title: Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI.
abstract: OBJECTIVE
  To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging.
  
  
  METHODS
  The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities.
  
  
  RESULTS
  Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions.
  
  
  CONCLUSIONS
  Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.
authors.affiliation: Department of Radiology, Boston Children's Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Ali
authors.initials: A
authors.lastname: Gholipour
authors.affiliation: Department of Radiology, Boston Children's Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Onur
authors.initials: O
authors.lastname: Afacan
authors.affiliation: Radiology Department, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts 02129 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Iman
authors.initials: I
authors.lastname: Aganj
authors.affiliation: Department of Radiology, Boston Children's Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Benoit
authors.initials: B
authors.lastname: Scherrer
authors.affiliation: Department of Radiology, Boston Children's Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Sanjay P
authors.initials: SP
authors.lastname: Prabhu
authors.affiliation: Department of Neurology, Boston Children's Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Mustafa
authors.initials: M
authors.lastname: Sahin
authors.affiliation: Department of Radiology, Boston Children's Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115.
authors.forename: Simon K
authors.initials: SK
authors.lastname: Warfield
mesh_terms: D001921:Brain / Q000473:pathology; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007257:Information Theory; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D019047:Phantoms, Imaging; D012189:Retrospective Studies; D014402:Tuberous Sclerosis / Q000473:pathology; D058067:Wavelet Analysis