IP Library Granted Patent US 12,318,254
Granted Patent B2
US 12,318,254 · App. 18/014,837 · Granted Jun 3, 2025

Method and device for characterizing at least one object depicted in an ultrasound image

Inventors: Michael Friebe (Munich, DE); Nazila Esmaeili (Munich, DE); Elmer Jeto Gomes Ataide (Munich, DE); Prabal Poudel (Munich, DE); Alfredo Illanes (Munich, DE); Jens Ziegle (Munich, DE); Satish Balakrishnan (Munich, DE)
Assignee: Brainlab AG
A61B8/5207G06T7/0012G06T7/13G06V10/44G06V10/761G06T2207/10132G06T2207/30008
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Quick Facts
Patent No.
US 12,318,254
App. No.
18/014,837
Granted
Jun 3, 2025
Kind
B2
Abstract

Disclosed is a method and a device for characterizing, for example identifying at least one object depicted in a raster image ( 1 ) or determining the speed of sound of the object, the raster image ( 1 ) having pixel rows and pixel columns. In order to efficiently and accurately characterize the object, the invention provides that several pixel columns (Cn) are selected and each of the selected pixel columns (Cn) is converted into a line profile (L), the amplitude of the line profile (L) representing the value (V) of image information of selected pixels of the respective selected pixel column (Cn), wherein the method comprises determining characteristics of the line profiles (L) and using the characteristics to characterize the at least one object depicted in the raster image ( 1 ).

Claims (20)

1. A method for characterizing at least one object depicted in a raster image, the raster image being an ultrasound image having pixel rows and pixel columns,

wherein at least one pixel column is selected and the at least one pixel column selected is converted into a selected line profile, an amplitude of the selected line profile representing a value of image information of selected pixels of the at least one pixel column selected, and

wherein the method comprises:

determining characteristics of the selected line profile and using the characteristics to characterize the at least one object depicted in the raster image, wherein the characteristics of the selected line profile are values of the selected line profile indicating the position of an edge of the at least one object, among values of the selected line profile, with a greatest distance from a predetermined position and having a predetermined relationship to a threshold value; and

processing the selected line profile to form a processed line profile, the processed line profile having an enhanced signal to noise ratio compared to the respective selected line profile, wherein processing the selected line profile to form the processed line profile includes determining individual offset values for selected amplitudes of the selected line profile and subtracting the individual offset values from respective amplitudes prior to determining the characteristics of the selected line profile to create the processed line profile,

wherein the predetermined relationship includes zero crossings of the processed line profile.

2. The method of claim 1 , further comprising determining different aspects of the processed line profile by performing signal decomposition of the processed line profile.

3. The method of claim 1 , further comprising identifying boundaries of a plurality of different objects depicted in the raster image.

4. The method of claim 1 , wherein the raster image is a B-mode ultrasound image.

5. The method of claim 1 , wherein processing the selected line profile to form the processed line profile includes calculating the curvature of the selected line profile.

6. The method of claim 1 , further comprising decomposing the processed line profile into n-empirical modes, wherein n is one of 1, 2, 3, 4 or 5, to form a decomposed line profile.

7. The method of claim 6 , further comprising determining different frequency changes in time as a result from changes in structure at boundaries from the decomposed line profile by pole-tracking.

8. A non-transitory, computer-readable storage medium having stored thereon computer-executable instructions that, when executed by at least one processor, configure the at least one processor to carry out the method of claim 1 .

9. A medical system, comprising:

at least one computer having at least one processor; and

a medical ultrasound imaging device for carrying out ultrasound imaging on a patient,

wherein the at least one computer is operably coupled to the medical ultrasound imaging device for receiving a signal from the medical ultrasound imaging device corresponding to a raster image having pixel rows and pixel columns, wherein at least one pixel column is selected and the at least one pixel column selected is converted into a selected line profile, an amplitude of the selected line profile representing a value of image information of selected pixels of the at least one pixel column selected, the at least one processor being configured to:

determine characteristics of the selected line profile and using the characteristics to characterize the at least one object depicted in the raster image, wherein the characteristics of the selected line profile are values of the selected line profile indicating the position of an edge of the at least one object, among values of the selected line profile, with a greatest distance from a predetermined position and having a predetermined relationship to a threshold value; and

processing the selected line profile to form a processed line profile, the processed line profile having an enhanced signal to noise ratio compared to the selected line profile, wherein processing the selecting line profile to form the processed line profile includes determining individual offset values for selected amplitudes of the selected line profile and subtracting the individual offset values from respective amplitudes prior to determining the characteristics of the selected line profile to create the processed line profile,

wherein the predetermined relationship includes zero crossings of the processed line profile.

Assignments (2)
CHANGE OF NAME Recorded Feb 24, 2026
From: BRAINLAB AG
To: BRAINLAB SE
Reel/Frame 073875/0224 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 6, 2023
From: FRIEBE, MICHAEL; ESMAEILI, NAZILA; ATAIDE, ELMER JETO GOMES; POUDEL, PRABAL; ILLANES, ALFREDO; ZIEGLE, JENS; BALAKRISHNAN, SATISH
To: BRAINLAB AG
Reel/Frame 062310/0916 →
Priority Claims (2)
DE 10 2020 118 132.9 · Jul 9, 2020 · national
DE 10 2020 118 133.7 · Jul 9, 2020 · national
Continuity (1)
Related Publication 20230270414A1 · Aug 31, 2023
References Cited (9)
US 5528302A · Basoglu et al. · 1996 [cited by applicant]
US 20030199762A1 · Fritz · 2003 [cited by examiner]
US 20090163811A1 · Fukumoto · 2009 [cited by examiner]
US 20120116227A1 · Suzuki · 2012 [cited by examiner]
US 20130116567A1 · Nishigaki · 2013 [cited by examiner]
US 20140088426A1 · Miyachi · 2014 [cited by examiner]
Poudel et al., “Thyroid Ultrasound Texture Classification Using Autoregressive Features in Conjunction With Machine Learning Approaches,” (Jun. 17, 2019), IEEE Access ( vol. 7), p. 79354-79365. (Year: 2019). [cited by examiner]
Shin, et al., Estimation of Average Speed of Sound Using Deconvolution of Medical Ultrasound Data, Jan. 28, 2010, 14 pages. [cited by applicant]
Wang et al Simultaneous Segmentation and Classification of Bone Surfaces from Ultrasound Using a Multi-feature Guided CNN, 2018, 9 pages. [cited by applicant]