Biomedical subjects

Chris J Taylor

Publications and source records attributed to Chris J Taylor.

5 recordsLinked to original sources

PubMed2005

Quantitative analysis of regional airways obstruction using dynamic hyperpolarized 3He MRI-preliminary results in children with cystic fibrosis.

PURPOSE: To investigate regional airways obstruction in patients with cystic fibrosis (CF) with quantitative analysis of dynamic hyperpolarized (HP) (3)He MRI. MATERIALS AND METHODS: Dynamic radial projection MRI of HP (3)He gas was used to study respiratory dynamics in a group of eight children with CF. Signal kinetics in a total of seven regions of interest (ROIs; three in each lung, and one in the trachea) were compared with the results of spirometric pulmonary function tests (PFTs). The tracheal signal intensity was used as a form of "input function" to normalize for input flow effects. RESULTS: A pattern of low flow rate in the upper lobes was observed. When the flow measurements from the peripheral ROIs were averaged to obtain an index of flow in the peripheral lung, a good correlation was found (P = 3.74 x 10(-5)) with the forced expired volume in one second (FEV1). CONCLUSION: These results suggest that a quantitative measurement of localized airways obstruction in the early stages of CF may be obtained from dynamic (3)He MRI by using the slope of the signal rise as a measure of air flow into the peripheral lung. This study also demonstrates that children can cooperate well with the (3)He MRI technique.

Adolescent↗

PubMed2005

Improved quantitative dynamic regional oxygen-enhanced pulmonary imaging using image registration.

Oxygen-enhanced MR imaging has been demonstrated in a number of recent studies as a potential method to visualize regional ventilation in the lung. A quantitative pixel-by-pixel analysis is hampered by motion and volume change due to breathing. In this study, image registration via active shape modeling is shown to produce significant improvements in the regional analysis of both static and dynamic oxygen-enhanced pulmonary MRI for five normal volunteers. The method enables the calculation of regional change in relaxation rate between breathing air and 100% oxygen, which is proportional to the change in regional oxygen concentration, and regional oxygen wash-in and wash-out time constants. Registration-corrected mapping of these parameters is likely to provide improved information in the regional assessment of a range of lung diseases.

Administration, Inhalation↗

PubMed2003

Shape discrimination in the hippocampus using an MDL model.

We extend recent work on building 3D statistical shape models, automatically, from sets of training shapes and describe an application in shape analysis. Using an existing measure of model quality, based on a minimum description length criterion, and an existing method of surface re-parameterisation, we introduce a new approach to model optimisation that is scalable, more accurate, and involves fewer parameters than previous methods. We use the new approach to build a model of the right hippocampus, using a training set of 82 shapes, manually segmented from 3D MR images of the brain. We compare the results with those obtained using another previously published method for building 3D models, and show that our approach results in a model that is significantly more specific, general, and compact. The two models are used to investigate the hypothesis that there are differences in hippocampal shape between age-matched schizophrenic and normal control subgroups within the training set. Linear discriminant analysis is used to find the combination of shape parameters that best separates the two subgroups. We perform an unbiased test that shows there is a statistically significant shape difference using either shape model, but that the difference is more significant using the model built using our approach. We show also that the difference between the two subgroups can be visualised as a mode of shape variation.

Algorithms↗

PubMed2003

Evaluation of 3D correspondence methods for model building.

The correspondence problem is of high relevance in the construction and use of statistical models. Statistical models are used for a variety of medical application, e.g. segmentation, registration and shape analysis. In this paper, we present comparative studies in three anatomical structures of four different correspondence establishing methods. The goal in all of the presented studies is a model-based application. We have analyzed both the direct correspondence via manually selected landmarks as well as the properties of the model implied by the correspondences, in regard to compactness, generalization and specificity. The studied methods include a manually initialized subdivision surface (MSS) method and three automatic methods that optimize the object parameterization: SPHARM, MDL and the covariance determinant (DetCov) method. In all studies, DetCov and MDL showed very similar results. The model properties of DetCov and MDL were better than SPHARM and MSS. The results suggest that for modeling purposes the best of the studied correspondence method are MDL and DetCov.

Algorithms↗

PubMed2002

A minimum description length approach to statistical shape modeling.

We describe a method for automatically building statistical shape models from a training set of example boundaries/surfaces. These models show considerable promise as a basis for segmenting and interpreting images. One of the drawbacks of the approach is, however, the need to establish a set of dense correspondences between all members of a set of training shapes. Often this is achieved by locating a set of "landmarks" manually on each training image, which is time consuming and subjective in two dimensions and almost impossible in three dimensions. We describe how shape models can be built automatically by posing the correspondence problem as one of finding the parameterization for each shape in the training set. We select the set of parameterizations that build the "best" model. We define "best" as that which minimizes the description length of the training set, arguing that this leads to models with good compactness, specificity and generalization ability. We show how a set of shape parameterizations can be represented and manipulated in order to build a minimum description length model. Results are given for several different training sets of two-dimensional boundaries, showing that the proposed method constructs better models than other approaches including manual landmarking-the current gold standard. We also show that the method can be extended straightforwardly to three dimensions.

Algorithms↗