RUS

by Hutom  · Based in South Korea →Redefining Surgical Standards with AI-Powered 3D Visualization
Cardiothoracic Surgery General Surgery Neurosurgery

Contact for pricing
Regulatory Status Disclosed

Overview

Hutom’s RUS (Reshaping and Unraveling Surgery) is a revolutionary AI-powered surgical navigation platform designed to enhance precision and safety in complex surgical procedures. It is a core component of Hutom’s broader AI Surgical Platform, which offers a comprehensive solution for preoperative rehearsal, intraoperative navigation, and post-operative analysis.

RUS leverages advanced AI-based 3D reconstruction technology to transform conventional 2D CT images into highly detailed, patient-specific 3D anatomical models. This allows surgeons to visualize critical structures, simulate surgical procedures, and plan optimal approaches before entering the operating room.

The platform includes specialized solutions such as RUS GA for gastric surgery, RUS NE for kidney surgery (partial nephrectomy), and RUS LUNG for thoracic surgery, each tailored to provide intelligent 3D mapping and visualization for specific anatomical challenges. RUS has received recognition for its intuitive user interface and user experience, which mirrors real-life surgical workflows to facilitate adaptation and provide critical information effectively during surgeries.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Real-time 3D visualization system
  • AI-based 3D reconstruction from CT images
  • Patient-specific 3D anatomical models
  • Virtual tumor resection simulation
  • Surgical simulation for optimal port placement
  • Preoperative rehearsal capabilities
  • Intraoperative navigation assistance
  • Post-operative analysis and review
  • Intuitive UI & UX mirroring surgical workflows
  • Light & Dark Modes for reduced eye strain

Use Cases

  • Revolutionizing gastrectomy with advanced 3D visualization (RUS GA)
  • Redefining partial nephrectomy with intelligent 3D mapping (RUS NE)
  • Enhancing safety and precision in thoracic surgery (RUS LUNG)
  • Personalized surgical planning and simulation
  • Surgical video data analysis and review
  • Improving overall surgical precision and patient safety

What Physicians Need to Know

Surgical Planning Capabilities
RUS automatically reconstructs 2D CT angiography images into a 3D model, enabling surgeons to simulate surgery and identify potential anatomical challenges pre-operatively. It provides patient-specific 3D virtual anatomy and surgical instrumental models for comprehensive preoperative planning and anatomy simulation.
Intraoperative Guidance
The system offers intraoperative anatomy navigation by integrating 3D virtual anatomical models with the surgeon's console, providing manipulable virtual anatomy during surgery. It enhances anatomical visualization, particularly for complex structures like regional calyces and intrarenal vessel branches, and helps visualize invisible and deep-seated anatomy.
3D Reconstruction Quality
RUS successfully implements patient-specific 3D anatomy reconstruction from preoperative CT scans without issues. In studies, all vessels encountered during gastric cancer surgery were successfully reconstructed, with vascular origins and variations identical to operative findings.
Robotic Surgery Integration
RUS is a virtual surgical navigation system specifically designed for use during robot-assisted procedures, such as partial nephrectomy. It integrates seamlessly with the surgeon's console (e.g., via TilePro) to provide enhanced anatomical information.
Surgical Navigation Accuracy
The system demonstrates high accuracy, with the anatomy of blood vessels identified by RUS being identical to actual intraoperative findings for vascular origins and variations. It provides accurate anatomical visualization to support precise surgical navigation.
Pre-Operative Assessment
RUS facilitates rapid, noninvasive 3D imaging for surgical and trauma assessment, delivering near-immediate 3D outputs. This capability enables earlier operative planning and helps in the identification of critical anatomical structures before surgery.
Operating Room Workflow Integration
The RUS navigation system is designed for smooth integration into the surgical workflow without technical issues. AI-powered modules, including those for surgical planning and guidance, aim to streamline OR operations by providing real-time visibility and predictive analytics, complementing existing hospital infrastructure.
Physician Tip

Leverage RUS for complex cases requiring detailed anatomical understanding and precise planning, especially in robotic-assisted surgeries. Utilize its 3D reconstruction and simulation features to virtually rehearse procedures and anticipate anatomical variations, which can significantly enhance surgical confidence and potentially reduce operative time and complications. Integrate the real-time intraoperative guidance to navigate challenging anatomies and confirm critical structures. While RUS excels in planning and guidance, consider complementary AI tools for comprehensive pre-operative risk assessment and post-operative monitoring to ensure holistic patient care.

RUS is designed to integrate with existing surgical platforms, such as robotic surgery consoles (e.g., via TilePro), to provide a virtual surgical environment. Its ability to process CT angiography DICOM files for 3D reconstruction indicates compatibility with standard medical imaging systems. Successful integration into the operating room workflow is a key aspect of its design, aiming to complement current processes with real-time insights and predictive analytics.

Details

Category Surgical AI
Pricing Contact for pricing
DeploymentSoftware (likely cloud-based or on-premise for hospital systems)
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

Hutom's RUS received 510(k) clearance from the U.S. Food and Drug Administration (FDA) on July 12, 2024, under submission number K233457. The software is intended to assist trained medical professionals in evaluating patient anatomy and creating 3D models from medical images for surgical planning.

Integrations
EHR Not specified
Specialties Cardiothoracic Surgery, General Surgery, Neurosurgery

What the Web Says

RUS, part of Hutom's AI Surgical Platform, is a surgical planning and navigation system that converts 2D CT images into 3D models for pre-operative simulation and intra-operative guidance. It aims to improve surgical outcomes by providing surgeons with a better understanding of patient-specific anatomy, particularly in minimally invasive procedures. The platform has received domestic class II device approval in South Korea and has been the subject of an observational study showing comparable short-term outcomes to traditional methods.

