This paper reports a novel method to track brain shift using a laser-range scanner (LRS) and nonrigid registration techniques. The LRS used in this paper is capable of generating textured point-clouds describing the surface geometry/intensity pattern of the brain as presented during cranial surgery. Using serial LRS acquisitions of the brain's surface and two-dimensional (2-D) nonrigid image registration, we developed a method to track surface motion during neurosurgical procedures. A series of experiments devised to evaluate the performance of the developed shifttracking protocol are reported. In a controlled, quantitative phantom experiment, the results demonstrate that the surface shift-tracking protocol is capable of resolving shift to an accuracy of approximately 1.6 mm given initial shifts on the order of 15 mm. Furthermore, in a preliminary in vivo case using the tracked LRS and an independent optical measurement system, the automatic protocol was able to reconstruct 50% of the brain shift with an accuracy of 3.7 mm while the manual measurement was able to reconstruct 77% with an accuracy of 2.1 mm. The results suggest that a LRS is an effective tool for tracking brain surface shift during neurosurgery.
Abstract-In this paper, we present the segmentation of the head and neck lymph node regions using a new active contour-based atlas registration model. We propose to segment the lymph node regions without directly including them in the atlas registration process; instead, they are segmented using the dense deformation field computed from the registration of the atlas structures with distinct boundaries. This approach results in robust and accurate segmentation of the lymph node regions even in the presence of significant anatomical variations between the atlas-image and the patient's image to be segmented. We also present a quantitative evaluation of lymph node regions segmentation using various statistical as well as geometrical metrics: sensitivity, specificity, dice similarity coefficient and Hausdorff distance. A comparison of the proposed method with two other state of the art methods is presented. The robustness of the proposed method to the atlas selection, in segmenting the lymph node regions, is also evaluated.Index Terms-Atlas-based segmentation, head and neck, IMRT, lymph node regions, non-rigid registration, radiotherapy.
a b s t r a c tThis paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and encompasses many of the state-of-the-art atlas-based segmentation methods. It also allows to perform the registration of atlas and target images based on only selected structures of interest. The versatility and potentiality of the proposed framework are demonstrated by presenting three diverse applications: In the first application, we show how the proposed framework can be used to simulate the growth of inconsistent structures like a tumor in an atlas. In the second application, we estimate the position of nonvisible brain structures based on the surrounding structures and validate the results by comparing with other methods. In the final application, we present the segmentation of lymph nodes in the Head and Neck CT images, and demonstrate how multiple registration forces can be used in this framework in an hierarchical manner.
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IntroductionAtlas-based segmentation is a widely used technique for automatic segmentation of normal MR images.
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