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At least 577 records · Page 32Linked to original sources
PubMed2006

An interactive three-dimensional virtual body structures system for anatomical training over the internet.

The Visible Human digital datasets make it possible to develop computer-based anatomical training systems that use virtual anatomical models (virtual body structures-VBS). Medical schools are combining these virtual training systems and classical anatomy teaching methods that use labeled images and cadaver dissection. In this paper we present a customizable web-based three-dimensional anatomy training system, W3D-VBS. W3D-VBS uses National Library of Medicine's (NLM) Visible Human Male datasets to interactively locate, explore, select, extract, highlight, label, and visualize, realistic 2D (using axial, coronal, and sagittal views) and 3D virtual structures. A real-time self-guided virtual tour of the entire body is designed to provide detailed anatomical information about structures, substructures, and proximal structures. The system thus facilitates learning of visuospatial relationships at a level of detail that may not be possible by any other means. The use of volumetric structures allows for repeated real-time virtual dissections, from any angle, at the convenience of the user. Volumetric (3D) virtual dissections are performed by adding, removing, highlighting, and labeling individual structures (and/or entire anatomical systems). The resultant virtual explorations (consisting of anatomical 2D/3D illustrations and animations), with user selected highlighting colors and label positions, can be saved and used for generating lesson plans and evaluation systems. Tracking users' progress using the evaluation system helps customize the curriculum, making W3D-VBS a powerful learning tool. Our plan is to incorporate other Visible Human segmented datasets, especially datasets with higher resolutions, that make it possible to include finer anatomical structures such as nerves and small vessels.

Anatomy↗
PubMed2006

Three-dimensional reconstruction of registered and fused Chinese Visible Human and patient MRI images.

Radiological images are commonly used as important tools in medical diagnoses and treatment. Different modalities of medical images provide uniquely different content. Hence, it is natural and desirable to combine different image modalities to obtain additional new information to enhance clinical assessment. However, given the current technology, radiological images are not always sufficiently informative to permit diagnosis and treatment. In order to address this problem, we fused selected portions of the Chinese Visible Human (CVH) dataset with MRI images from a patient. Specifically, we segmented the caudate nucleus, the lentiform nucleus, and the thalamus in the CVH dataset and then registered and fused this dataset with corresponding MRI images using both rigid and nonrigid registration techniques. After rigid and nonrigid registration, the CVH and MRI images largely coincided with each other. The shape, relationship, and position of focal areas and neural structures were clearly displayed. Using volume and surface rendering, these images were three-dimensionally reconstructed to display the neural structures of interest within the brain. These structures can be rotated at will and observed from different angles. Our research indicates that the fusion of CVH and patients' MRI images can enhance the amount of neural information available to physicians and lay a foundation for the clinical use of the CVH dataset.

Asian People↗
PubMed2006

Linkage analysis with gene-environment interaction: model illustration and performance of ordered subset analysis.

The ordered subset analysis (OSA) method allows for the incorporation of covariates into the linkage analysis of a dichotomous disease phenotype in order to reduce genetic heterogeneity. Complex human diseases may involve gene-environment (G x E) interactions, which represent a special form of heterogeneity. Here, we present results of a simulation study to evaluate the performance of OSA when the disease-generating mechanism includes G x E interaction, in the absence of main effects of gene and environment. First, the complex simulation models are illustrated graphically. Second, we show that OSA is underpowered to detect small to moderate interaction effects, consistent with previous evaluations of other linkage analysis methods. When interaction effects are large enough to produce substantial marginal effects, standard linkage methods have sufficient power to detect significant baseline linkage evidence in the entire dataset. The power of OSA to improve upon a high baseline lod score is then strongly dependent on the underlying genetic model, especially the susceptibility allele frequency. If significant, OSA identifies family subsets that are more efficient for follow-up analysis than the entire dataset, in terms of the proportion of susceptible genotypes among generated marker genotypes. For example, when strong G x E interaction with RR(G x E) = 10 is operating in at least 70% of families in the dataset, OSA has at least 70% power to detect a subset of families with significantly greater linkage evidence, the majority of linked families are captured in the OSA subset, and the per-genotype efficiency in the subset is 20-30% greater than in the entire dataset.

Chromosome Mapping↗
PubMed2004

Method for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error.

