DeepCT

by Deep01 Limited  · Based in Taiwan → — World-Leading AI-Powered Detection System for Head CT
Emergency Medicine Neurology Radiology
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Regulatory Status Disclosed

Overview

DeepCT by Deep01 Limited is an artificial intelligence-based software designed for the rapid triage and notification of suspected intracranial hemorrhage (ICH) cases from non-contrast CT (NCCT) scans of the brain. This AI tool analyzes head CT images to detect and quantify abnormal lesions, including ICH, midline shift, acute stroke, TBI, and fractures. By prioritizing suspected ICH cases and sending alarms to clinicians, DeepCT aims to expedite workflow in emergency departments and assist physicians in making critical decisions faster, ultimately optimizing patient outcomes and reducing inpatient length of stay.

The system integrates into standard reading environments (PACS), can function as a stand-alone third-party application, or be web-based. It supports cloud-based, hybrid, and local deployment on dedicated hardware. DeepCT processes images within 10-60 seconds, generating analysis reports with an accuracy rate of 95%. Deep01 Limited is recognized as the first AI company in the world to obtain both U.S. and Taiwan FDA clearances for its deep learning technology.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Detection of intracranial hemorrhage (ICH)
  • Notification to clinicians for suspected findings
  • Segmentation and quantification of ICH
  • Worklist prioritization for time-sensitive cases
  • Detection of midline shift
  • Detection of acute stroke
  • Detection of traumatic brain injury (TBI)
  • Detection of fractures
  • Automated analysis reports
  • High accuracy rate (95%)

Use Cases

  • Triaging suspected intracranial hemorrhage cases in emergency settings
  • Expediting workflow in emergency departments and radiology
  • Assisting physicians in making critical decisions faster
  • Reducing inpatient length of stay for ICH patients
  • Prioritizing time-sensitive and life-threatening cases
  • Providing a 'second opinion' for radiologists and ER physicians

What Physicians Need to Know

Evidence Base
Deep learning models in radiology, such as those integrated into platforms like deepcOS, are trained on extensive datasets of medical images. The deepcOS platform itself orchestrates and integrates various AI solutions, each with its own underlying evidence base and validation.
Clinical Validation Studies
Multiple studies demonstrate clinical validation of deep learning in CT applications. Examples include accurate differentiation of benign and malignant vertebral fractures on CT (achieving 88% per-patient accuracy), successful generation of synthetic CT images comparable to real CTs, high diagnostic accuracy for classifying non-contrast brain CT reports, and near-perfect inter-rater agreement for detecting high-grade metastatic epidural spinal cord compression with potential to reduce diagnostic delays.
Alert Fatigue Management
While specific alert fatigue management features for 'DeepCT' (deepcOS) are not explicitly detailed, the platform's focus on seamless workflow integration and providing urgency flags in worklists could indirectly help manage alert perception. General strategies for alert fatigue in healthcare include improving interface design, personalizing alerts, and reducing clinically inconsequential warnings.
Override Rate Data
No specific override rate data for 'DeepCT' or deepcOS was found in the provided information. General literature on clinical decision support (CDS) systems indicates that clinicians often override a significant majority of warnings, even critical ones, a phenomenon attributed to alert fatigue.
Differential Diagnosis Support
Deep learning has been applied to specific differential diagnosis tasks in imaging, such as distinguishing benign from malignant vertebral fractures on CT. Clinical decision support systems, including AI-native tools, can generate differential diagnoses to help physicians consider a broader range of possibilities and combat cognitive biases. deepcOS can embed clinical findings from third-party AI vendors directly into the worklist.
Guideline Update Frequency
As deepcOS functions as a platform integrating various AI models, the update frequency for specific guidelines or algorithms would depend on the individual AI solutions it hosts. Generally, clinical guidelines are recommended to be updated every 2-5 years or when new evidence emerges that could alter clinical practice.
Clinical Workflow Integration
deepcOS is designed for seamless integration into existing radiology workflows, including Picture Archiving and Communication Systems (PACS), Radiology Information Systems (RIS), and Electronic Health Record (EHR) systems. It aims to eliminate the need for switching between multiple interfaces and integrates AI-generated findings directly into reporting workflows to reduce reporting times and improve accuracy. It supports various integration options such as DICOM PDF, DICOM SR, DICOM SC, DICOM GSPS, and API integrations.
Decision Audit Trail
While the importance of audit trails for accountability and transparency in AI systems is recognized, specific details on a 'Decision Audit Trail' for 'DeepCT' (deepcOS) were not explicitly found. General audit trails in healthcare track access, reviews, and changes to electronic medical records, providing a chronological, tamper-evident record of events.
Physician Tip

Leverage DeepCT's integration capabilities to streamline imaging interpretation and reporting, reducing manual tasks and potentially improving diagnostic speed. Pay attention to AI-generated findings and urgency flags within your existing worklist to prioritize cases effectively. While AI offers valuable support, always apply your clinical judgment and correlate findings with the patient's full clinical picture. Be aware that the evidence base and update frequency may vary for different AI models integrated into the platform.

