TY - JOUR
T1 - An augmented reality system using improved-iterative closest point algorithm for on-patient medical image visualization
AU - Wu, Ming Long
AU - Chien, Jong Chih
AU - Wu, Chieh Tsai
AU - Lee, Jiann Der
N1 - Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2018/8/1
Y1 - 2018/8/1
N2 - In many surgery assistance systems, cumbersome equipment or complicated algorithms are often introduced to build the whole system. To build a system without cumbersome equipment or complicated algorithms, and to provide physicians the ability to observe the location of the lesion in the course of surgery, an augmented reality approach using an improved alignment method to image-guided surgery (IGS) is proposed. The system uses RGB-Depth sensor in conjunction with the Point Cloud Library (PCL) to build and establish the patient’s head surface information, and, through the use of the improved alignment algorithm proposed in this study, the preoperative medical imaging information obtained can be placed in the same world-coordinates system as the patient’s head surface information. The traditional alignment method, Iterative Closest Point (ICP), has the disadvantage that an ill-chosen starting position will result only in a locally optimal solution. The proposed improved para-alignment algorithm, named improved-ICP (I-ICP), uses a stochastic perturbation technique to escape from locally optimal solutions and reach the globally optimal solution. After the alignment, the results will be merged and displayed using Microsoft’s HoloLens Head-Mounted Display (HMD), and allows the surgeon to view the patient’s head at the same time as the patient’s medical images. In this study, experiments were performed using spatial reference points with known positions. The experimental results show that the proposed improved alignment algorithm has errors bounded within 3 mm, which is highly accurate.
AB - In many surgery assistance systems, cumbersome equipment or complicated algorithms are often introduced to build the whole system. To build a system without cumbersome equipment or complicated algorithms, and to provide physicians the ability to observe the location of the lesion in the course of surgery, an augmented reality approach using an improved alignment method to image-guided surgery (IGS) is proposed. The system uses RGB-Depth sensor in conjunction with the Point Cloud Library (PCL) to build and establish the patient’s head surface information, and, through the use of the improved alignment algorithm proposed in this study, the preoperative medical imaging information obtained can be placed in the same world-coordinates system as the patient’s head surface information. The traditional alignment method, Iterative Closest Point (ICP), has the disadvantage that an ill-chosen starting position will result only in a locally optimal solution. The proposed improved para-alignment algorithm, named improved-ICP (I-ICP), uses a stochastic perturbation technique to escape from locally optimal solutions and reach the globally optimal solution. After the alignment, the results will be merged and displayed using Microsoft’s HoloLens Head-Mounted Display (HMD), and allows the surgeon to view the patient’s head at the same time as the patient’s medical images. In this study, experiments were performed using spatial reference points with known positions. The experimental results show that the proposed improved alignment algorithm has errors bounded within 3 mm, which is highly accurate.
KW - Head-mounted display
KW - Image alignment
KW - Improved-ICP algorithm
UR - http://www.scopus.com/inward/record.url?scp=85051167481&partnerID=8YFLogxK
U2 - 10.3390/s18082505
DO - 10.3390/s18082505
M3 - 文章
C2 - 30071645
AN - SCOPUS:85051167481
SN - 1424-8220
VL - 18
JO - Sensors
JF - Sensors
IS - 8
M1 - 2505
ER -