東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Tissue Segmentation and Classificati...

Leynes, Andrew.

FindBook

Google Book

Amazon

博客來

Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-Echo Time (ZTE) MRI.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-Echo Time (ZTE) MRI./
作者:	Leynes, Andrew.
面頁冊數:	36 p.
附註:	Source: Masters Abstracts International, Volume: 55-01.
Contained By:	Masters Abstracts International55-01(E).
標題:	Medical imaging. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1600643
ISBN:	9781339098203

Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-Echo Time (ZTE) MRI.
Leynes, Andrew.

Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-Echo Time (ZTE) MRI. - 36 p.

Source: Masters Abstracts International, Volume: 55-01.

Thesis (M.S.)--University of California, San Francisco, 2015.

To reduce errors in the reconstructed PET image, the photon attenuation of all tissues needs to be accounted for. Current sequence-based methods to generate an MR-derived attenuation map are unable to account for all tissue classes. Recent work has demonstrated that there is phase contrast in ultrashort echo time (UTE) or zero echo time (ZTE) images that would allow classification of all necessary tissue classes (bone, air, fat, and water) from only a single ZTE scan. The aim of this thesis is to demonstrate the feasibility of generating a pseudo-CT attenuation map based on bone, air, fat, and water classifications from a single ZTE acquisition. A 3D image of the pelvis was acquired using a ZTE pulse sequence on a 3T GE Signa PET/MRI system. Semi-automated algorithms were used to segment bone, air, and soft tissue from the ZTE magnitude image. Air was segmented using an intensity limited region growing algorithm and global thresholding. Bone was segmented by enhancing bone, and then using global thresholding. Soft tissue was defined as regions where bone and air were absent. A continuous-value fat/water map was then generated with fuzzy c-means clustering using the ZTE phase image and the soft tissue mask. Appropriate HU values were assigned to the segmented tissue maps, and combined to produce the pseudo-CT attenuation map. Qualitative comparisons with CT, and Dixon pseudo-CT images presented similar tissue classification results. Preliminary results demonstrate that bone, air, fat, and water can be classified using a single ZTE acquisition.

ISBN: 9781339098203Subjects--Topical Terms:

3172799
Medical imaging.

Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-Echo Time (ZTE) MRI.
LDR:02483nmm a2200289 4500 001 2075900
005 20161028152019.5
008 170521s2015 ||||||||||||||||| ||eng d
020 $a 9781339098203
035 $a (MiAaPQ)AAI1600643
035 $a AAI1600643
040 $a MiAaPQ $c MiAaPQ
100 1 $a Leynes, Andrew. $3 3191324
245 1 0 $a Tissue Segmentation and Classification for PET/MR MR-based Attenuation Correction Using Zero-Echo Time (ZTE) MRI.
300 $a 36 p.
500 $a Source: Masters Abstracts International, Volume: 55-01.
500 $a Adviser: Peder Larson.
502 $a Thesis (M.S.)--University of California, San Francisco, 2015.
520 $a To reduce errors in the reconstructed PET image, the photon attenuation of all tissues needs to be accounted for. Current sequence-based methods to generate an MR-derived attenuation map are unable to account for all tissue classes. Recent work has demonstrated that there is phase contrast in ultrashort echo time (UTE) or zero echo time (ZTE) images that would allow classification of all necessary tissue classes (bone, air, fat, and water) from only a single ZTE scan. The aim of this thesis is to demonstrate the feasibility of generating a pseudo-CT attenuation map based on bone, air, fat, and water classifications from a single ZTE acquisition. A 3D image of the pelvis was acquired using a ZTE pulse sequence on a 3T GE Signa PET/MRI system. Semi-automated algorithms were used to segment bone, air, and soft tissue from the ZTE magnitude image. Air was segmented using an intensity limited region growing algorithm and global thresholding. Bone was segmented by enhancing bone, and then using global thresholding. Soft tissue was defined as regions where bone and air were absent. A continuous-value fat/water map was then generated with fuzzy c-means clustering using the ZTE phase image and the soft tissue mask. Appropriate HU values were assigned to the segmented tissue maps, and combined to produce the pseudo-CT attenuation map. Qualitative comparisons with CT, and Dixon pseudo-CT images presented similar tissue classification results. Preliminary results demonstrate that bone, air, fat, and water can be classified using a single ZTE acquisition.
590 $a School code: 0034.
650 4 $a Medical imaging. $3 3172799
650 4 $a Biomedical engineering. $3 535387
650 4 $a Electrical engineering. $3 649834
690 $a 0574
690 $a 0541
690 $a 0544
710 2 $a University of California, San Francisco. $b Biomedical Imaging. $3 2106351
773 0 $t Masters Abstracts International $g 55-01(E).
790 $a 0034
791 $a M.S.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1600643