DeepCT, particularly through platforms like deepcOS, emphasizes 'quiet integrations' with existing healthcare IT systems such as PACS, RIS, and EHRs. This aims to embed AI insights directly into the radiologist's workflow without requiring new portals or significant workflow changes. Integration options include various DICOM standards and APIs, facilitating the consumption and display of AI output data natively within downstream systems.

Details

Category Neurology AI, Radiology & Imaging AI, Triage & ER/ICU AI
Pricing Contact for details — Not disclosed
DeploymentCloud-based, Hybrid solution, Locally on dedicated hardware, Integration in standard reading environment (PACS), Stand-alone third party application, Stand-alone web-based
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

DeepCT obtained US FDA 510(k) clearance (K182875) on July 10, 2019, as a Class II radiological computer aided triage and notification software. It is a notification-only, parallel workflow tool for identifying suspected intracranial hemorrhage (ICH) cases from non-contrast CT images of the brain.
Integrations
EHR Not specified
Specialties Emergency Medicine, Neurology, Radiology

What the Web Says

DeepCT by Deep01 is an AI-powered diagnostic tool designed to assist physicians in interpreting CT scans, particularly for identifying acute intracranial hemorrhages. Reviews suggest it aims to improve diagnostic accuracy and speed, potentially reducing physician workload and improving patient outcomes in emergency settings.

Overall: Positive

Strengths

  • Aids in rapid detection of acute intracranial hemorrhage, crucial for time-sensitive conditions.
  • Potentially reduces diagnostic errors and improves accuracy, especially for less experienced physicians.
  • Can decrease the workload on radiologists and emergency physicians, allowing more focus on complex cases.
  • Integrates with existing PACS systems, making adoption potentially smoother.
  • May lead to faster treatment initiation due to quicker diagnosis.
  • Potential for use in remote or underserved areas where specialist radiologists are scarce.

Limitations

  • Reliance on AI may lead to over-reliance and deskilling among physicians over time.
  • Concerns about 'black box' nature of AI and lack of transparency in its decision-making process.
  • Potential for false positives or false negatives, requiring careful human oversight.
  • Integration challenges and IT infrastructure requirements in some healthcare settings.
  • Cost of implementation and ongoing maintenance might be a barrier for smaller institutions.
  • Regulatory hurdles and ongoing validation studies are necessary for broader adoption and trust.

Based on reviews from: Deep01 Website, Healthcare IT News, Radiology Today, Medical journals (e.g., European Radiology, American Journal of Neuroradiology), Physician forums (general discussions, not specific platforms like Reddit/G2/Capterra for this niche product), Tech review sites (general AI in healthcare discussions)

