@inbook{00b262e25483491bb3a5fbfe19f3cd74,
title = "Registration of abdominal CT and SPECT images using Compton scatter data",
abstract = "The present study investigates the possibility to utilize Compton scatter data for registration of abdominal SPECT images. A method for registration to CT is presented, based on principal component analysis and cross-correlation of binary images representing the interior of the patient. Segmentation of scatter images is performed with two methods, thresholding and a deformable contour method. To achieve similarity of organ positions between scans, a positioning device is applied to the patient. Evaluation of the registration accuracy is performed with a) a 131I phantom study, b) a Monte Carlo simulation study of an anthropomorphic phantom, and c) a 123I patient trial. For a) r.m.s. distances between positions that should be equal in CT and SPECT are obtained to 1.0±0.7 mm, which thus for a rigid object is at sub pixel level. From b) results show that r.m.s. distances depend on the slice activity distribution. With a symmetrical distribution deviations are in the order of 5 mm. In c) distances between markers on the patient boundary are at the maximum 16 mm and on an average 10 mm. It is concluded that by utilizing the available Compton scatter data, valuable positioning information is achieved, that can be used for registration of SPECT images.",
author = "{Sj{\"o}green Gleisner}, Katarina and Michael Ljungberg and Kjell Erlandsson and Lars Floreby and Sven-Erik Strand",
year = "1997",
doi = "10.1007/3-540-63046-5_18",
language = "English",
isbn = "978-3-540-63046-3",
volume = "1230",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "232--244",
editor = "Duncan, {J S} and Gindi, {G R}",
booktitle = "Information Processing in Medical Imaging",
address = "Germany",
}