Algorithm for image reconstruction in multi-slice helical CT
Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the z dire...
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| Vydané v: | Medical physics (Lancaster) Ročník 25; číslo 4; s. 550 - 561 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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United States
American Association of Physicists in Medicine
01.04.1998
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| ISSN: | 0094-2405, 2473-4209 |
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| Abstract | Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the
z
direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi-slice CT. Two helical interpolation methods for single-slice CT, 360LI and 180LI, were used as starting points and extended to multi-slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan-beam reconstruction. Optimized sampling scan refers to a special type of multi-slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the
z
direction. Filter interpolation refers to a filtering process performed in the
z
direction using several data. The normal fan-beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four-array multi-slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single-slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination. |
|---|---|
| AbstractList | Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the z direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi-slice CT. Two helical interpolation methods for single-slice CT, 360LI and 180LI, were used a starting points and extended to multi-slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan-beam reconstruction. Optimized sampling scan refers to a special type of multi-slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the z direction. Filter interpolation refers to a filtering process performed in the z direction using several data. The normal fan-beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four-array multi-slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single-slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination. Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the z direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi-slice CT. Two helical interpolation methods for single-slice CT, 360LI and 180LI, were used as starting points and extended to multi-slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan-beam reconstruction. Optimized sampling scan refers to a special type of multi-slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the z direction. Filter interpolation refers to a filtering process performed in the z direction using several data. The normal fan-beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four-array multi-slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single-slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination. Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi‐slice CT, which involves several detector arrays stacked in the z direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi‐slice CT. Two helical interpolation methods for single‐slice CT, 360LI and 180LI, were used as starting points and extended to multi‐slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan‐beam reconstruction. Optimized sampling scan refers to a special type of multi‐slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the z direction. Filter interpolation refers to a filtering process performed in the z direction using several data. The normal fan‐beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four‐array multi‐slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single‐slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination. Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the z direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi-slice CT. Two helical interpolation methods for single-slice CT, 360LI and 180LI, were used a starting points and extended to multi-slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan-beam reconstruction. Optimized sampling scan refers to a special type of multi-slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the z direction. Filter interpolation refers to a filtering process performed in the z direction using several data. The normal fan-beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four-array multi-slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single-slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination.Efforts are being made to develop a new type of CT system that can scan volumes over a large range within a short time with thin slice images. One of the most promising approaches is the combination of helical scanning with multi-slice CT, which involves several detector arrays stacked in the z direction. However, the algorithm for image reconstruction remains one of the biggest problems in multi-slice CT. Two helical interpolation methods for single-slice CT, 360LI and 180LI, were used a starting points and extended to multi-slice CT. The extended methods, however, had a serious image quality problem due to the following three reasons: (1) excessively close slice positions of the complementary and direct data, resulting in a larger sampling interval; (2) the existence of several discontinuous changeovers in pairs of data samples for interpolation; and (3) the existence of cone angles. Therefore we have proposed a new algorithm to overcome the problem. It consists of the following three parts: (1) optimized sampling scan; (2) filter interpolation; and (3) fan-beam reconstruction. Optimized sampling scan refers to a special type of multi-slice helical scan developed to shift the slice position of complementary data and to acquire data with a much smaller sampling interval in the z direction. Filter interpolation refers to a filtering process performed in the z direction using several data. The normal fan-beam reconstruction technique is used. The section sensitivity profile (SSP) and image quality for four-array multi-slice CT were investigated by computer simulations. Combinations of three types of optimized sampling scan and various filter widths were used. The algorithm enables us to achieve acceptable image quality and spatial resolution at a scanning speed that is about three times faster than that for single-slice CT. The noise characteristics show that the proposed algorithm efficiently utilizes the data collected with optimized sampling scan. The new algorithm allows suitable combinations of scan and filter parameters to be selected to meet the purpose of each examination. |