Last updated: 2026-07-18

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Press & Coverage

Imaging Technology News
Deep01 Cuts ICH Patients' LOS in the Emergency Department by 3.67 Hours
A clinical trial at Kaohsiung Veterans General Hospital in Taiwan demonstrated that DeepCT shortened the length of stay for intracranial hemorrhage (ICH) patients in the emergency department by an average of 3 hours and 40 minutes. The study, involving 2,999 patients, showed the AI system's effectiveness in accelerating patient flow and improving treatment procedures.
2022-07
Neurosurgical.TV
Taiwan-based company develops AI-based medical imaging software to help physicians diagnose bleeding around the brain.
Deep01, a Taiwan-based medical imaging startup, developed DeepCT, an AI-based software for evaluating acute intracerebral hemorrhage (ICH) with 95% accuracy in 30 seconds. The company is the first AI company in Asia to receive FDA clearances in both the U.S. and Taiwan.
2021-05
Imsight
DeepCT: the first AI-based software filed to MDCO
DeepCT, an AI-based medical imaging software for diagnosing brain bleeding, was filed and listed with the Medical Device Control Office (MDCO) in Hong Kong in September 2021. This marks it as one of the first AI-based software solutions for aid diagnosis to be registered in the region.
2021-09
Hospital Authority - IT Innovation Office
DeepCT - Hospital Authority - IT Innovation Office
DeepCT, developed by Imsight Technology Co., Limited, is an AI-powered diagnostic tool that analyzes non-contrast CT brain images to identify suspected intracranial hemorrhage and notify specialists for review.
2021-05
ResearchGate
Pilot Report for Intracranial Hemorrhage Detection with Deep Learning Implanted Head Computed Tomography Images at Emergency Department
This pilot clinical trial, published in the Journal of Medical Systems, investigated the implementation of the DeepCT system for intracranial hemorrhage detection in an emergency department. The study concluded that DeepCT significantly shortened the length of stay for ICH patients and improved the quality of care.
2022-06
Molecular Pharmaceutics - ACS Publications
DeepCt: Predicting Pharmacokinetic Concentrationu2013Time Curves and Compartmental Models from Chemical Structure Using Deep Learning
This peer-reviewed article introduces DeepCt, a novel deep learning approach for predicting pharmacokinetic concentration-time curves and compartmental models directly from chemical structures. The methodology aims to reduce animal studies and accelerate drug discovery by providing early estimations of compound pharmacokinetics.
2024-11
GigaScience
Cell typeu2013specific interpretation of noncoding variants using deep learningu2013based methods
This research article presents a new neural network architecture, also named DeepCT, designed to interpret noncoding genomic variants by learning complex interconnections of epigenetic features and inferring unmeasured data. The model can learn cell type-specific properties and generate predictions for the effects of noncoding variations.
2023-03
British Journal of Radiology
Artificial intelligence in neuroradiology: a review of Food and Drug Administration-regulated algorithms
This review article discusses FDA-cleared AI algorithms in neuroradiology, including DeepCT by Deep01 (Taiwan), which is listed for the detection and flagging of intracranial hemorrhage on CT scans, with its clearance date noted as July 10, 2019.
2026-05

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Frequently Asked Questions

DeepCT is an AI-powered software designed to triage suspected intracranial hemorrhage (ICH) cases from non-contrast CT scans. It helps prioritize urgent cases, detects and quantifies ICH, and sends alarms to clinicians, thereby expediting workflow and supporting faster critical decisions in emergency settings.
DeepCT has received CE Certification as a Class I medical device under the Medical Device Directive (MDD) and is FDA 510(k) cleared as a Class II medical device. These certifications indicate that the software meets recognized safety and performance standards for medical devices in the European Union and the United States.
DeepCT can integrate into standard reading environments such as Picture Archiving and Communication Systems (PACS), or it can operate as a standalone application. It processes non-contrast head CT scans from adults, flagging suspected findings and generating annotated images, typically within 10 to 60 seconds to support rapid clinical assessment.
While AI tools like DeepCT enhance efficiency, physicians should be aware of general AI limitations, including the potential for diagnostic errors or subtle misinterpretations of data. Over-reliance on AI output without critical human evaluation can also lead to automation bias, underscoring the need for physician oversight.
Yes, the field of AI in medical imaging is evolving, with several AI medical diagnostic platforms offering various functionalities, including triage and workflow orchestration for critical findings like ICH. While specific direct competitors to DeepCT for ICH triage were not detailed, other AI solutions exist for radiology departments to aid in image analysis and diagnostic support.
The specific pricing model for DeepCT is not publicly specified in the available information. Generally, AI software in healthcare can be priced based on factors such as per-study fees, subscription models, or enterprise licenses, often influenced by the volume of scans, the scope of integration, and the size of the healthcare institution.

Compare DeepCT

VS
DeepCT vs HealthPNX
Clinical Decision Support & Reference Adjacent · 65/100
DeepCT and HealthPNX are adjacent healthcare-AI tools, both providing FDA-cleared clinical decision support to enhance radiology workflows and patient outcomes. DeepCT specializes in detecting intracranial hemorrhage and other…
VS
DeepCT vs Viz SDH
Clinical Decision Support & Reference Direct · 80/100
These two tools are direct competitors for the detection and triage of intracranial hemorrhage from non-contrast CT scans. DeepCT offers a broader scope, including detection of acute stroke,…
VS
DeepCT vs ContaCT
Clinical Decision Support & Reference Direct · 80/100
DeepCT specializes in the rapid detection and triage of intracranial hemorrhage and other brain abnormalities from CT scans, focusing on image analysis and prioritization. ContaCT, while also offering…
VS
DeepCT vs Viz CTP
Clinical Decision Support & Reference Adjacent · 75/100
DeepCT is a specialized AI software focused on the rapid detection and triage of intracranial hemorrhage and other brain abnormalities from non-contrast CT scans. Viz CTP offers a…

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Suggest an Edit → | Last Verified: 2026-04-18 | First Added: 2026-04-18
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