This work presents a new algorithm (nonuniform intensity correction; NIC) for correction of intensity inhomogeneities in T1-weighted magnetic resonance (MR) images. The bias field and a bias-free image are obtained through an iterative process that uses brain tissue segmentation. The algorithm was validated by means of realistic phantom images and a set of 24 real images. The first evaluation phase was based on a public domain phantom dataset, used previously to assess bias field correction algorithms. NIC performed similar to previously described methods in removing the bias field from phantom images, without introduction of degradation in the absence of intensity inhomogeneity. The real image dataset was used to compare the performance of this new algorithm to that of other widely used methods (N3, SPM'99, and SPM2). This dataset included both low and high bias field images from two different MR scanners of low (0.5 T) and medium (1.5 T) static fields. Using standard quality criteria for determining the goodness of the different methods, NIC achieved the best results, correcting the images of the real MR dataset, enabling its systematic use in images from both low and medium static field MR scanners. A limitation of our method is that it might fail if the bias field is so high that the initial histogram does not show bimodal distribution for white and gray matter.

Algorithms↗
PubMed2006

Quantitative evaluation of automated skull-stripping methods applied to contemporary and legacy images: effects of diagnosis, bias correction, and slice location.

Performance of automated methods to isolate brain from nonbrain tissues in magnetic resonance (MR) structural images may be influenced by MR signal inhomogeneities, type of MR image set, regional anatomy, and age and diagnosis of subjects studied. The present study compared the performance of four methods: Brain Extraction Tool (BET; Smith [2002]: Hum Brain Mapp 17:143-155); 3dIntracranial (Ward [1999] Milwaukee: Biophysics Research Institute, Medical College of Wisconsin; in AFNI); a Hybrid Watershed algorithm (HWA, Segonne et al. [2004] Neuroimage 22:1060-1075; in FreeSurfer); and Brain Surface Extractor (BSE, Sandor and Leahy [1997] IEEE Trans Med Imag 16:41-54; Shattuck et al. [2001] Neuroimage 13:856-876) to manually stripped images. The methods were applied to uncorrected and bias-corrected datasets; Legacy and Contemporary T1-weighted image sets; and four diagnostic groups (depressed, Alzheimer's, young and elderly control). To provide a criterion for outcome assessment, two experts manually stripped six sagittal sections for each dataset in locations where brain and nonbrain tissue are difficult to distinguish. Methods were compared on Jaccard similarity coefficients, Hausdorff distances, and an Expectation-Maximization algorithm. Methods tended to perform better on contemporary datasets; bias correction did not significantly improve method performance. Mesial sections were most difficult for all methods. Although AD image sets were most difficult to strip, HWA and BSE were more robust across diagnostic groups compared with 3dIntracranial and BET. With respect to specificity, BSE tended to perform best across all groups, whereas HWA was more sensitive than other methods. The results of this study may direct users towards a method appropriate to their T1-weighted datasets and improve the efficiency of processing for large, multisite neuroimaging studies.

Adult↗
PubMed2004

Predicting subcellular localization of proteins by hybridizing functional domain composition and pseudo-amino acid composition.

Recent advances in large-scale genome sequencing have led to the rapid accumulation of amino acid sequences of proteins whose functions are unknown. Since the functions of these proteins are closely correlated with their subcellular localizations, many efforts have been made to develop a variety of methods for predicting protein subcellular location. In this study, based on the strategy by hybridizing the functional domain composition and the pseudo-amino acid composition (Cai and Chou [2003]: Biochem. Biophys. Res. Commun. 305:407-411), the Intimate Sorting Algorithm (ISort predictor) was developed for predicting the protein subcellular location. As a showcase, the same plant and non-plant protein datasets as investigated by the previous investigators were used for demonstration. The overall success rate by the jackknife test for the plant protein dataset was 85.4%, and that for the non-plant protein dataset 91.9%. These are so far the highest success rates achieved for the two datasets by following a rigorous cross validation test procedure, further confirming that such a hybrid approach may become a very useful high-throughput tool in the area of bioinformatics, proteomics, as well as molecular cell biology.

Algorithms↗
PubMed2005

In search of the vertebrate phylotypic stage: a molecular examination of the developmental hourglass model and von Baer's third law.

