Evaluation of a module for the fusion of data on blood vessels from multiple sources.
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Carotid Arteries↗
Biomedical subjects
G P Robinson
Publications and source records attributed to G P Robinson.
Accurate combination of CT and MR data of the head: validation and applications in surgical and therapy planning.
A method is presented for the accurate combination of magnetic resonance (MR) and computed tomographic (CT) images of the head. Our technique is based on user identified 3D landmarks followed by data combination and display as adjacent slices, a single fused slice representation, colour overlay and three-dimensional (3D) rendered scenes. Validation with a point phantom and computer simulation has established the relationship of registration accuracy with point location accuracy, the number of points used and their spatial distribution. The technique is in clinical use in the planning of skull base surgery, transferring MR images acquired without a stereotaxic frame to stereotaxic space, and staging and planning therapy of nasopharyngeal tumours.
Computer Simulation↗
Medical image collection indexing: shape-based retrieval using KD-trees.
The capacity to retrieve images containing objects with shapes similar to a query shape is desirable in medical image databases. We propose a similarity measure and an indexing mechanism for non-rigid comparison of shape which adds this capability to image databases. The (dis-)similarity measure is based on the observations that: (1) the geometry of the same organ in different subjects is not related by a strictly rigid transformation; and (2) the orientation of the organ plays a key role in comparing shape. We propose a similarity measure that computes a non-rigid mapping between curves and uses this mapping to compare oriented shape. We also show how KD-trees can index curves so that retrieval with our similarity measure is efficient. Experiments with real-world data from a database of magnetic resonance images are provided.
Abstracting and Indexing↗
Computer-aided interpretation of SPECT images of the brain using an MRI-derived 3D neuro-anatomical atlas.
Nuclear medicine images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. A 3D neuro-anatomical atlas has been generated from the MRI data set of a normal, healthy volunteer to assist in the interpretation of nuclear medicine scans of the brain. Region growing and edge-detection techniques were used to semi-automatically segment the data set into the major tissue types within the brain. The atlas was then labelled interactively by marking points on each 2D slice. Anatomical structures useful in the interpretation of SPECT images were labelled. Additional, more detailed information corresponding to these structures is provided via an interactive index which allows access to images, diagrams and explanations. Registration of patient SPECT studies with the atlas is accomplished by using the position of the skull vertex and four external fiducial markers attached to the skin surface. The 3D coordinates determined from these points are used to calculate the transformation required to rotate, scale and translate the SPECT data, in 3D, to match the atlas. Corresponding 2D slices from the two 3D data sets are then displayed side-by-side on a computer screen. A cursor linking the two images allows the delineation of regions of interest (ROIs) in the SPECT scan based on anatomical structures identified from the atlas. Conversely regions of abnormal isotope distribution in the SPECT image can be localized by reference to corresponding structures in the atlas.
Brain↗