Overall: Positive

Strengths

  • Transforms 2D CT images into 3D anatomical models for detailed pre-surgical planning.
  • Enables surgical simulation to identify potential anatomical challenges before an operation.
  • Provides intra-operative navigation with a 3D endoscope view, mirroring the actual surgical field.
  • Aids in personalizing and standardizing operations by identifying critical anatomical structures.
  • Potentially helps to bridge the experience gap between expert and novice surgeons.
  • Supports both robotic and laparoscopic surgeries.

Limitations

  • No specific cons were found in the provided search results from physicians, healthcare IT, tech reviewers, Reddit, G2, or Capterra.
  • Short-term outcomes in a study were comparable to control groups but without statistical significance, suggesting further research may be needed to definitively prove superior outcomes.

Based on reviews from: BioWorld, YouTube (Hutom Official Channel)

Last updated: 2026-07-20

Ratings & Reviews

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Press & Coverage

hutom.io
RUS Kidney Achieves PMDA Approval in Japan!
Hutom's RUS Kidney, an innovative surgical navigation software, has received approval from Japan's PMDA, marking its official recognition in the Japanese healthcare market for precise and safe partial nephrectomies.
2024-12
hutom.io
RUS Wins the 2024 Red Dot Design Award
Hutom's RUS has been honored with the Red Dot Design Award in the Design Concept | Interaction, UI, and User Experience category for its intuitive interface and user-centered design, enhancing surgical precision and patient safety.
2024-11
hutom.io
Exciting News from Hutom: FDA Clearance for 'RUS Stomach'!
Hutom announced that its 'RUS Stomach' platform received FDA clearance, further expanding the regulatory approvals for their AI-based surgical navigation tools.
2024-07
KBR
J&J MedTech and Hutom to co-promote AI-based surgical navigation platform
Johnson & Johnson MedTech Korea has partnered with Hutom to co-promote the RUS (Reshaping and Unraveling Surgery) platform, an AI-based surgical navigation system designed to assist surgeons in pre- and post-operative planning.
2024-05
BioWorld
Hutom to 'reshape, unravel surgery' with AI-surgical navigation
Hutom's 'Reshaping and Unraveling Surgery' (RUS) platform utilizes AI to reconstruct 2D images into 3D models, allowing surgeons to simulate procedures and improve pre-, intra-, and post-operative decisions.
2024-03
Frontiers
Patient-specific virtual three-dimensional surgical navigation for gastric cancer surgery: A prospective study for preoperative planning and intraoperative guidance
This study evaluates the feasibility of Hutom's RUSu2122 system, a virtual surgical navigation system providing patient-specific 3D vascular information and a pneumoperitoneum model, for robotic gastrectomy in gastric cancer patients.
2023-02
ClinicalTrials.gov
A Multicenter Study of RUS NE
Hutom Corp. is sponsoring a randomized controlled clinical trial to demonstrate the clinical efficacy of the RUS NE Surgical Navigation System in patients undergoing robotic-assisted partial nephrectomy.
2025-09
Annals of Hepato-Biliary-Pancreatic Surgery
Deep learning-based surgical phase recognition in laparoscopic cholecystectomy
This peer-reviewed article discusses a deep learning model designed to automatically identify surgical phases in laparoscopic cholecystectomy videos, with videos annotated using Hutom's Video Annotation Tool.
2024-07

Videos

Product demos, reviews, and walkthroughs for RUS.

View all on YouTube

Frequently Asked Questions

Robotic Ultrasound Systems (RUS) can be integrated into surgical workflows by providing real-time, high-resolution imaging for critical intraoperative decisions, complementing surgical planning and navigation systems. This integration enhances surgical precision and confidence, supporting various specialties like neurosurgery, urology, and general surgery by offering dynamic visualization of anatomy.
Key challenges include the absence of specific regulations tailored for AI in healthcare robotics, ambiguity in liability for errors, and the need for robust frameworks to safeguard patient data. Regulatory bodies like the FDA and those governing EU MDR require adherence to quality management systems and risk analysis, but AI-specific validation and ethical considerations for algorithmic transparency are still evolving.
Alternatives to RUS for intraoperative imaging and guidance include traditional intraoperative ultrasound (IOUS), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). IOUS offers real-time, non-invasive, and cost-effective imaging, while CT and MRI provide high spatial resolution and versatility, though CT involves radiation exposure and MRI has spatial constraints for robotic integration.
The initial investment for a robotic-assisted surgical system, which may include advanced imaging like RUS, can range from $2.0 to $2.5 million, with annual maintenance costs exceeding $100,000. Significant ongoing expenses also come from specialized instruments and accessories, which can cost thousands per procedure. Calculating ROI requires a comprehensive analysis of acquisition, integration, maintenance, and potential savings from improved patient outcomes and operational efficiency.
Current limitations of RUS include challenges in achieving full autonomy, potential dependency on other imaging modalities for comprehensive navigation, and issues with diagnostic variability and reproducibility. There is also a scarcity of high-quality medical data needed to robustly train AI algorithms for complex real-time decision-making. Patient acceptance of robotic systems in healthcare can also be a factor.
Robotic Ultrasound Systems address data privacy and cybersecurity through multi-layered defense strategies, including encryption of patient data both in transit and at rest, and robust access controls. However, vulnerabilities can exist, and standard deletion methods may not fully remove patient data from devices, necessitating careful data management and regular security updates to prevent unauthorized access or manipulation.
Specialized training for RUS typically involves a combination of theoretical instruction, hands-on practice using simulators, and dry labs to master basic robotic skills. Comprehensive team training is crucial to ensure effective communication, coordination, and proficiency in system setup, troubleshooting, and emergency protocols. Continuous education and proctored experience are also essential for maintaining competence as technology evolves.

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