title: Illumination correction on MR images.
abstract: OBJECTIVE
  An important artifact corrupting Magnetic Resonance Images is the rf inhomogeneity, also called bias artifact. This anomaly produces an abnormal illumination fluctuation on the image, due to variations of the device magnetic field. This artifact is particularly strong on images acquired with a device specialized on upper and lower limbs due to their coil configuration. A method based on homomorphic filtering aimed to suppress this artifact was proposed by Guillemaud. This filter has two faults: it doesn't provide an indication about the cutoff frequency (cf) and introduces another illumination artifact on the edges of the foreground. This work is an improvement to this method because it resolves both problems.
  
  
  METHODS
  The experimental setup has been performed on knee images obtained by 5 volunteers and acquired through an Artoscan device using the following parameters: Spin Echo sequence, Repetition time: 980 ms, Echo time: 26 ms, Slice thickness: 4 mm, Flip Angle: 90 degrees .
  
  
  RESULTS
  Two specialists in orthoptics evaluated the results of the proposed approach by examining the restored images and validating the results produced by the filter. A quantitative evaluation has been performed on a manually segmented restored image using the coefficient of variation (cv) measure.
  
  
  CONCLUSIONS
  Following the specialists qualitative evaluation, the illuminance of upper and lower peripheral zones results to be enhanced; a loose of contrast can be noted only in few cases. The Bias image exhibits an artifact focused usually on the central part of the foreground. The quantitative evaluation based on cv shows that this index is lowered for all the segmented regions with respect to the original value. The method is automatic and doesn't require any hypothesis on the tissues. A manual version of the algorithm can be also implemented allowing the physician to choose the preferred cf. In this case the value selected by the method can be considered as a default value.
authors.affiliation: Dipartimento di Ingegneria Informatica, Computer Science and Artificial Intelligence Laboratory, Universita' degli Studi di Palermo, viale delle Scienze, Building 6, 3rd floor, Palermo, Italy.
authors.forename: Edoardo
authors.initials: E
authors.lastname: Ardizzone
authors.forename: Roberto
authors.initials: R
authors.lastname: Pirrone
authors.forename: Orazio
authors.initials: O
authors.lastname: Gambino
mesh_terms: D000465:Algorithms; D015982:Bias; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D007717:Knee / Q000033:anatomy & histology; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*