title: Composite and classified color display in MR imaging of the female pelvis.
abstract: Because of its superior soft-tissue-imaging capabilities, MRI has proved to be an excellent modality for visualizing the contents of the female pelvis. In an effort to potentially improve gynecological MRI studies, we have applied color composite techniques to sets of spin-echo and gradient-echo gray-tone MR images obtained from various individuals. For composite generation, based on tissue region of interest calculated mean pixel intensity values, various colors were applied to spatially aligned images using a DEC MicroVAX II computer with interactive digital language (IDL) so that tissue contrast patterns could be optimized in the final image. The IDL procedures, which are similar to those used in NASA's LANDSAT image processing system, allowed the generation of single composite images displaying the combined information present in a series of spatially aligned images acquired using different pulse sequences. With our composite generation techniques, it was possible to generate seminatural-appearing color images of the female pelvis that possessed enhanced conspicuity of specific tissues and fluids. For comparison with color composites, classified images were also generated based on computer recognition and statistical separation of distinct tissue intensity patterns in an image set using the maximum likelihood processing algorithm.
authors.affiliation: Department of Anatomy, University of South Florida College of Medicine, Tampa 33612-4799.
authors.forename: H K
authors.initials: HK
authors.lastname: Brown
authors.forename: T R
authors.initials: TR
authors.lastname: Hazelton
authors.forename: J V
authors.initials: JV
authors.lastname: Fiorica
authors.forename: A K
authors.initials: AK
authors.lastname: Parsons
authors.forename: L P
authors.initials: LP
authors.lastname: Clarke
authors.forename: M L
authors.initials: ML
authors.lastname: Silbiger
mesh_terms: D003116:Color; D005260:Female; D005831:Genital Diseases, Female / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010388:Pelvis / Q000033:anatomy & histology*