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Hybrid wavelet shrinkage (HWS) filter suppress the noise propagation in ordered subset expectation maximization (OS-EM) algorithm

https://repo.qst.go.jp/records/70965
https://repo.qst.go.jp/records/70965
f97866ea-09d3-4ee1-9f7d-dd0eec2c06f7
Item type 会議発表用資料 / Presentation(1)
公開日 2012-11-07
タイトル
タイトル Hybrid wavelet shrinkage (HWS) filter suppress the noise propagation in ordered subset expectation maximization (OS-EM) algorithm
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_c94f
資源タイプ conference object
アクセス権
アクセス権 metadata only access
アクセス権URI http://purl.org/coar/access_right/c_14cb
著者 Shiraishi, Takahiro

× Shiraishi, Takahiro

WEKO 697425

Shiraishi, Takahiro

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Kanno, Iwao

× Kanno, Iwao

WEKO 697426

Kanno, Iwao

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Ito, Hiroshi

× Ito, Hiroshi

WEKO 697427

Ito, Hiroshi

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Yoshikawa, Kyosan

× Yoshikawa, Kyosan

WEKO 697428

Yoshikawa, Kyosan

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Tanimoto, Katsuyuki

× Tanimoto, Katsuyuki

WEKO 697429

Tanimoto, Katsuyuki

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Ishii, Noriyuki

× Ishii, Noriyuki

WEKO 697430

Ishii, Noriyuki

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Kimura, Taku

× Kimura, Taku

WEKO 697431

Kimura, Taku

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Omatsu, Mika

× Omatsu, Mika

WEKO 697432

Omatsu, Mika

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Ohashi, Seiya

× Ohashi, Seiya

WEKO 697433

Ohashi, Seiya

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Toubaru, Sachiko

× Toubaru, Sachiko

WEKO 697434

Toubaru, Sachiko

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Takano, Harumasa

× Takano, Harumasa

WEKO 697435

Takano, Harumasa

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Tsuji, Hiroshi

× Tsuji, Hiroshi

WEKO 697436

Tsuji, Hiroshi

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Ando, Yutaka

× Ando, Yutaka

WEKO 697437

Ando, Yutaka

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Kamada, Tadashi

× Kamada, Tadashi

WEKO 697438

Kamada, Tadashi

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Shibayama, Kouichi

× Shibayama, Kouichi

WEKO 697439

Shibayama, Kouichi

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白石 貴博

× 白石 貴博

WEKO 697440

en 白石 貴博

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菅野 巖

× 菅野 巖

WEKO 697441

en 菅野 巖

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伊藤 浩

× 伊藤 浩

WEKO 697442

en 伊藤 浩

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吉川 京燦

× 吉川 京燦

WEKO 697443

en 吉川 京燦

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谷本 克之

× 谷本 克之

WEKO 697444

en 谷本 克之

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石井 徳幸

× 石井 徳幸

WEKO 697445

en 石井 徳幸

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木村 卓

× 木村 卓

WEKO 697446

en 木村 卓

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尾松 美香

× 尾松 美香

WEKO 697447

en 尾松 美香

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大橋 靖也

× 大橋 靖也

WEKO 697448

en 大橋 靖也

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桃原 幸子

× 桃原 幸子

WEKO 697449

en 桃原 幸子

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高野 晴成

× 高野 晴成

WEKO 697450

en 高野 晴成

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辻 比呂志

× 辻 比呂志

WEKO 697451

en 辻 比呂志

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安藤 裕

× 安藤 裕

WEKO 697452

en 安藤 裕

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鎌田 正

× 鎌田 正

WEKO 697453

en 鎌田 正

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柴山 晃一

× 柴山 晃一

WEKO 697454

en 柴山 晃一

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抄録
内容記述タイプ Abstract
内容記述 Purpose
Image reconstruction for most nuro-transmission PET scan data is performed by FBP because of a positive bias caused by the noise propagation in OS-EM algorithm. A positive bias affects the estimation of binding potential (BP) calculated from radioactive concentrations of reference regions and target region in nuroreceptor binding assay. To suppress the noise propagation in OS-EM algorithm, the hybrid wavelet shrinkage (HWS) filter is developed. In this study, we performed the phantom study to evaluate the effect of HWS filter on noise propagation in OS-EM algorithm.
\nMaterials and Methods
Phantom studies are performed by SET-3000GCT/X (shimadzu corp). To evaluate the effect of the HWS filter, we planned the some phantom study. IEC body phantom filled with 18F (activity concentration ratios relative to background of 4:1) are used for evaluation of image quality. A pool phantom filled with 18F (11.4kBq/ml) is scanned by dynamic scan mode for evaluation the quantification of PET image. Prior to emission scans, a transmission scan (6min) for attenuation correction with a 137Cs point source with a BGO transmission detector ring coaxially attached to the GSO emission detector ring. Reconstruction parameters of PET images are follows; FBP with Gaussian filter 5.0mm, OS-EM, OS-EM with HWS filter (OS-EMw). Iteration numbers in OS-EM algorithm are varied from 1 to 100 to evaluate the noise propagation.
\nResults
In pool phantom study, a positive bias at low count rate is shown in PET images reconstructed by OS-EM algorithm, while any biases are not shown in images reconstructed by FBP and OS-EMw algorithm. The N10 values are diverged due to noise propagation in OS-EM algorithm while N10 values calculated from PET image reconstructed by OS-EMw algorithm are convergence at the point of 10 iterations in IEC body phantom study. Similarly, the Q10 values are diverged depends on iteration number in OS-EM algorithm while that of OS-EMw has fast convergence. Furthermore, these results indicate that OS-EMw has the fast convergence of pixel number and suppress the noise propagation.
\nConclusion
According to our study, OS-EMw has fast convergence and suppresses the noise propagation in OS-EM algorithm. These results show that HWS filter can be a standard de-noising method for nuro-recptor PET imaging with OS-EM algorithm.
会議概要(会議名, 開催地, 会期, 主催者等)
内容記述タイプ Other
内容記述 Annual Congress of the European Association of Nuclear Medicine
発表年月日
日付 2012-10-31
日付タイプ Issued
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