Koninklijke Philips Corporation N.V.

Koninklijke Philips Electronics N.v.

Angela Da Silva

Lingxiong Shao

Jinghan Ye

Zuo Zhao

Xiyun Song

Horace H Hines

Carsten Meyer

Michael J Petrillo

Andreas Goedicke

Hans-Aloys Wischmann

Jürgen Weese

Ingwer-Curt Carlsen

Jingkun Hu

Hongjie Liang

Peter Roesch

Anna Exner

Ingwer C Carlsen

Sudhir K Mahakali

Alicia Wong

Sudhir K Mahakai

An anatomical image data set and an emission image data set are acquired for a subject. An attenuation map is generated from the anatomical image data set. The emission image data set is reconstructed to generate an emission image. The reconstructing includes correcting for attenuation of emission radiation in the subject using the attenuation map. A value is calculated for a quality assurance (QA) metric quantifying alignment of the attenuation map with the emission image. The emission image is displayed or printed together with the calculated quality assurance metric. In some embodiments, prior to the reconstructing the attenuation map is registered with the emission image data set by performing a global rigid registration followed by a local non-rigid registration of a region of interest.

Dual modality imaging including quality metrics

Hybrid dual-modality image processing systems and methods are disclosed. For example, an image processing system includes a computer for processing SPECT tomographic projection data and a CT volume image. The computer derives a SPECT transverse volume image from the projection data and registers the SPECT transverse volume image with the CT volume image to obtain an attenuation map and registration information. The computer uses the attenuation map and the registration information to derive a SPECT transverse volume image with attenuation correction. The computer uses the registration information to derive a SPECT transverse volume image without attenuation correction. The SPECT transverse volume images, with and without attenuation correction, are derived at or near the same time, using the same registration information. The registration information is stored in, carried by, or otherwise communicated through the attenuation map for subsequent processing of the SPECT transverse volume images.

Hybrid dual-modality image processing system and method

Medical images are collected in a plurality of cardiac and respiratory phases. The images are transformed into a series of respiratory compensated images with the plurality of cardiac phases, but all at a common respiration phase. The series of respiratory compensated images are transformed into one image at a selected cardiac phase and the common respiration phase. In some embodiments, a database of gated transform matrices is generated. The database may be based on specific patient information or on information generated from a pool of patients. The database may account for respiratory motion, cardiac contractile motion, other physiological motion, or combinations thereof. For a current image to be motion corrected, the transformation matrices collected in the database are used to estimate a current set of transformation matrices accounting for the motion in the current image, and a motion-compensated image is generated based on the current set of transform matrices.

Motion compensation in functional imaging

A phantom () is used to calibrate a multi-modality imaging system () that includes a nuclear imaging system () and a CT scanner (). The phantom () includes marker receiving cavities () positioned at fixed locations in the phantom, in which markers () are removably placed. The markers () include CT markers (), which are imageable by the CT scanner (), and radioisotope markers (), which are imageable by the nuclear imaging system (). The radioisotope markers () are disposed into wells () provided at a center of mass of each disk-like CT marker. The markers () have a label () identifying its isotope. The phantom (), rigidly affixed to a couch (), is imaged by the nuclear imaging system () and by the CT scanner (). A transformation processor () calculates a transformation which brings centroids of the CT markers () in a CT image and the radioisotope markers () in a nuclear image into alignment.

Calibration image alignment in a PET-CT system

method A first image of a moving object is acquired by of a first imaging method, e.g by PET or SPECT imaging. The first image contains artifacts caused by object motion. From two further images acquired by a second imaging method, e.g. C.T. or M.R., and representing the object in respective states of motion, a motion model is formed. The information contents of either the first image or a combination image, formed from the first image and the two further images, and the motion model is enhanced.

Motion artifact correction of tomographical images

A method for non-rigid registration and fusion of images with physiological modeled organ motions resulting from respiratory motion and cardiac motion that are mathematically modeled with physiological constraints. A method of combining images comprises the steps of obtaining a first image dataset () of a region of interest of a subject and obtaining a second image dataset () of the region of interest of the subject. Next, a general model of physiological motion for the region of interest is provided (). The general model of physiological motion is adapted with data derived from the first image data set () to provide a subject specific physiological model (). The subject specific physiological model is applied () to the second image dataset () to provide a combined image ().

Physiological model based non-rigid image registration

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Danville, CA, United States of America

Angela Da Silva