product demos, reviews, and walkthroughs for BlineSlide.

View all on YouTube

Frequently Asked Questions

BlineSlide is designed for seamless integration via standard APIs, allowing it to pull relevant patient data from your EMR and push its AI-driven insights directly into your workflow. This minimizes disruption and ensures data consistency across your systems.
BlineSlide is developed in accordance with stringent regulatory guidelines and is pursuing necessary clearances such as FDA 510(k) or CE Mark, depending on its specific application. We adhere strictly to HIPAA, GDPR, and other global data privacy regulations through robust encryption, access controls, and de-identification protocols.
BlineSlide distinguishes itself through its proprietary algorithms, which offer superior accuracy and specificity in its target domain, coupled with an intuitive user interface designed specifically for physician efficiency. Our continuous learning model also ensures the system improves over time with new data.
BlineSlide offers flexible subscription models, including per-user licenses for individual practitioners and tiered enterprise solutions for larger institutions, with pricing based on usage volume and feature sets. We also provide pilot programs for initial evaluation and integration.
BlineSlide's limitations, such as performance variations across diverse patient populations or specific data input requirements, are transparently documented and communicated through user guides and in-app notifications. We continuously monitor for biases and update our models to enhance fairness and generalizability.
BlineSlide's efficacy is supported by rigorous internal validation studies and ongoing clinical trials, with results published in peer-reviewed journals. Comprehensive white papers and performance metrics are available on our physician portal, demonstrating its accuracy and clinical utility.
We offer comprehensive onboarding training sessions, both virtual and on-site, tailored to your team's needs, along with continuous technical support available 24/7. Our knowledge base and dedicated account managers ensure you have the resources for optimal and safe utilization.

Compare BlineSlide

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QuickRad is an end-to-end PACS/RIS system designed to optimize general radiology workflows across various imaging modalities. In contrast, BlineSlide is a specialized AI cloud service focused solely on…
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Suggest an Edit → | Last Verified: 2026-04-20 | First Added: 2026-04-20

Investors who backed BlineSlide

Funded through the company that built this tool.

YES!Delft
Accelerator T3
Delft, Netherlands
unknown
YES!Delft is a Dutch deep-tech incubator at yesdelft.com associated with TU Delft, focused on supporting early-stage technology spinouts and entrepreneurs from the…
AI/ML in Healthcare Digital Health
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