Picker International, Inc.

The Cleveland Clinic Foundation

Christopher H Wood

Gene H Barnett

Patrick A Dayton

Anthony Apicella

Moriel S NessAiver

Quan Min Shao

Fares Hajjar

Kevin E Matthews

Elizabeth M D'addio

Bryan Clair Hoke

A position signaling is usable in connection with an image guided surgery system. A plurality of infrared emitters are mounted on a reference object. The reference object is in turn attached to the rocker arm of a head clamp. The head clamp includes a frame and a first head engaging pin secured to one side of the frame. The rocker arm includes two head engaging pins and is movable in relation to the frame. The image guided surgery system uses the signals provided by the infrared emitters to determine and account for movement of the patient's head.

Apparatus for anatomical tracking

A surgical guide for use with an image guided surgery includes first and second surfaces. At least three signaling devices such as infrared emitters are disposed on the first surface, and a cylindrical mounting boss is disposed on the second surface. A guide aperture is perpendicular to the first and second surfaces and extends between them. The guide aperture is configured to support a surgical tool such as a biopsy needle. A sleeve may be placed in the aperture to support additional tools.

Trackable guide block

A magnetic resonance imaging system (A) generates an image (16) of a slice or other region of an examined subject. A smoothing filter (B) smooths the generated image to create a smoothed or filtered image representation (30). The filtering of the image, unfortunately, tends to smooth or blur the edges. An edge detecting means (C.sub.1) views the region around each sampled pixel of the filtered image to determine an amount of deviation in the pixel values. A large deviation indicates an edge; whereas, substantial homogeneity indicates the lack of an edge. Analogously, the direction of the maximum deviation is orthogonal to the direction of the edge. A plurality of soft edge directional filters (54) operate on the filtered image data to create a plurality of soft edge directionally filtered image representations (62). A plurality of hard edge directional filters (56) operate on the filtered image data to create a plurality of hard edge directionally filtered image representations (64). Preferably, the directional filtering is done at regular angular increments, e.g. every ten degrees. An edge enhanced final image representation (72) is created in which filtered pixels not adjacent an edge are assembled directly from the filtered image (30). Pixels which are adjacent an edge with a smaller (larger) rate of deviation are replaced by the corresponding pixel of the soft (hard) edge filtered image representation that was directionally filtered along a direction most nearly parallel to the determined edge direction.

Concurrent smoothing and edge enhancement of medical diagnostic images

A CT scanner or other medical diagnostic imager (A) generates data which is reconstructed (B) into a three-dimensional image representation that is stored in an image memory (C). Points on a surface (10) of a selected subregion, such as the surface of an internal organ, in the three-dimensional image representation are determined (12) which are visible from and correspond to pixels on a viewing plane (14). For each viewable point on the surface, a mean variation along an x, y, and z-coordinate system with its origin at the surface point in question is determined (20). A covariance matrix whose matrix elements along the diagonal are indicative of a rate of variance along each axis and whose other matrix values are indicative of a rate of variance relative to pairs of axes is defined (20). A rate of most rapid change through the 3D data is determined (22), by eigenvalue decomposition (24) of the covariance matrix. A vector along the rate of most rapid change is normalized (26). Gray scale shading for a pixel of a man-readable display (E) corresponding to the surface point is determined (28). In the preferred embodiment, the gray scale shading is proportional to the cosine of the angle between the normalized vector in a direction of most rapid gray scale change and a light source vector. In this manner, the surface normal to a surface at the points which correspond to each pixel of an image display are efficiently determined and provided with an appropriate gray scale value to make the two-dimensional image display appear as if it were three-dimensional.

Accurate estimation of surface normals in 3-D data sets

A first image (20) and a second image (22) are taken through the patient's heart region at small time displaced intervals. The first and second images are subtracted (24) to generate a difference image which is indicative of the tissue which has moved during the short time interval, i.e. the boundary of the ventricles. Voxels from regions outside the boundary are adjusted to remove lung tissue (40), and ventricle boundary or edge voxels (48) and analyzed to generate a non-blood tissue histogram (62). Voxels within the boundary are analyzed to generate a blood tissue histogram (60). The histograms are fit (66, 74) to smooth curves which represent the probability distribution or confidence that each voxel value represents blood or non-blood tissue. Contiguous voxels within the boundary are counted (96) and adjusted for voxel size (98) to create an indication of left and right ventricle volume (100l, 100r). In the preferred embodiment, the ventricle volume is determined by summing the confidence value that each voxel within the boundary represents blood.

Growing community of inventors

Cleveland, OH, United States of America

Christopher H Wood