US 12,453,602 B2
Ultrasonic puncture guidance planning system based on multi-modal medical image registration using an iterative closest point algorithm
Xiongwen Huang, Shenzhen (CN); Rongliang Zhu, Shenzhen (CN); Shanshan Wang, Shenzhen (CN); Pablo David Burstein, Shenzhen (CN); and Mengling Wu, Shenzhen (CN)
Assigned to Carbon (Shenzhen) Medical Device Co, Ltd., Shenzhen (CN)
Filed by Carbon (Shenzhen) Medical Device Co, Ltd., Shenzhen (CN)
Filed on Jul. 20, 2023, as Appl. No. 18/224,064.
Claims priority of application No. 202211219688.3 (CN), filed on Oct. 8, 2022.
Prior Publication US 2024/0115322 A1, Apr. 11, 2024
Int. Cl. A61B 34/10 (2016.01); A61B 8/00 (2006.01); A61B 17/34 (2006.01); G06T 5/70 (2024.01); G06T 7/33 (2017.01); G06T 7/38 (2017.01); G06T 15/08 (2011.01); G06T 17/20 (2006.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01)
CPC A61B 34/10 (2016.02) [A61B 8/4254 (2013.01); A61B 8/463 (2013.01); A61B 8/5261 (2013.01); A61B 17/3403 (2013.01); G06T 5/70 (2024.01); G06T 7/344 (2017.01); G06T 7/38 (2017.01); G06T 15/08 (2013.01); G06T 17/20 (2013.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); A61B 2017/3411 (2013.01); A61B 2017/3413 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30196 (2013.01); G06T 2210/41 (2013.01); G06T 2210/56 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method for an ultrasonic puncture guidance planning system based on a multi-modal medical image registration, comprising:
(a) receiving magnetic resonance imaging (MRI) sequence images of a human body, performing three-dimensional rendering on the MRI sequence images and plotting a puncture point;
(b) receiving ultrasound sequence images of the human body, extracting three-dimensional coordinates of four vertices of each frame of the ultrasound sequence images, and reconstructing ultrasound volume data;
(c) performing, by using an Iterative Closest Point (ICP) iterative algorithm, a three-dimensional registration operation on (i) the ultrasound volume data reconstructed in step (b) and (ii) the MRI data rendered in step (a) to obtain a registration transformation coefficient that transforms three-dimensional coordinates corresponding to ultrasound data into three-dimensional coordinates corresponding to MRI data, wherein the registration operation comprises (1) performing triangle-mesh processing and smoothing on the reconstructed ultrasound volume data and down-sampling to obtain a three-dimensional source point cloud of the reconstructed ultrasound volume data, and (2) performing structural pairing on the three-dimensional source point cloud and three-dimensional target point cloud of the MRI-rendered data using a K-Nearest Neighbor (KNN) tree, determining corresponding point pairs, and executing the ICP iterative algorithm to complete registration, thereby obtaining a registration rotation matrix R and a registration translation amount T; and
(d) receiving ultrasound images of the human body acquired by an ultrasound probe, and generating and displaying a puncture planning image based on a system puncture point and a current ultrasound image.