In 1828, Karl von Baer proposed a set of four evolutionary "laws" pertaining to embryological development. According to von Baer's third law, young embryos from different species are relatively undifferentiated and resemble one another but as development proceeds, distinguishing features of the species begin to appear and embryos of different species progressively diverge from one another. An expansion of this law, called "the hourglass model," has been proposed independently by Denis Duboule and Rudolf Raff in the 1990s. According to the hourglass model, ontogeny is characterized by a starting point at which different taxa differ markedly from one another, followed by a stage of reduced intertaxonomic variability (the phylotypic stage), and ending in a von-Baer-like progressive divergence among the taxa. A possible "translation" of the hourglass model into molecular terminology would suggest that orthologs expressed in stages described by the tapered part of the hourglass should resemble one another more than orthologs expressed in the expansive parts that precede or succeed the phylotypic stage. We tested this hypothesis using 1,585 mouse genes expressed during 26 embryonic stages, and their human orthologs. Evolutionary divergence was estimated at different embryonic stages by calculating pairwise distances between corresponding orthologous proteins from mouse and human. Two independent datasets were used. One dataset contained genes that are expressed solely in a single developmental stage; the second was made of genes expressed at different developmental stages. In the second dataset the genes were classified according to their earliest stage of expression. We fitted second order polynomials to the two datasets. The two polynomials displayed minima as expected from the hourglass model. The molecular results suggest, albeit weakly, that a phylotypic stage (or period) indeed exists. Its temporal location, sometimes between the first-somites stage and the formation of the posterior neuropore, was in approximate agreement with the morphologically defined phylotypic stage. The molecular evidence for the later parts of the hourglass model, i.e., for von Baer's third law, was stronger than that for the earlier parts.

Animals↗
PubMed2005

Evaluation of gestational age and admission date assumptions used to determine prenatal drug exposure from administrative data.

OBJECTIVE: Our aim was to evaluate the 270-day gestational age and delivery date assumptions used in an administrative dataset study assessing prenatal drug exposure compared to information contained in a birth registry. STUDY DESIGN AND SETTING: Kaiser Permanente Colorado (KPCO), a member of the Health Maintenance Organization (HMO) Research Network Center for Education and Research in Therapeutics (CERTs), previously participated in a CERTs study that used claims data to assess prenatal drug exposure. In the current study, gestational age and deliveries information from the CERTs study dataset, the Prescribing Safely during Pregnancy Dataset (PSDPD), was compared to information in the KPCO Birth Registry. Sensitivity and positive predictive value (PPV) of the claims data for deliveries were assessed. The effect of gestational age and delivery date assumptions on classification of prenatal drug exposure was evaluated. RESULTS: The mean gestational age in the Birth Registry was 273 (median = 275) days. Sensitivity of claims data at identifying deliveries was 97.6%, PPV was 98.2%. Of deliveries identified in only one dataset, 45% were related to the gestational age assumption and 36% were due to claims data issues. The effect on estimates of prevalence of prescribing during pregnancy was an absolute change of 1% or less for all drug exposure categories. For Category X, drug exposures during the first trimester, the relative change in prescribing prevalence was 13.7% (p = 0.014). CONCLUSION: Administrative databases can be useful for assessing prenatal drug exposure, but gestational age assumptions can result in a small proportion of misclassification.

Databases, Factual↗
PubMed2005

Large-scale prediction of function shift in protein families with a focus on enzymatic function.

Protein function shift can be predicted from sequence comparisons, either using positive selection signals or evolutionary rate estimation. None of the methods have been validated on large datasets, however. Here we investigate existing and novel methods for protein function shift prediction, and benchmark the accuracy against a large dataset of proteins with known enzymatic functions. Function change was predicted between subfamilies by identifying two kinds of sites in a multiple sequence alignment: Conservation-Shifting Sites (CSS), which are conserved in two subfamilies using two different amino acid types, and Rate-Shifting Sites (RSS), which have different evolutionary rates in two subfamilies. CSS were predicted by a new entropy-based method, and RSS using the Rate-Shift program. In principle, the more CSS and RSS between two subfamilies, the more likely a function shift between them. A test dataset was built by extracting subfamilies from Pfam with different EC numbers that belong to the same domain family. Subfamilies were generated automatically using a phylogenetic tree-based program, BETE. The dataset comprised 997 subfamily pairs with four or more members per subfamily. We observed a significant increase in CSS and RSS for subfamily comparisons with different EC numbers compared to cases with same EC numbers. The discrimination was better using RSS than CSS, and was more pronounced for larger families. Combining RSS and CSS by discriminant analysis improved classification accuracy to 71%. The method was applied to the Pfam database and the results are available at http://FunShift.cgb.ki.se. A closer examination of some superfamily comparisons showed that single EC numbers sometimes embody distinct functional classes. Hence, the measured accuracy of function shift is underestimated.

