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Title: Image filtering as an alternative to the application of a different reconstruction kernel in CT imaging: Feasibility study in lung cancer screening

Abstract

Purpose: While the acquisition of projection data in a computed tomography (CT) scanner is generally carried out once, the projection data is often removed from the system, making further reconstruction with a different reconstruction filter impossible. The reconstruction kernel is one of the most important parameters. To have access to all the reconstructions, either prior reconstructions with multiple kernels must be performed or the projection data must be stored. Each of these requirements would increase the burden on data archiving. This study aimed to design an effective method to achieve similar image quality using an image filtering technique in the image space, instead of a reconstruction filter in the projection space for CT imaging. The authors evaluated the clinical feasibility of the proposed method in lung cancer screening. Methods: The proposed technique is essentially the same as common image filtering, which performs processing in the spatial-frequency domain with a filter function. However, the filter function was determined based on the quantitative analysis of the point spread functions (PSFs) measured in the system. The modulation transfer functions (MTFs) were derived from the PSFs, and the ratio of the MTFs was used as the filter function. Therefore, using an image reconstructed withmore » a kernel, an image reconstructed with a different kernel was obtained by filtering, which used the ratio of the MTFs obtained for the two kernels. The performance of the method was evaluated by using routine clinical images obtained from CT screening for lung cancer in five subjects. Results: Filtered images for all combinations of three types of reconstruction kernels (''smooth,''''standard,'' and ''sharp'' kernels) showed good agreement with original reconstructed images regarded as the gold standard. On the filtered images, abnormal shadows suspected as being lung cancers were identical to those on the reconstructed images. The standard deviations (SDs) for the difference between filtered images and reconstructed images ranged from 1.9 to 23.5 Hounsfield units for all kernel combinations; these SDs were much smaller than the noise SDs in the reconstructed images. Conclusions: The proposed method has good performance and is clinically feasible in lung cancer screening. This method can be applied to images reconstructed on any scanner by measuring the PSFs in each system.« less

Authors:
; ; ; ;  [1];  [2];  [2]
  1. Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Niigata University, Niigata 951-8518 (Japan)
  2. (Japan)
Publication Date:
OSTI Identifier:
22098544
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 38; Journal Issue: 7; Other Information: (c) 2011 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; COMPUTERIZED TOMOGRAPHY; FEASIBILITY STUDIES; FILTERS; GOLD; IMAGE PROCESSING; IMAGES; KERNELS; LUNGS; MODULATION; NEOPLASMS; NOISE; PERFORMANCE; SCREENING; SPATIAL RESOLUTION; TRANSFER FUNCTIONS

Citation Formats

Ohkubo, Masaki, Wada, Shinichi, Kayugawa, Akihiro, Matsumoto, Toru, Murao, Kohei, Kensei Clinic, Chiba 260-0032, and Fujitsu Ltd., Tokyo 144-8588. Image filtering as an alternative to the application of a different reconstruction kernel in CT imaging: Feasibility study in lung cancer screening. United States: N. p., 2011. Web. doi:10.1118/1.3590363.
Ohkubo, Masaki, Wada, Shinichi, Kayugawa, Akihiro, Matsumoto, Toru, Murao, Kohei, Kensei Clinic, Chiba 260-0032, & Fujitsu Ltd., Tokyo 144-8588. Image filtering as an alternative to the application of a different reconstruction kernel in CT imaging: Feasibility study in lung cancer screening. United States. doi:10.1118/1.3590363.
Ohkubo, Masaki, Wada, Shinichi, Kayugawa, Akihiro, Matsumoto, Toru, Murao, Kohei, Kensei Clinic, Chiba 260-0032, and Fujitsu Ltd., Tokyo 144-8588. Fri . "Image filtering as an alternative to the application of a different reconstruction kernel in CT imaging: Feasibility study in lung cancer screening". United States. doi:10.1118/1.3590363.
@article{osti_22098544,
title = {Image filtering as an alternative to the application of a different reconstruction kernel in CT imaging: Feasibility study in lung cancer screening},
author = {Ohkubo, Masaki and Wada, Shinichi and Kayugawa, Akihiro and Matsumoto, Toru and Murao, Kohei and Kensei Clinic, Chiba 260-0032 and Fujitsu Ltd., Tokyo 144-8588},
abstractNote = {Purpose: While the acquisition of projection data in a computed tomography (CT) scanner is generally carried out once, the projection data is often removed from the system, making further reconstruction with a different reconstruction filter impossible. The reconstruction kernel is one of the most important parameters. To have access to all the reconstructions, either prior reconstructions with multiple kernels must be performed or the projection data must be stored. Each of these requirements would increase the burden on data archiving. This study aimed to design an effective method to achieve similar image quality using an image filtering technique in the image space, instead of a reconstruction filter in the projection space for CT imaging. The authors evaluated the clinical feasibility of the proposed method in lung cancer screening. Methods: The proposed technique is essentially the same as common image filtering, which performs processing in the spatial-frequency domain with a filter function. However, the filter function was determined based on the quantitative analysis of the point spread functions (PSFs) measured in the system. The modulation transfer functions (MTFs) were derived from the PSFs, and the ratio of the MTFs was used as the filter function. Therefore, using an image reconstructed with a kernel, an image reconstructed with a different kernel was obtained by filtering, which used the ratio of the MTFs obtained for the two kernels. The performance of the method was evaluated by using routine clinical images obtained from CT screening for lung cancer in five subjects. Results: Filtered images for all combinations of three types of reconstruction kernels (''smooth,''''standard,'' and ''sharp'' kernels) showed good agreement with original reconstructed images regarded as the gold standard. On the filtered images, abnormal shadows suspected as being lung cancers were identical to those on the reconstructed images. The standard deviations (SDs) for the difference between filtered images and reconstructed images ranged from 1.9 to 23.5 Hounsfield units for all kernel combinations; these SDs were much smaller than the noise SDs in the reconstructed images. Conclusions: The proposed method has good performance and is clinically feasible in lung cancer screening. This method can be applied to images reconstructed on any scanner by measuring the PSFs in each system.},
doi = {10.1118/1.3590363},
journal = {Medical Physics},
issn = {0094-2405},
number = 7,
volume = 38,
place = {United States},
year = {2011},
month = {7}
}