Automatic Object Detection on Tomographic Projections

被引:0
作者
Ivanov, D. A. [1 ]
Chukalina, M. V. [2 ,3 ,4 ]
Ingacheva, A. S. [3 ]
Buzmakov, A. V. [2 ]
Krivonosov, Yu. S. [2 ]
Shabelnikova, Ya. L. [5 ]
Nikolaev, D. P. [3 ,4 ]
机构
[1] State Univ, Moscow Inst Phys & Technol, Dolgoprudnyi 141701, Moscow Oblast, Russia
[2] Russian Acad Sci, Shubnikov Inst Crystallog FSRC Crystallog & Photo, Moscow 119333, Russia
[3] Russian Acad Sci, Inst Informat Transmiss Problems, Moscow 127051, Russia
[4] Smart Engines Serv, Moscow 117312, Russia
[5] Russian Acad Sci, Inst Microelect Technol Problems & High, Chernogolovka 142432, Moscow Oblast, Russia
来源
JOURNAL OF SURFACE INVESTIGATION | 2020年 / 14卷 / 05期
基金
俄罗斯基础研究基金会;
关键词
X-ray; computer tomography; region of interest (ROI); tomographic projections; reconstruction time; signal-to-noise ratio; Shepp-Logan phantom; ALGEBRAIC RECONSTRUCTION; ART;
D O I
10.1134/S1027451020050079
中图分类号
O469 [凝聚态物理学];
学科分类号
070205 ;
摘要
In this study we present an approach used to truncate the empty space outside ROI on a stack of 2D tomographic projections by the means of locating the specific region of interest (ROI). In this work we shall consider the following definition of the region of interest-it is the area of the detector which only receives rays incident to the object during each measurement. Our goal is defined as-using a stack of 2D projection to find ROI and use it to truncate the amount of data processed by reconstruction block. We evaluate our approach on a phantom data to get the idea of how the amount of truncated pixels influence reconstruction time and signal-to-noise ratio. We use SART method as our primary tool of reconstruction. The approach is also applied to the real dataset. Significant improvement of the reconstruction time is achieved in both cases.
引用
收藏
页码:978 / 990
页数:13
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