Biomedical subjects

V A Saxena

Publications and source records attributed to V A Saxena.

4 recordsLinked to original sources

PubMed1999

CT and PET lung image registration and fusion in radiotherapy treatment planning using the chamfer-matching method.

PURPOSE: We present a validation study of CT and PET lung image registration and fusion based on the chamfer-matching method. METHODS AND MATERIALS: The contours of the lung surfaces from CT and PET transmission images were automatically segmented by the thresholding technique. The chamfer-matching technique was then used to register the extracted lung surfaces. Arithmetic means of distance between the two data sets of the pleural surfaces were used as the cost function. Matching was then achieved by iteratively minimizing the cost function through three-dimensional (3D) translation and rotation with an optimization method. RESULTS: Both anatomic thoracic phantom images and clinical patient images were used to evaluate the performance of our registration system. Quantitative analysis from five patients indicates that the registration error in translation was 2-3 mm in the transverse plane, 3-4 mm in the longitudinal direction, and about 1.5 degree in rotation. Typical computing time for chamfer matching is about 1 min. The total time required to register a set of CT and PET lung images, including contour extraction, was generally less than 30 min. CONCLUSION: We have implemented and validated the chamfer-matching method for CT and PET lung image registration and fusion. Our preliminary results show that the chamfer-matching method for CT and PET images in the lung area is feasible. The described registration system has been used to facilitate target definition and treatment planning in radiotherapy.

Aged↗

PubMed1998

A simple algorithm for planar image registration in radiation therapy.

A simple algorithm is presented for planar image registration and the method is applied to the simulator and portal image registration for patient setup verification in radiation therapy. Basically, the algorithm follows the concept proposed by Balter et al. [Med. Phys. 19, 329-334 (1992)], which converts the problem of open curve registration into matching a series of points along the curves. Balter's algorithm consists of three steps: (1) to determine a common starting point for each curve pair, (2) acquire two corresponding point sets along each curve, and (3) obtain a global transform matrix by matching two point sets. We integrate all three steps into one simple procedure which fits the sampled points along the intended curve pair by taking the relative path length shift as an independent fitting parameter. After being modified, the algorithm is able to take the different magnification factors of images into account, and it avoids curvature calculations. Numerical simulation as well as clinical and phantom images have been utilized to test the accuracy of the algorithm. The typical errors are less than 1 mm in translation and 1 degree in rotation. We also made a comparison study with the chamfer method. The results of the two methods agree to within 0.5 mm in translation and 0.5 degree in rotation.

Algorithms↗

PubMed1997

A method for more efficient source localization of interstitial implants with biplane radiographs.

The conventional method for source localization in an interstitial ribbon implant by means of biplane radiographs can be difficult, especially when a large number of seeds are involved. We present a new algorithm for more efficient source localization with the same conventional biplane radiographs. The method does not require a one-to-one source correspondence between two radiographs. The user needs only to digitize several points, following the shape of each ribbon from both films. The points that are digitized do not need to be the location of the seeds, and they do not have to correspond to the same points on both films. The algorithm uses the multidimensional minimization method to reconstruct the three-dimensional locus of the ribbon. The location of each seed is then determined by its pathlength relative to the corresponding starting point. We have used phantom experiments and clinical cases to test the reliability of the algorithm. The results show that the errors in the determination of seed locations are less than 2 mm, and the efficiency in source digitization for data entry can be increased by a factor up to 5.

Biophysical Phenomena↗

PubMed1996

Alignment of multi-segmented anatomical features from radiation therapy images by using least square fitting.

A least square fitting algorithm for alignment of multi-open-curved segments and point pairs of anatomical features obtained from both portal images and simulation radiographs has been developed for patient position verification in radiation therapy. A coordinate system associated with each curved segment pair is constructed so that the discrepancies of each segment pair can be obtained easily. The algorithm allows users to select not only multiple curve pairs but also individual point pairs on the important anatomic landmarks. The misregistration is measured by the sum of the position deviation of individual point pairs and ordinate discrepancies of all segment pairs from their corresponding coordinate systems. A mathematical minimization method is applied to seek an optimal transformation for matching of all segment and/or point pairs involved. The reliability of the algorithm has been tested with both phantom and clinical images. The test results indicate that the typical errors are less than 1 mm and 1 degrees in translation and rotation, respectively.

Algorithms↗