Amino Acid Sequence↗
PubMed2006

Rough set-based proteochemometrics modeling of G-protein-coupled receptor-ligand interactions.

G-Protein-coupled receptors (GPCRs) are among the most important drug targets. Because of a shortage of 3D crystal structures, most of the drug design for GPCRs has been ligand-based. We propose a novel, rough set-based proteochemometric approach to the study of receptor and ligand recognition. The approach is validated on three datasets containing GPCRs. In proteochemometrics, properties of receptors and ligands are used in conjunction and modeled to predict binding affinity. The rough set (RS) rule-based models presented herein consist of minimal decision rules that associate properties of receptors and ligands with high or low binding affinity. The information provided by the rules is then used to develop a mechanistic interpretation of interactions between the ligands and receptors included in the datasets. The first two datasets contained descriptors of melanocortin receptors and peptide ligands. The third set contained descriptors of adrenergic receptors and ligands. All the rule models induced from these datasets have a high predictive quality. An example of a decision rule is "If R1_ligand(Ethyl) and TM helix 2 position 27(Methionine) then Binding(High)." The easily interpretable rule sets are able to identify determinative receptor and ligand parts. For instance, all three models suggest that transmembrane helix 2 is determinative for high and low binding affinity. RS models show that it is possible to use rule-based models to predict ligand-binding affinities. The models may be used to gain a deeper biological understanding of the combinatorial nature of receptor-ligand interactions.

Algorithms↗
PubMed2006

Two-stage support vector regression approach for predicting accessible surface areas of amino acids.

We address the problem of predicting solvent accessible surface area (ASA) of amino acid residues in protein sequences, without classifying them into buried and exposed types. A two-stage support vector regression (SVR) approach is proposed to predict real values of ASA from the position-specific scoring matrices generated from PSI-BLAST profiles. By adding SVR as the second stage to capture the influences on the ASA value of a residue by those of its neighbors, the two-stage SVR approach achieves improvements of mean absolute errors up to 3.3%, and correlation coefficients of 0.66, 0.68, and 0.67 on the Manesh dataset of 215 proteins, the Barton dataset of 502 nonhomologous proteins, and the Carugo dataset of 338 proteins, respectively, which are better than the scores published earlier on these datasets. A Web server for protein ASA prediction by using a two-stage SVR method has been developed and is available (http://birc.ntu.edu.sg/~ pas0186457/asa.html).

Amino Acids↗
PubMed2005

Prenatal diagnosis of congenital heart disease using four-dimensional spatio-temporal image correlation (STIC) telemedicine via an Internet link: a pilot study.

OBJECTIVE: To assess whether the spatio-temporal image correlation (STIC) acquisition technique can be taught to a general obstetrician by e-mail; whether STIC volume datasets can be transmitted over the Internet; and whether STIC volume datasets analyzed offline at a remote setting can be used to confirm or exclude major cardiac defects (TELE-STIC). METHODS: This was a prospective study involving 50 pregnant women with gestational ages ranging between 20 and 36 weeks. These patients were selected by two general obstetricians (operators) working in geographically remote areas of Chile. Although both obstetricians were users of equipment capable of four-dimensional (4D) ultrasound with STIC, they lacked skill in the performance of fetal cardiac examination. A dedicated web disk was created to upload the acquired volume datasets using an Internet broadband connection. Offline analysis was performed by a single investigator experienced in fetal echocardiography (the administrator). RESULTS: A telemedicine link via the Internet was possible in all cases. Seventy-seven volume datasets were sent to the web server. A complete cardiac examination according to set criteria was achieved by the administrator in 86% of the cases scanned by one operator and 95% of the cases scanned by the other operator. Three patients had cardiac defects confirmed postnatally, two fetuses had extracardiac anomalies and one fetus had a suspected cardiac defect unconfirmed by second-opinion TELE-STIC. There were two isolated major congenital heart defects. Both patients were given advice by e-mail and teleconference using a web camera about the likely outcome and benefits of scheduling in utero transport to a tertiary care center. CONCLUSIONS: STIC volumes can be obtained by operators inexperienced in fetal echocardiography, transmitted via the Internet, and their analysis enables recognition of most of the structures and views necessary to assess fetal cardiac anatomy. The preliminary use of TELE-STIC allowed us to demonstrate that some intracardiac anomalies can be ruled out and others confirmed, allowing perinatal management to be tailored accordingly.

