title: Liver detection algorithm: its efficacy for CT noise reduction in the liver.
abstract: OBJECTIVE
  This study was performed to evaluate the efficacy of a novel computed tomography (CT) liver detection algorithm (LDA), which allows for targeted increase of radiation dose to the upper abdomen, on image quality of the liver.
  
  
  METHODS
  We retrospectively evaluated the LDA by comparing 40 consecutive patients who had portal venous CT abdomen performed without use of the algorithm, to 40 patients in whom the algorithm was used. Image quality was assessed objectively by comparing the standard deviation (SD) of attenuation values in Hounsfield units (HU) of the abdominal organs. Qualitative analysis was performed by two blinded radiologists who independently graded the image quality of abdominal organs
  
  
  RESULTS
  There was significant noise reduction in the liver (P < 0.001) and spleen (P < 0.001) in the LDA group compared to the conventional group. There was also a significant improvement in image quality of the liver (P < 0.001), kidney (P < 0.001), spleen (P < 0.001), pancreas (P < 0.001), and psoas (P = 0.005) in the LDA group compared to the conventional group. Overall dose between the two groups was similar.
  
  
  CONCLUSIONS
  This liver detection algorithm improves the subjective image quality of upper abdominal organs, in particular the liver, without increasing overall radiation dose.
authors.affiliation: Monash Imaging, Monash Health, 246 Clayton Road, Clayton, VIC, 3168, Australia. ashwini_dev@hotmail.com.
authors.forename: Ashwini
authors.initials: A
authors.lastname: Devapalasundaram
authors.affiliation: Monash Imaging, Monash Health, 246 Clayton Road, Clayton, VIC, 3168, Australia.|Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia.
authors.forename: Kenneth K
authors.initials: KK
authors.lastname: Lau
authors.affiliation: Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
authors.forename: Eldho
authors.initials: E
authors.lastname: Paul
authors.affiliation: Monash Imaging, Monash Health, 246 Clayton Road, Clayton, VIC, 3168, Australia.
authors.forename: Larry
authors.initials: L
authors.lastname: Mak
authors.affiliation: Monash Imaging, Monash Health, 246 Clayton Road, Clayton, VIC, 3168, Australia.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Ardley
authors.affiliation: Clinical Science, Phillips Healthcare, P. O. Box 312, Mont Albert, VIC, 3127, Australia.
authors.forename: Kevin
authors.initials: K
authors.lastname: Buchan
authors.affiliation: Monash Imaging, Monash Health, 246 Clayton Road, Clayton, VIC, 3168, Australia.
authors.forename: Ahilan
authors.initials: A
authors.lastname: Kuganesan
mesh_terms: D000465:Algorithms; D005260:Female; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011829:Radiation Dosage; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D059629:Signal-To-Noise Ratio; D014057:Tomography, X-Ray Computed / Q000379:methods* / Q000706:statistics & numerical data
keywords: Algorithm; Dosage; Image quality; Liver; Multidetector computed tomography