title: Automatic registration of MR and SPECT images for treatment planning in prostate cancer.
abstract: OBJECTIVE
  To aid in surgical and radiation therapy planning for prostate adenocarcinoma, a general-purpose automatic registration method that is based on mutual information was used to align magnetic resonance (MR) images and single photon emission computed tomographic (SPECT) images of the pelvis and prostate.
  
  
  METHODS
  The authors assessed the effects of various factors on alignment between pairs of MR and SPECT images, including the use of particular pulse sequences in MR imaging, image voxel intensity scaling, the use of different regions on the MR-SPECT histogram, spatial masking of nonoverlapping visual data between images, and multiresolution optimization. A mutual information algorithm was used as the cost function for automatic registration. Automatic registration was deemed acceptable when it resulted in a transformation with less than 2 voxel units (6 mm) difference in translation and less than 2 degree difference in rotation from that obtained with manual registration performed independently by nuclear medicine radiologists.
  
  
  RESULTS
  Paired sets of MR and SPECT image volumes from four of five patients were successfully registered. For successful registration, MR images must be optimal and registration must be performed at full spatial resolution and at the full intensity range. Masking, cropping, and the normalization of mutual information, used to register partially overlapping MR-SPECT volumes, were not successful. Multiresolution optimization had little effect on the accuracy and speed of the registration.
  
  
  CONCLUSIONS
  Automatic registration between MR and SPECT images of the pelvis can be achieved when data acquisition and image processing are performed properly. It should prove useful for prostate cancer diagnosis, staging, and treatment planning.
authors.affiliation: Department of Radiology, University Hospitals of Cleveland, School of Medicine, Cleveland, Ohio 44106, USA.
authors.forename: Zhenghong
authors.initials: Z
authors.lastname: Lee
authors.forename: Kenichi K
authors.initials: KK
authors.lastname: Nagano
authors.forename: Jeffrey L
authors.initials: JL
authors.lastname: Duerk
authors.forename: D Bruce
authors.initials: DB
authors.lastname: Sodee
authors.forename: David L
authors.initials: DL
authors.lastname: Wilson
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis*; D000465:Algorithms; D001853:Bone Marrow / Q000000981:diagnostic imaging; D002985:Clinical Protocols; D001330:Electronic Data Processing; D005269:Femur / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D011631:Pubic Symphysis / Q000000981:diagnostic imaging; D011859:Radiography; D012042:Registries; D015899:Tomography, Emission-Computed, Single-Photon