X-ray Synthesis Based on Triangular Mesh Models Using GPU-Accelerated Ray Tracing for Multi-modal Breast Image Registration

被引:4
作者
Maul, J. [1 ]
Said, S. [1 ]
Ruiter, N. [1 ]
Hopp, T. [1 ]
机构
[1] Karlsruhe Inst Technol, Inst Data Proc & Elect, Karlsruhe, Germany
来源
SIMULATION AND SYNTHESIS IN MEDICAL IMAGING, SASHIMI 2021 | 2021年 / 12965卷
关键词
X-ray simulation; Ray tracing; GPU; Triangular mesh; Multi-modal image registration; Bio-mechanical Model;
D O I
10.1007/978-3-030-87592-3_9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
For image registration of breast MRI and X-ray mammography we apply detailed biomechanical models. Synthesizing X-ray mammograms from these models is an important processing step for optimizing registration parameters and deriving images for multi-modal diagnosis. A fast computation time for creating synthetic images is essential to enable a clinically relevant application. In this paper we present a method to create synthetic X-ray attenuation images with an hardware-optimized ray tracing algorithm on recent graphics processing units' (GPU) ray tracing (RT) cores. The ray tracing algorithm is able to calculate the attenuation of the X-rays by tracing through a triangular polygon-mesh. We use the Vulkan API, which enables access to RT cores. One frame for a triangle mesh with over 5 million triangles in the mesh and a detector resolution of 1080 x 1080 can be calculated and transferred to and from the GPU in about 0.76 s on NVidia RTX 2070 Super GPU. Calculation duration of an interactive application without the transfer overhead allows real time application with more than 30 frames per second (fps) even for very large polygon models. The presented method is able to calculate synthetic X-ray images in a short time and has the potential for real-time applications. Also it is the very first implementation using RT cores for this purpose. The toolbox will be available as an open source.
引用
收藏
页码:87 / 96
页数:10
相关论文
共 15 条
[1]   TETRAHEDRAL MESH GENERATION FROM VOLUMETRIC BINARY AND GRAY-SCALE IMAGES [J].
Fang, Qianqian ;
Boas, David A. .
2009 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1 AND 2, 2009, :1142-1145
[2]   Implementation and Evaluation of Various DRR Algorithms on GPU [J].
Folkerts, M. ;
Jia, X. ;
Gu, X. ;
Choi, D. ;
Majumdar, A. ;
Jiang, S. .
MEDICAL PHYSICS, 2010, 37 (06) :3367-+
[3]   X-ray based methods for non-destructive testing and material characterization [J].
Hanke, Randolf ;
Fuchs, Theobald ;
Uhlmann, Norman .
NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2008, 591 (01) :14-18
[4]   Automatic multimodal 2D/3D breast image registration using biomechanical FEM models and intensity-based optimization [J].
Hopp, T. ;
Dietzel, M. ;
Baltzer, P. A. ;
Kreisel, P. ;
Kaiser, W. A. ;
Gemmeke, H. ;
Ruiter, N. V. .
MEDICAL IMAGE ANALYSIS, 2013, 17 (02) :209-218
[5]   2D/3D image fusion of X-ray mammograms with breast MRI: visualizing dynamic contrast enhancement in mammograms [J].
Hopp, Torsten ;
Baltzer, Pascal ;
Dietzel, Matthias ;
Kaiser, Werner A. ;
Ruiter, Nicole V. .
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2012, 7 (03) :339-348
[6]  
Lickteig S, 2021, SEGMENTIERUNG VISUAL
[7]   Medical image registration: a review [J].
Oliveira, Francisco P. M. ;
Tavares, Joao Manuel R. S. .
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, 2014, 17 (02) :73-93
[8]  
Rineau L., 2008, 3D Surface Mesh Generation
[9]  
Rueckert D, 2011, BIOL MED PHYS BIOMED, P131, DOI 10.1007/978-3-642-15816-2_5
[10]   Image registration between MRI and spot mammograms for X-ray guided stereotactic breast biopsy: preliminary results [J].
Said, S. ;
Clauser, P. ;
Ruiter, N., V ;
Baltzer, P. A. T. ;
Hopp, T. .
MEDICAL IMAGING 2021: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING, 2021, 11598