Chile↗
PubMed2000

Phylogenetic analyses of the rhipicephaline ticks indicate that the genus Rhipicephalus is paraphyletic.

We inferred the phylogeny of 21 species and subspecies of ticks from the subfamilies Rhipicephalinae and Hyalomminae using cytochrome c oxidase subunit I (COI) and 12S rRNA mitochondrial gene sequences. Two members of the subfamily Haemaphysalinae were used for outgroup reference. The largest rhipicephaline genus, Rhipicephalus, was represented by ticks from six of the species groups, the second largest genus, Dermacentor, by species from two of three of its subgenera, and the genus Boophilus by 3 of its 5 species. We analyzed the 12S and COI sequences separately and together; statistically significant incongruence between the 12S rDNA and the COI sequences was not detected in the combined dataset using the incongruence length difference test. The combined dataset provided greater phylogenetic resolution than the individual datasets, and although the 12S rDNA data had only 25% of the parsimony-informative characters, it provided half of the total partitioned Bremer support for the combined dataset. We present the first hypothesis of phylogenetic relationships among some species groups of Rhipicephalus but our most controversial result was that the genus Rhipicephalus is apparently paraphyletic, unless species of Boophilus are included in it. The species of Rhipicephalus most closely related to Boophilus spp. were from the R. pravus and R. evertsi species groups, which may implicate an African origin for this important group of ticks.

Animals↗
PubMed2005

The BrainIT Group: concept and current status 2004.

INTRODUCTION: An open collaborative international network has been established which aims to improve inter-centre standards for collection of high-resolution, neurointensive care data on patients with traumatic brain injury. The group is also working towards the creation of an open access, detailed and validated database that will be useful for hypothesis generation. In Part A, we describe the underlying concept of the group and it's aims and in Part B we describe the current status of the groups development. METHODS: Four group meetings funded by the EEC have enabled definition of a "Core Dataset" to be collected from all centres regardless of specific project aim. A form based feasibility study was conducted and a prospective data collection exercise of core data using PC and hand held computer based methods is in progress. FINDINGS: A core-dataset was defined and can be downloaded from the BrainIT web-site (go to "Core dataset" link at: www.brainit.org). A form based feasibility study was conducted showing the overall feasibility for collection of the core data elements was high. Software tools for collection of the core dataset have been developed. Currently, 130 patient's data from 16 European centres have been recruited to the joint database as part of an EEC funded proof of concept study. INTERPRETATION: The BrainIT network provides a more standardised and higher resolution data collection mechanism for research groups, organisations and the device industry to conduct multicentre trials of new health care technology in patients with traumatic brain injury.

Brain Injuries↗
PubMed2002

[Sources of error and risks in CT based navigation].

Based on the experience of 4 cervical, 102 thoracic/lumbar pedicle screw and 14 transiliosacral screw implantations all problems and complications were collected. Problems noted within the data collection in the preoperative CT were an incomplete acquisition of the surgical target (n = 3), an exceeding of the processable scan slices (n = 1) and a non focused field of view. Transmission of the CT datas often were documented as incomplete (n = 16). Segmentation of the CT dataset turned out to be the significant problem with incorrect differentiation of the bone-soft tissue transition (n = 2), where as the choice of the matching points and the trajectories did not provoke any mistakes in the planning modus. The intraoperative matching of both corresponding datasets was insufficient (n = 7), while the assignment of the CT dataset to the correct vertebral was not a major problem (n = 1). Navigation was not possible (n = 2) due to an instability of the spinal process. All fiducial based matching procedures (pelvis) were carried out without any problems. During intraoperative navigation potential complications resulted from deformation of instruments (n = 1) and interaction of instruments and the data reference base (n = 2). Further, the CT-based navigation of fractured vertebrae or unstable iliosacral joints is not safe, because dislocations between acquisition of the dataset and operation will lead to misguidance.

Artifacts↗
PubMed2005

A collection of amino acid replacement matrices derived from clusters of orthologs.

