WEKO3
アイテム
Inter-crystal scatter identification for a depth-sensitive detector using support vector machine for small animal positron emission tomography
https://repo.qst.go.jp/records/44796
https://repo.qst.go.jp/records/44796d4e89984-05b0-45ea-b75b-a43c20babff1
| Item type | 学術雑誌論文 / Journal Article(1) | |||||
|---|---|---|---|---|---|---|
| 公開日 | 2007-02-22 | |||||
| タイトル | ||||||
| タイトル | Inter-crystal scatter identification for a depth-sensitive detector using support vector machine for small animal positron emission tomography | |||||
| 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_6501 | |||||
| 資源タイプ | journal article | |||||
| 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 |
Yoshida, Eiji
× Yoshida, Eiji× Kitamura, Keishi× Kimura, Yuichi× Nishikido, Fumihiko× Shibuya, Kengo× Yamaya, Taiga× Murayama, Hideo× 吉田 英治× 北村 圭司× 木村 裕一× 錦戸 文彦× 澁谷 憲悟× 山谷 泰賀× 村山 秀雄 |
|||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | In a conventional positron emission tomography (PET) detector, detected events are projected onto a 2D position histogram by an Anger calculation for crystal identification. However, the measured histogram is affected by inter-crystal scatterings (ICS) which occur in the entire detector. Peaks which are projected for each crystal in the histogram are blurred, and this causes ICS mispositioning. A depth-of-interaction (DOI) detector has been developed for the small animal PET scanner jPET-RD. This DOI detector uses 32*32 crystals with four layers and a 256-channel multi-anode flat panel photomultiplier tube (FP-PMT) which was developed by Hamamatsu Photonics K.K. Each crystal element is 1.45*1.45*4.5mm3. The FP-PMT has a large detective area (49*49mm2) and a small anode pitch (3.04 mm). Therefore, the FP-PMT can extensively trace the behavior of incident g rays in the crystals including ICS event. We, therefore, propose a novel method for ICS estimation using a statistical pattern recognition algorithm based on a support vector machine (SVM). In this study, we applied the SVM for discriminating photoelectric events from ICS events generated from multiple-anode outputs. The SVM was trained by uniform irradiation events generated from a detector simulator using a Monte Carlo calculation. The success rate for ICS event identification is about 78% for non-training data. The SVM can achieve a true subtraction of ICS events from measured events, and it is also useful for random correction in PET. | |||||
| 書誌情報 |
Nuclear Instruments & Methods in Physics Research Section A 巻 571, 号 1/2, p. 243-246, 発行日 2007-02 |
|||||
| ISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 0168-9002 | |||||
