Showing papers in "Computerized Medical Imaging and Graphics in 2009"

TL;DR: A systematic overview of the recent border detection methods in the literature paying particular attention to computational issues and evaluation aspects is presented.

TL;DR: An improved region-based active contour model in a variational level set formulation that has been applied to brain MR image segmentation with desirable results and is presented as a two-phaselevel set formulation and then extended to a multi-phase formulation.

TL;DR: A technical review on computational methodologies developed for fcMRI analysis into model-driven and data-driven methods and their advantages and drawbacks are provided.

TL;DR: This work examined recent literature on digital image processing in the field of diabetic retinopathy and classified algorithms into a small number of categories, definition of terms and discussion of evolving techniques will provide guidance to algorithm designers for diabetic Retinopathy.

TL;DR: The proposed registration method reduced motion artifacts in the image time series and improved further analysis of the DCE-MRI data and might improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function in patients.

TL;DR: This work aims to improve the image quality of low-dose CT images using a novel AW nonlocal (adaptive-weighting nonlocal) prior statistical reconstruction approach that imposes an effective resolution-preserving and noise-removing regularization for reconstructions.

TL;DR: A surgical guide system was developed to accurately reproduce virtually planned bone sectioning procedures in animal models to obtain a perfect fit during surgery and produce a perfect-fitting bone substitute model for rapid prototyped hydroxyapatite (HA) scaffolds.

TL;DR: The method constructs 3D fences that separate adjacent vertebrae from valley-emphasized Gaussian images using a deformable model and a minimum cost path finding method corrects any erroneous curves trapped into a local minimum.

TL;DR: The performance of the automated methodology was better or similar to the manual method and its results were reproducible and it is expected to have a variety of applications in surgery planning and intra-operative navigation.

TL;DR: This paper extends the basic LBP histogram descriptor into a spatially enhanced histogram which encodes both the local region appearance and the spatial structure of the masses and shows that LBP are effective and efficient descriptors for mammographic masses.

TL;DR: The experiment results show that the repaired images can satisfy the requirement of medical diagnosis by the proposed algorithm and the segmentation veracity is effectively improved after repairing the hair-occluded information.

TL;DR: This paper evaluates the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization approach for both automated tumor and enhanced-tumor segmentation and shows that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

TL;DR: The presented results indicate that the use of non-rigid image registration to solve the point correspondence problem leads to improved ASMs and more accurate segmentation results.

TL;DR: A hybrid 3D image segmentation method which combines region growing and deformable models to obtain accurate and topologically preserving surface structures of anatomical objects of interest and achieves high quality segmentations with low computational complexity is described.

TL;DR: An improved three-dimensional (3D) scale invariant feature transform (SIFT) algorithm to globally register ultrasound volumes acquired from dedicated ultrasound probe, where local deformations are corrected by block-based warping algorithm.

TL;DR: A fully automated texture-based segmentation and recognition system for lesion and lungs from CT of thorax is presented and reveals an accuracy of delineation to be 94.06%, 94.32% and 89.04% for left lung, right lung and lesion, respectively.

TL;DR: A multi-step heuristic technique to segment liver from other tissues in multi-slice CT images based on anatomical knowledge of liver, its surrounding tissues as well as the approach that a clinician follows in screening liver in a CT dataset is developed.

TL;DR: A variational level set approach to bias correction and segmentation for images with intensity inhomogeneities, which is able to capture bias of quite general profiles and is robust to initialization, and thereby allows fully automated applications.

TL;DR: A new approach to analyze tongue color based on spectra with spectral angle mapper is presented and it is shown that this new color analysis approach is superior to the traditional method especially in achieving meaningful areas of substances and coatings of tongue.

TL;DR: A computer-based classification scheme that utilized various morphological and novel wavelet-based features towards malignancy risk evaluation of thyroid nodules in ultrasonography is presented.

TL;DR: The obtained results demonstrate that the proposed approach provides objective and reproducible segmentations that are similar to the manually obtained results and the processing time of the proposed method is about 4 min compared to the 10 min required for manual segmentation.

TL;DR: In this paper, the authors investigated the application of texture analysis of the intima-media thickness (IMT) of the common carotid artery (CCA) and how texture is affected by age and gender.

TL;DR: New, fully automated algorithm for airway tree segmentation based on high-resolution multidetector computed tomography (MDCT) chest scans is presented and it is proved that it detects up to 10 generations of bronchi and diminishes leakages into the lung parenchyma which are common when simple region growing is used for segmentingAirway tree.

TL;DR: Preliminary results obtained from the phantom and a subject's forearm demonstrated that the proposed algorithm was able to well suppress speckles and preserve edges in 3D images.

TL;DR: This paper provides for an inventive algorithm for the holistic extraction of gallbladder image contours based on rank filtration, as well as on the analysis of histogram sections on tested organs.

TL;DR: It is found that machining cortical bone segments prior to CT scanning is an effective method for accuracy evaluation of CT-based bone reconstruction and can provide a reference for assessing the sensitivity, reliability and accuracy ofCT-based applications in the study of movement, finite element modeling, and prosthesis construction.

TL;DR: A comprehensive review of the literature in this evolving field of medical imaging particularly focusing on three-dimensional analysis of facial movement and outlining the current concepts in objective analysis of the data set is provided.

TL;DR: Tests and a comparison with the method of non-parametric non-uniform intensity normalization (N3) indicate that the method is effective in background intensity inhomogeneity correction and may have a slight edge over the N3 method.

TL;DR: The problem of computer vision-guided reconstruction of a fractured human mandible from a computed tomography image sequence exhibiting multiple broken fragments is addressed and a polynomial time solution using graph matching is proposed.

TL;DR: The effectiveness of the method in enhancing the visibility of a prosthetic case was quantified in terms of removal of ghosting artifacts and the potential of artifact reduction processing for digital linear tomosynthesis in the evaluation of hip prostheses was demonstrated.