Redefining the path to
treatment for lung patients
Lung cancer is a prominent malignancy posing a significant threat to individuals in China and other nations alike1. Timely diagnosis plays a pivotal role in achieving the most favorable prognosis. The detection of lung nodules presents challenges due to their diverse characteristics in terms of size, location, and appearance2. Moreover, the identification of numerous false positive nodules remains an urgent issue that needs resolution during clinical CT examinations and LDCT screenings. Excessive false positives can result in overdiagnosis, overtreatment, wastage of medical resources, and heightened patient anxiety3.

The objective of BINARY is to expedite the diagnostic process for patients by facilitating access to hard-to-reach nodules within the surrounding lung tissue for biopsy purposes. BINARY aims to assist both patients and physicians in obtaining prompt results along the pathway towards diagnosing lung nodules.
How BINARY works
Our journey from planning to completing lung surgery begins with the integration of BINARY's IPGM robot and specialized tools, enabling precise path planning and navigation towards the lung lesions. This process is facilitated by the comprehensive analysis of the patient's CT scans and other relevant imaging data. Through meticulous calculation and analysis, the optimal surgical trajectory is delineated in reverse, ensuring precise guidance during the surgical procedure.

When you're ready, the immersive teleoperation control outside the operating room allows the physicians to watch and control the operation of the surgical robot in real time through virtual reality technology in the operating room. Physicians can be immersed in a three-dimensional surgical environment, through the operation of the control terminal to precisely control the robot, surgical operations.
  • IPGM
    Interventional Planning
    Generation Module
    The use of IPGM can effectively decrease surgical duration, minimize surgical complications, and enhance surgical efficiency by implementing meticulous navigation planning.
  • ICNM
    Immersive Control
    and Navigation Module
    The navigation technology of ICNM employed encompasses reverse planning navigation and virtual reality navigation, in conjunction with a medical image processing assistance system, thereby enhancing surgical precision, efficiency, and safety.
  • EMTS
    Tracking System
    The EMTS is configured to acquire the position of the distal end of the bronchoscope within the EMTS coordinate system, facilitating the teleoperation to guide the tip of the bronchoscope to the target location and posture. In additional, the EMTS coordinate system is registered with the 3D bronchial model within the navigation cart, enabling the real-time tracking of the bronchoscope's distal end. This process maps the current position of the bronchoscope's distal end within the EMTS coordinate system onto the 3D bronchial model on the navigation cart.
  • SIEM
    Seed Implantation
    Execution Module
    The SIEM holds the endoscope traditionally held by surgical physicians, enabling the physician to remotely control the end handle for stable and precise maneuvering of the endoscope. This advanced technology allows for four-way rotation within the bronchus, facilitating accurate targeting of nodules and other functionalities.
Navigate to target
BINARY integrates an electromagnetic sensor at the bronchoscope's tip to acquire real-time positional data within the patient's body. Leveraging the centerline algorithm, this data is utilized to offer intuitive and precise virtual navigation, ensuring precise access to the target area. During the operation, the 2D data from the endoscope image is harmonized with the 3D information from the optical fiber sensor, facilitating seamless synchronization of virtual navigation details.

BINARY's joystick incorporates a robust embedded control board, boasting versatile functionality and a programmable interface for seamless program burning. This feature enables redevelopment to suit a broader spectrum of application scenarios, enhancing adaptability and versatility.
Start planing your procedure
The IPGM navigation preview interface provides a visually clear observation of the planned spatial relationship for each precise position within the lung. The IPGM surgery planning software enables visual processing and analysis of CT images, including three-directional visualization, multi-organ segmentation, three-dimensional digital human body representation, manual creation of targets and puncture paths.

By utilizing the visual three-dimensional airway tree generated from a patient's lung CT scan, physicians can conduct surgical planning and path preview to proactively understand potential surgical difficulties and mitigate risks while providing more accurate surgical plans.
  • Contact target
    Once the target focus has been navigated and reached, BINARY's advanced image processing technology and algorithms can perform manual or automatic registration of the main branch of the lung. This process is designed to mitigate interference caused by the patient's breathing movements and variations in the position and angle of the bronchoscope, ensuring precise and uninterrupted surgical visualization.
  • When segmentating precise lung bronchus, BINARY uses FR module to integrate 3D coordinate space information to achieve re-calibration of channel features. By simulating high resolution attention and correcting low resolution attention, the learning ability of tubular objects is enhanced. Lung Tracheal Segmentation Network (LTSC-Net) was used to segment lung lobes from CT images.
  • The CT image-based modeling algorithm for lung trachea and lung lobe segmentation achieves a comprehensive 6-level tracheal modeling, resulting in impressive Dice coefficients of 95.6% and 98% respectively. Additionally, our internally developed AI algorithm for lung nodule recognition in CT images utilizes a multitask subnetwork comprising classification and frame regression, delivering accurate predictions with a sensitivity of 88.5%. These advancements provide intelligent guidance for bronchoscopic interventional surgery, enhancing precision and efficacy in clinical practice.
Treat the lesion
BINARY's SIEM robot features an endoscopic delivery mechanism capable of omnidirectional steering, enabling movement in all directions including forward and backward. Upon reaching the pulmonary nodule, it precisely controls the endoscope to target and lock onto the pulmonary nodule. This is achieved through the integration of real-time position and attitude measurement with sophisticated robot control algorithms, ensuring accurate and stable navigation during the procedure.
  • BINARY is distinguished by its integration of multiple magnetic navigation sensors, high-brightness white light source, and high-definition camera into a slender 3.5-millimeter insert tube, accompanied by a spacious 2-millimeter inner diameter working channel. With the capability for 180° bending and rotation in any direction, it enables seamless propulsion, steering, and locking maneuvers. Upon reaching the target area, BINARY's end-locking function activates, ensuring precise penetration of the puncture needle into target nodules and diseased tissues at the desired distance and angle.
Endoscope Assembly Steps
  • Steps 1
  • Steps 2
  • Steps 3
  • Steps 4
  • Steps 5
Instruments and accessories
3.5mm outer diameter
2mm working channel
Bending part of the Four-Way rotation
Hanglok develops a generalized distributed system architecture for medical robots in interventional radiology area, named as REMIND.
With comprehensive interfaces and services, REMIND empowers the R&D of BINARY,
such as Exception Handling Interface, Advance Function Interface, Communication Service,
Computing Intensive Service, etc.
  1. J. F. ME, R. L. Siegel, M. Isabelle Soerjomataram, and D. Ahmedin Jemal, “Global cancer statistics 2022: Globocan estimates of incidence and mortality worldwide for 36 cancers in 185 countries,” CA: A Cancer Journal for Clinicians, 2024, in press, DOI: 10.3322/caac.21834.
  2. Zhou, Qinghua et al. Zhongguo fei ai za zhi = Chinese journal of lung cancer vol. 19,12 (2016): 793-798. doi:10.3779/j.issn.1009-3419.2016.12.12
  3. Bach, Peter B et al. “Benefits and harms of CT screening for lung cancer: a systematic review.” JAMA vol. 307,22 (2012): 2418-29. doi:10.1001/jama.2012.5521
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