Sequence divergence among orthologous proteins was characterized with 34 amino acid replacement matrices, sequence context analysis, and a phylogenetic tree. The model was trained on very large datasets of aligned protein sequences drawn from 15 organisms including protists, plants, Dictyostelium, fungi, and animals. Comparative tests with models currently used in phylogeny, i.e., with JTT+gamma+/-F and WAG+gamma+/-F, made on a test dataset of 380 multiple alignments containing protein sequences from all five of the major taxonomic groups mentioned, indicate that our model should be preferred over the JTT+gamma+/-F and WAG+gamma+/-F models on datasets similar to the test dataset. The strong performance of our model of orthologous protein sequence divergence can be attributed to its ability to better approximate amino acid equilibrium frequencies to compositions found in alignment columns.

Amino Acid Substitution↗
PubMed2025

Support vector machine classification of 18F-FDG PET scans across subtypes of amyotrophic lateral sclerosis.

PURPOSE: While 18F-FDG PET imaging has demonstrated diagnostic value in people with Amyotrophic Lateral Sclerosis (PwALS) and group-level differences were identified between different disease subtypes (e.g., genetic and clinical variants), refining and validating a machine-learning-based subject-level diagnostic algorithm may improve the general applicability and reliability of 18F-FDG PET as a diagnostic tool in ALS. In this study, we employed support vector machines (SVM) to further explore the diagnostic potential of 18F-FDG PET in ALS, alongside its ability to classify between different genetic subtypes or clinical phenotypes. METHODS: 18F-FDG PET data of 36 healthy volunteers (HV), 25 people with ALS-mimicking diseases (Mimics), and 167 PwALS, grouped by genetic status (e.g., sporadic (sALS) or carrying a C9orf72 hexanucleotide repeat expansion (ALSC9orf72RE) and onset (bulbar or spinal) type, acquired with Biograph 'TruePoint' PET/CT scanner, were included in the study (Dataset 1). A second dataset of 183 PwALS and 31 Mimics acquired with Biograph 'HiRez' scanner was included as an independent cross-validation set (Dataset 2). PET images were spatially normalised to MNI space to fit linear SVMs with cross-validation. Only age-matched groups were considered to eliminate age-related effects. RESULTS: For Dataset 1, the linear SVM resulted in an average accuracy of 0.86 for the classification of ALS vs. HV, 0.53 for ALS vs. Mimics, 0.83 for ALSC9orf72RE vs. sALS, and 0.58 for bulbar vs. spinal onset. These findings were corroborated with Dataset2, with an accuracy of up to 0.76 for ALSC9orf72RE vs. sALS, and 0.59 for bulbar vs. spinal. CONCLUSION: 18F-FDG brain PET imaging, combined with SVM and age-matching, can distinguish between ALSC9orf72RE and sALS with good accuracy, but lacks sufficient discriminative power to differentiate between ALS and Mimics and between different sites of onset.

Humans↗
PubMed2007

The effect of dose reduction and feasibility of edge-preserving noise reduction on the detection of liver lesions using MSCT.

The purpose of this study was to assess the effect of dose reduction and the potential of noise reduction filters on image quality and the detection of liver lesions using MSCT. Twenty-nine patients with a total of 40 liver lesions underwent 16-slice CT (120 kV; 180 mAs). Virtual noise was added to CT raw datasets simulating effective mAs levels of 155, 130, 105, 80, 55, 30 and 10 mAs. All datasets were post-processed with an edge-preserving noise-reduction filter (ANR-3D), yielding a total of 15 datasets per patient. Ten radiologists performed independent evaluations of image quality, the presence of liver lesions and diagnostic confidence. Quantitative noise and contrast-to-noise ratios (CNR) were obtained. Superior image quality (P < 0.02), reduction of image noise (P < 0.001) and the increase of lesion-to-liver CNR (P < 0.001) were observed in images processed with the ANR-3D filter. Sensitivity for lesion detection remained unchanged down to 105 mAs (CTDI(w) 6.6 mGy) without filter and 80 mAs (CTDI(w) 5.1 mGy) with ANR-3D. Confidence was rated significantly higher for datasets reconstructed with ANR-3D. The use of a noise-reducing, but edge-preserving filter (ANR-3D) is a promising option to reduce further the radiation dose in liver CT.

Adult↗