Biomedical subjects

P F Hemler

Publications and source records attributed to P F Hemler.

5 recordsLinked to original sources

PubMed1995

A versatile system for multimodality image fusion.

This paper presents a versatile system for registering and visualizing computed tomography and magnetic resonance images. The system utilizes a semi-automatic, surface-based registration strategy which has proven useful for registering a number of different anatomical structures. A triangular mesh approximates surfaces in one image set while a set of surface points is used as a surface approximation in the other set. A non-linear optimization procedure determines the transformation that minimizes the total sum-squared perpendicular distance between triangles of the mesh and surface points. This system has been used without modification to successfully register images of the brain, spine and calcaneus.

Brain↗

PubMed1995

Method for correcting magnetic resonance image distortion for frame-based stereotactic surgery, with preliminary results.

We previously described a technique for correcting patient-specific magnetic field inhomogeneity spatial distortion in magnetic resonance images (MRI), which was not applicable to patients fitted with MRI-compatible stereotactic fiducial frames. Here we describe an improvement to the technique that permits application for these patients. Measurements with a cadaver head show that this method achieves MRI stereotactic localization accuracy of 1 mm.

Head↗

PubMed1995

MR geometric distortion correction for improved frame-based stereotaxic target localization accuracy.

We present a method to correct the geometric distortion caused by field inhomogeneity in MR images of patients wearing MR-compatible stereotaxic frames. Our previously published distortion correction method derives patient-dependent error maps by computing the phase-difference of 3D images acquired at different TEs. The time difference (delta TE = 4.9 ms at 1.5 T) is chosen such that the water and fat signals are in phase. However, delta TE is long enough to permit phase wraps in the difference images for frequency offsets greater than 205 Hz. Phase unwrapping techniques resolve these only for connected structures; therefore, the phase difference for fiducial rods may be off by multiples of 2 pi relative to the head. We remove this uncertainty by using an additional single 2D phase-different image with delta TE = 1 ms (during which time no phase-wraps are typically expected) to determine the correct multiple of 2 pi for each rod. We tested our method in a cadaver and in a patient using CT as the gold standard. Targets in the frame coordinates were chosen from CT and compared with their locations in MR. Localizing errors using MR compared with CT were as large as 3.7 mm before correction and were reduced to less than 1.11 mm after correction.

Artifacts↗

PubMed1995

Registration error quantification of a surface-based multimodality image fusion system.

This paper presents a new reference data set and associated quantification methodology to assess the accuracy of registration of computerized tomography (CT) and magnetic-resonance (MR) images. Also described is a new semiautomatic surface-based system for registering and visualizing CT and MR images. The registration error of the system was determined using a reference data set that was obtained from a cadaver in which rigid fiducial tubes were inserted prior to imaging. Registration error was measured as the distance between an analytic expression for each fiducial tube in one image set and transformed samples of the corresponding tube obtained from the other. Registration was accomplished by first identifying surfaces of similar anatomic structures in each image set. A transformation that best registered these structures was determined using a nonlinear optimization procedure. Even though the root-mean-square (rms) distance at the registered surfaces was similar to that reported by other groups, it was found that rms distances for the tubes were significantly larger than the final rms distances between the registered surfaces. It was also found that minimizing rms distance at the surface did not minimize rms distance for the tubes.

Biophysical Phenomena↗

PubMedDate not supplied

Comparison and evaluation of retrospective intermodality brain image registration techniques.

PURPOSE: The primary objective of this study is to perform a blinded evaluation of a group of retrospective image registration techniques using as a gold standard a prospective, marker-based registration method. To ensure blindedness, all retrospective registrations were performed by participants who had no knowledge of the gold standard results until after their results had been submitted. A secondary goal of the project is to evaluate the importance of correcting geometrical distortion in MR images by comparing the retrospective registration error in the rectified images, i.e., those that have had the distortion correction applied, with that of the same images before rectification. METHOD: Image volumes of three modalities (CT, MR, and PET) were obtained from patients undergoing neurosurgery at Vanderbilt University Medical Center on whom bone-implanted fiducial markers were mounted. These volumes had all traces of the markers removed and were provided via the Internet to project collaborators outside Vanderbilt, who then performed retrospective registrations on the volumes, calculating transformations from CT to MR and/ or from PET to MR. These investigators communicated their transformations again via the Internet to Vanderbilt, where the accuracy of each registration was evaluated. In this evaluation, the accuracy is measured at multiple volumes of interest (VOIs), i.e., areas in the brain that would commonly be areas of neurological interest. A VOI is defined in the MR image and its centroid c is determined. Then, the prospective registration is used to obtain the corresponding point c' in CT or PET. To this point, the retrospective registration is then applied, producing c" in MR. Statistics are gathered on the target registration error (TRE), which is the distance between the original point c and its corresponding point c". RESULTS: This article presents statistics on the TRE calculated for each registration technique in this study and provides a brief description of each technique and an estimate of both preparation and execution time needed to perform the registration. CONCLUSION: Our results indicate that retrospective techniques have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.

Brain↗