USPTO Patent Grant for Thermal Ablation Planning and Neural Network Training

ChangeBridge: Patent Grants - AI & Computing (G06N)

Published March 24th, 2026

Detected March 24th, 2026

Summary

The USPTO has granted patent US12582479B2 to Siemens Healthineers AG for a method and system for planning minimally invasive thermal ablation using neural network training. The patent covers a computer-implemented method that utilizes acquired object images and neural ordinary differential equations to output an ablation plan for guiding clinicians.

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What changed

The United States Patent and Trademark Office (USPTO) has issued patent US12582479B2 to Siemens Healthineers AG. This patent covers a novel computer-implemented method for planning minimally invasive thermal ablation procedures. The method involves acquiring object images within a biological body, determining object and external surface positions, and using a neural ordinary differential equation algorithm to generate an ablation plan. This plan includes the type and trajectory of needles required for ablating the target object, providing guidance to clinicians.

This patent grant signifies a new technological advancement in medical procedures, particularly in the use of AI for surgical planning. While not a regulatory rule imposing new obligations, it represents a development that may influence future medical device regulations and standards. Companies in the medical device and healthcare technology sectors, especially those involved in AI-driven surgical planning or thermal ablation, should be aware of this patented technology as it could impact their own research, development, and product strategies. No immediate compliance actions are required for regulated entities based solely on this patent grant.

Source document (simplified)

← USPTO Patent Grants

Method and system for automatic planning of a minimally invasive thermal ablation and method for training a neural network

Grant US12582479B2 Kind: B2 Mar 24, 2026

Assignee

Siemens Healthineers AG

Inventors

Chloe Audigier, Tommaso Mansi

Abstract

A computer-implemented method for planning a thermal ablation of a target object within a biological body includes acquiring an object image within the body, determining an object position within the body from the image, determining external body surface position relative to the object position from the image, acquiring, for an initial set of ablation needles those of types for the ablation, and for each type, a set of characterizing features common to all needles of a same type, including a fixed and/or variable parameter. A neural ordinary differential equation algorithm receives a characterizing feature, external surface position, object position, algorithm for outputting an ablation plan, including a final set of needles for ablating the object, and for each needle of the final set, type, trajectory from the external surface, and optionally, a variable parameter value. The plan is provided through an interface to guide a clinician for object ablation.

CPC Classifications

A61B 34/10 A61B 90/36 A61B 2018/00577 A61B 2034/107 A61B 2090/364 A61B 34/25 A61B 6/032 A61B 6/5217 A61B 18/1477 A61B 2018/0016 A61B 2018/1467 A61B 2018/1475 A61B 2034/254 A61B 2090/365 A61B 2090/3762 A61B 2576/00 A61B 2034/104 A61B 18/12 A61B 18/1402 A61B 34/20 A61B 2018/00529 A61B 2018/00595 A61B 2018/1425 A61B 2034/108 A61B 2034/2065 G06N 3/045 G06N 3/09 G06N 3/04 G06N 3/08