Voxel-wise Weighted MR Image Enhancement using an Extended Neighborhood Filter
نویسندگان
چکیده
We present an edge preserving and denoising filter for enhancing the features in images, which contain an ROI having a narrow spatial extent. Typical examples include angiograms, or ROI’s spatially distributed in multiple locations and contained within an outlying region, such as in multiple-sclerosis. The filtering involves determination of multiplicative weights in the spatial domain using an extended set of neighborhood directions. Equivalently, the filtering operation may be interpreted as a combination of directional filters in the frequency domain, with selective weighting for spatial frequencies contained within each direction. The advantages of the proposed filter in comparison to specialized non-linear filters, which operate on diffusion principle, are illustrated using numerical phantom data. The performance evaluation is carried out on simulated images from BrainWeb database for multiple-sclerosis, acute ischemic stroke using clinically acquired FLAIR images and MR angiograms.
منابع مشابه
Fast pseudo-CT synthesis from MRI T1-weighted images using a patch-based approach
MRI-based bone segmentation is a challenging task because bone tissue and air both present low signal intensity on MR images, making it difficult to accurately delimit the bone boundaries. However, estimating bone from MRI images may allow decreasing patient ionization by removing the need of patient-specific CT acquisition in several applications. In this work, we propose a fast GPU-based pseu...
متن کاملPredicting breakdown of the blood-brain barrier in multiple sclerosis without contrast agents.
BACKGROUND AND PURPOSE Disruption of the BBB in MS is associated with the development of new lesions and clinical relapses and signifies the presence of active inflammation. It is most commonly detected as enhancement on MR imaging performed with contrast agents that are costly and occasionally toxic. We investigated whether the BBB status in white matter lesions may be indirectly ascertained v...
متن کاملGaussian Intensity Model with Neighborhood Cues for Fluid-Tissue Categorization of Multi-Sequence MR Brain Images
This work presents an automatic brain MRI segmentation method which can classify brain voxels into one of three main tissue types: gray matter (GM), white matter (WM) and Cerebro-spinal fluid (CSF). Intensity-model based classification of MR images has proven problematic. The statistical approach does not carry any spatial, textural and neighborhood information in it. We propose to use a comput...
متن کاملImage Quality Enhancement Using Pixel Wise Gamma Correction
This paper presents a new automatic image enhancement method by modifying the gamma value of its individual pixels. Most of existing gamma correction methods apply a uniform gamma value across the image. Considering the fact that gamma variation for a single image is actually nonlinear, the proposed method locally estimates the gamma values in an image using support vector machine. First, a dat...
متن کاملFusing Markov Random Fields with Anatomical Knowledge and Shape-Based Analysis to Segment Multiple Sclerosis White Matter Lesions in Magnetic Resonance Images of the Brain
This paper proposes an image analysis system to segment multiple sclerosis lesions of magnetic resonance (MR) brain volumes consisting of 3 mm thick slices using three channels (images showing T1-, T2and PD -weighted contrast). The method uses the statistical model of Markov Random Fields (MRF) both at low and high levels. The neighborhood system used in this MRF is defined in three types: (1) ...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Visual Communication and Image Representation
دوره 25 شماره
صفحات -
تاریخ انتشار 2014