Advanced Force-Sensed Surface Scanning for Personalized Surgical Planning

Publication ID: 24-11857379_0010_PTD

Published: October 28, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Advanced Force-Sensed Surface Scanning for Personalized Surgical Planning,” Published Technical Disclosure No. 24-11857379_0010_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857379_0010_PTD

This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,379.

Summary of the Inventive Concept

A next-generation surface scanning system integrating real-time biomechanical modeling, machine learning-based surface reconstruction, and personalized surgical planning for enhanced accuracy and patient-specific care.

Background and Problem Solved

The original patent, 'Force sensed surface scanning systems, devices, controllers and methods,' provided a foundational approach to surface scanning for anatomical organs. However, it had limitations in terms of real-time data processing, biomechanical modeling, and personalized surgical planning. The new inventive concept addresses these limitations by incorporating advanced technologies to provide a more accurate, efficient, and patient-centric solution.

Detailed Description of the Inventive Concept

The advanced force-sensed surface scanning system comprises a robotic system integrated with a real-time biomechanical modeling module, a surface scanning controller, and a machine learning-based surface reconstruction algorithm. The system acquires real-time force sensing data and generates a personalized, patient-specific surface deformation offset profile based on the biomechanical modeling and real-time force sensing data. The surface scanning controller then uses this profile to generate a high-resolution, 3D surface map of the anatomical organ. Additionally, the system enables real-time tracking of anatomical organ deformation and fusion of preoperative imaging and intraoperative surface scanning data using deep learning-based registration algorithms.

Novelty and Inventive Step

The new claims introduce several novel and non-obvious elements, including the integration of real-time biomechanical modeling, machine learning-based surface reconstruction, and personalized surgical planning. These advancements enable a more accurate, efficient, and patient-centric surface scanning system that overcomes the limitations of the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include variations in the robotic system design, the use of different machine learning algorithms, or the integration of additional sensors or imaging modalities. These variations could enable the system to be adapted for use in different surgical specialties or for scanning different types of anatomical organs.

Potential Commercial Applications and Market

The advanced force-sensed surface scanning system has significant commercial potential in the medical device industry, particularly in the areas of surgical planning, navigation, and robotics. The system's ability to provide personalized, patient-specific care could lead to improved surgical outcomes, reduced complications, and enhanced patient satisfaction. Target industries include orthopedic, neurosurgical, and cardiovascular surgery.

CPC Classifications

Section	Class	Group
A	A61	A61B90/03
A	A61	A61B34/20
A	A61	A61B34/30
A	A61	A61B90/06
G	G06	G06T7/10
A	A61	A61B2034/2068
A	A61	A61B2090/065
A	A61	A61B2090/378
G	G06	G06T2207/10028
G	G06	G06T2207/30004

Section 103 Obviousness Analysis (PHOSITA)

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Field of Art

Medical imaging, robotic surgical systems, and biomechanical modeling, requiring advanced technical knowledge in medical robotics, computer vision, machine learning, and surgical navigation technologies

Person of Ordinary Skill (PHOSITA) Profile

A PhD-level engineer with expertise in medical robotics, computer vision, and machine learning, familiar with surgical navigation systems, force sensing technologies, and advanced imaging techniques

Obviousness Rationale

The PTD's variations represent predictable extensions of the source patent's core technology by integrating machine learning and advanced biomechanical modeling techniques that were known in the field of surgical surface scanning. A PHOSITA would recognize that applying machine learning algorithms to force sensing and surface reconstruction was a natural progression of existing robotic surgical scanning technologies. The proposed innovations represent incremental improvements using standard techniques available in the medical robotics domain.

Obvious Combinations & Variations

Source Patent Element

Surface scanning robot with force sensing end-effector for anatomical organ scanning

PTD Variation

Integration of real-time biomechanical modeling module with machine learning-based surface reconstruction algorithm

Obviousness Reasoning

Adding machine learning to existing force sensing systems was a predictable enhancement for improving scanning accuracy and precision, representing a known technique for improving robotic medical imaging

Source Patent Element

Surface scanning controller for defining surface deformation offset

PTD Variation

Generating personalized patient-specific surface deformation offset profile using biomechanical modeling

Obviousness Reasoning

Personalizing scanning algorithms using patient-specific data was an obvious extension of existing surface scanning technologies, representing a standard approach to improving medical imaging precision

Source Patent Element

Intraoperative volume model generation

PTD Variation

Deep learning-based registration of preoperative imaging and intraoperative scanning data

Obviousness Reasoning

Applying machine learning techniques to medical image registration was a well-known approach for improving surgical navigation accuracy, representing a predictable technological progression

Source Patent Element

Surface scanning of anatomical organs

PTD Variation

Real-time tracking of anatomical organ deformation using machine learning algorithms

Obviousness Reasoning

Implementing real-time deformation tracking was an obvious enhancement using standard machine learning techniques available in medical imaging technologies

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857379, the present technical disclosure demonstrates that the claimed innovations represent obvious variations to a person having ordinary skill in the art of medical robotic scanning technologies. The integration of machine learning, biomechanical modeling, and personalized scanning techniques would have been predictable and within the capabilities of an ordinarily skilled practitioner at the time of invention.

Original Patent Information

Patent Number	US 11,857,379
Title	Force sensed surface scanning systems, devices, controllers and methods
Assignee(s)	Koninklijke Philips N.V.