Blind Deconvolution of PET Images using Anatomical Priors

نویسندگان

  • Stéphanie Guérit
  • Adriana Gonzalez
  • Anne Bol
  • John A. Lee
  • Laurent Jacques
چکیده

Images from positron emission tomography (PET) provide metabolic information about the human body. They present, however, a spatial resolution that is limited by physical and instrumental factors often modeled by a blurring function. Since this function is typically unknown, blind deconvolution (BD) techniques are needed in order to produce a useful restored PET image. In this work, we propose a general BD technique that restores a low resolution blurry image using information from data acquired with a high resolution modality (e.g., CT-based delineation of regions with uniform activity in PET images). The proposed BD method is validated on synthetic and actual phantoms.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Blind deconvolution of turbulence-degraded images using natural PSF priors

Deconvolution of images taken through atmospheric turbulence often requires regularization in order to prevent the restoration algorithm over-fitting the noisy observation. For this purpose many object priors have been proposed but their utility might be limited to one class of real objects. Optical effects of atmospheric turbulence are well understood and therefore priors on the point-spread f...

متن کامل

Bayesian Blind Deconvolution with General Sparse Image Priors

We present a general method for blind image deconvolution using Bayesian inference with super-Gaussian sparse image priors. We consider a large family of priors suitable for modeling natural images, and develop the general procedure for estimating the unknown image and the blur. Our formulation includes a number of existing modeling and inference methods as special cases while providing additio...

متن کامل

A novel framework method for non-blind deconvolution using subspace images priors

Non-blind deconvolution has been an active challenge in the research fields of computer vision and computational photography. However, most existing deblurring methods conduct direct deconvolution only on the degraded image and are sensitive to noise. To enhance the performance of non-blind deconvolution, we propose a novel framework method by exploiting different sparse priors of subspace imag...

متن کامل

PSO-Optimized Blind Image Deconvolution for Improved Detectability in Poor Visual Conditions

Abstract: Image restoration is a critical step in many vision applications. Due to the poor quality of Passive Millimeter Wave (PMMW) images, especially in marine and underwater environment, developing strong algorithms for the restoration of these images is of primary importance. In addition, little information about image degradation process, which is referred to as Point Spread Function (PSF...

متن کامل

Blind deconvolution of images with model discrepancies using maximum a posteriori estimation with heavy-tailed priors

Single image blind deconvolution aims to estimate the unknown blur from a single observed blurred image and recover the original sharp image. Such task is severely ill-posed and typical approaches involve some heuristic or other steps without clear mathematical explanation to arrive at an acceptable solution. We show that a straightforward maximum a posteriori estimation incorporating sparse pr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1608.01896  شماره 

صفحات  -

تاریخ انتشار 2016