| Author | Aradate, Hiroshi Taguchi, Katsuyuki |
| Author_xml | – sequence: 1 givenname: Katsuyuki surname: Taguchi fullname: Taguchi, Katsuyuki organization: Medical Engineering Laboratory, Toshiba Corporation, 1385 Shimoishigami, Otawara, Tochigi 324-8550, Japan – sequence: 2 givenname: Hiroshi surname: Aradate fullname: Aradate, Hiroshi organization: Medical Engineering Laboratory, Toshiba Corporation, 1385 Shimoishigami, Otawara, Tochigi 324-8550, Japan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/9571623$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1118/1.597706 10.1109/42.241876 10.1118/1.596464 10.1148/radiology.176.1.2353088 |
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| References_xml | – volume: 189P start-page: 335 year: 1996 ident: r7 article-title: Helical reconstruction algorithm with user-selectable section profiles publication-title: Radiology – volume: 17 start-page: 967 year: 1990 ident: r5 article-title: Computed tomography scanning with simultaneous patient translation publication-title: Med. Phys. – volume: 12 start-page: 3 year: 1993 ident: r9 article-title: A general cone-beam reconstruction algorithm publication-title: IEEE Trans. Med. Imaging – volume: 23 start-page: 221 year: 1996 ident: r6 article-title: A general approach to the reconstruction of x-ray helical computed tomography publication-title: Med. Phys. – volume: 176 start-page: 181 year: 1990 ident: r2 article-title: Spiral volumetric CT with single-breath-hold technique, continuous transport, and continuous scanner rotation publication-title: Radiology – volume: J74-D-II start-page: 1108 year: 1991 ident: r8 article-title: Three-dimensional helical-scan computed tomography using cone-beam projections publication-title: IEICE (D-II) – volume: 121P start-page: 108 year: 1990 ident: r4 article-title: New reconstruction algorithm in helical-volume CT publication-title: Radiology – volume: J74‐D‐II start-page: 1108 year: 1991 end-page: 1114 article-title: Three‐dimensional helical‐scan computed tomography using cone‐beam projections publication-title: IEICE (D‐II) – volume: 121P start-page: 108 year: 1990 article-title: New reconstruction algorithm in helical‐volume CT publication-title: Radiology – volume: 23 start-page: 221 year: 1996 end-page: 229 article-title: A general approach to the reconstruction of x‐ray helical computed tomography publication-title: Med. Phys. – volume: 176 start-page: 181 year: 1990 end-page: 183 article-title: Spiral volumetric CT with single‐breath‐hold technique, continuous transport, and continuous scanner rotation publication-title: Radiology – volume: 189P start-page: 335 year: 1996 article-title: Helical reconstruction algorithm with user‐selectable section profiles publication-title: Radiology – volume: 17 start-page: 967 year: 1990 end-page: 982 article-title: Computed tomography scanning with simultaneous patient translation publication-title: Med. Phys. – volume: 12 start-page: 3 year: 1993 article-title: A general cone‐beam reconstruction algorithm publication-title: IEEE Trans. Med. Imaging – ident: 10.1118/1.598230-BIB10|rf10 – volume: 23 start-page: 221 year: 1996 ident: 10.1118/1.598230-BIB6|rf6 article-title: A general approach to the reconstruction of x-ray helical computed tomography publication-title: Med. Phys. doi: 10.1118/1.597706 – ident: 10.1118/1.598230-BIB3|rf3 – ident: 10.1118/1.598230-BIB1|rf1 – volume: 12 start-page: 3 year: 1993 ident: 10.1118/1.598230-BIB9|rf9 article-title: A general cone-beam reconstruction algorithm publication-title: IEEE Trans. Med. Imaging doi: 10.1109/42.241876 – volume: 189P start-page: 335 year: 1996 ident: 10.1118/1.598230-BIB7|rf7 article-title: Helical reconstruction algorithm with user-selectable section profiles publication-title: Radiology – volume: 121P start-page: 108 year: 1990 ident: 10.1118/1.598230-BIB4|rf4 article-title: New reconstruction algorithm in helical-volume CT publication-title: Radiology – volume: 17 start-page: 967 year: 1990 ident: 10.1118/1.598230-BIB5|rf5 article-title: Computed tomography scanning with simultaneous patient translation publication-title: Med. Phys. doi: 10.1118/1.596464 – volume: J74-D-II start-page: 1108 year: 1991 ident: 10.1118/1.598230-BIB8|rf8 article-title: Three-dimensional helical-scan computed tomography using cone-beam projections publication-title: IEICE (D-II) – volume: 176 start-page: 181 year: 1990 ident: 10.1118/1.598230-BIB2|rf2 article-title: Spiral volumetric CT with single-breath-hold technique, continuous transport, and continuous scanner rotation publication-title: Radiology doi: 10.1148/radiology.176.1.2353088 |
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| SubjectTerms | 87.56.05 Algorithms Computed radiography Computed tomography Computer Simulation computerised tomography Detector arrays filter interpolation helical scan Image processing image reconstruction image resolution Interpolation medical image processing Medical image quality Medical image reconstruction Medical imaging Models, Theoretical Multislice computed tomography multi‐slice CT optimized sampling scan Phantoms, Imaging Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Single slice computed tomography Tomography, X-Ray Computed |
| Title | Algorithm for image reconstruction in multi-slice helical CT |
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