检索结果-内蒙古大学图书馆

atlas-based segmentation of cochlear microstructures in cone beam CT

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2021年第3期16卷 363-373页

作者： Powell, Kimerly A. Wiet, Gregory J. Hittle, Brad Oswald, Grace, I Keith, Jason P. Stredney, Don Andersen, Steven Arild Wuyts Ohio State Univ Dept Biomed Informat Columbus OH 43210 USA Ohio State Univ Dept Otolaryngol Head & Neck Surg Columbus OH 43210 USA Nationwide Childrens Hosp Columbus OH 43210 USA Ohio State Univ Dept Biomed Engn Columbus OH 43210 USA Ohio State Univ Interface Lab Columbus OH 43210 USA Rigshosp Dept OtorhinolaryngologyHead & Neck Surg Copenhagen Denmark

Purpose To develop an automated segmentation approach for cochlear microstructures [scala tympani (ST), scala vestibuli (SV), modiolus (Mod), mid-modiolus (Mid-Mod), and round window membrane (RW)] in clinical cone beam computed tomography (CBCT) images of the temporal bone for use in surgical simulation software and for preoperative surgical evaluation. Methods This approach was developed using the publicly available OpenEar (OE) Library that includes temporal bone specimens with spatially registered CBCT and 3D micro-slicing images. Five of these datasets were spatially aligned to our internal OSU atlas. An atlas of cochlear microstructures was created from one of the OE datasets. An affine registration of this atlas to the remaining OE CBCT images was used for automatically segmenting the cochlear microstructures. Quantitative metrics and visual review were used for validating the automatic segmentations. Results The average DICE metrics were 0.77 and 0.74 for the ST and SV, respectively. The average Hausdorff distance (AVG HD) was 0.11 mm and 0.12 mm for both scalae. The mean distance between the centroids for the round window was 0.32 mm, and the mean AVG HD was 0.09 mm. The mean distance and angular rotation between the mid-modiolar axes were 0.11 mm and 9.8 degrees, respectively. Visually, the segmented structures were accurate and similar to that manually traced by an expert observer. Conclusions An atlas-based approach using 3D micro-slicing data and affine spatial registration in the cochlear region was successful in segmenting cochlear microstructures of temporal bone anatomy for use in simulation software and potentially for pre-surgical planning and rehearsal.

关键词： atlas-based segmentation Image registration Surgical simulation Pre-surgical planning Cochlea anatomy

来源：评论

学校读者我要写书评

暂无评论

atlas-based segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks 24th

Atlas-based Segmentation of Intracochlear Anatomy in Metal A...

引用

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)

作者： Wang, Jianing Su, Dingjie Fan, Yubo Chakravorti, Srijata Noble, Jack H. Dawant, Benoit M. Vanderbilt Univ Dept Elect & Comp Engn Nashville TN 37235 USA

ISBN: (纸本)9783030872021;9783030872014

We propose an atlas-based method to segment the intracochlear anatomy (ICA) in the post-implantation CT (Post-CT) images of cochlear implant (CI) recipients that preserves the point-to-point correspondence between the meshes in the atlas and the segmented volumes. To solve this problem, which is challenging because of the strong artifacts produced by the implant, we use a pair of co-trained deep networks that generate dense deformation fields (DDFs) in opposite directions. One network is tasked with registering an atlas image to the Post-CT images and the other network is tasked with registering the Post-CT images to the atlas image. The networks are trained using loss functions based on voxel-wise labels, image content, fiducial registration error, and cycle-consistency constraint. The segmentation of the ICA in the Post-CT images is subsequently obtained by transferring the predefined segmentation meshes of the ICA in the atlas image to the Post-CT images using the corresponding DDFs generated by the trained registration networks. Our model can learn the underlying geometric features of the ICA even though they are obscured by the metal artifacts. We show that our end-to-end network produces results that are comparable to the current state of the art (SOTA) that relies on a two-steps approach that first uses conditional generative adversarial networks to synthesize artifact-free images from the Post-CT images and then uses an active shape model-based method to segment the ICA in the synthetic images. Our method requires a fraction of the time needed by the SOTA, which is important for end-user acceptance.

关键词： Non-rigid registration atlas-based segmentation Metal artifact Cochlear implant

来源：评论

学校读者我要写书评

暂无评论

atlas-based segmentation in Extraction of Knee Joint Bone Structures from CT and MR

引用

SENSORS 2022年第22期22卷 8960页

作者： Zarychta, Piotr Silesian Tech Univ Fac Biomed Engn Roosevelta 40 St PL-41800 Zabrze Poland

The main goal of the approach proposed in this study, which is dedicated to the extraction of bone structures of the knee joint (femoral head, tibia, and patella), was to show a fully automated method of extracting these structures based on atlas segmentation. In order to realize the above-mentioned goal, an algorithm employed automated image-matching as the first step, followed by the normalization of clinical images and the determination of the 11-element dataset to which all scans in the series were allocated. This allowed for a delineation of the average feature vector for the teaching group in the next step, which automated and streamlined known fuzzy segmentation methods (fuzzy c-means (FCM), fuzzy connectedness (FC)). These averaged features were then transmitted to the FCM and FC methods, which were implemented for the testing group and correspondingly for each scan. In this approach, two features are important: the centroids (which become starting points for the fuzzy methods) and the surface area of the extracted bone structure (protects against over-segmentation). This proposed approach was implemented in MATLAB and tested in 61 clinical CT studies of the lower limb on the transverse plane and in 107 T1-weighted MRI studies of the knee joint on the sagittal plane. The atlas-based segmentation combined with the fuzzy methods achieved a Dice index of 85.52-89.48% for the bone structures of the knee joint.

关键词： atlas-based segmentation image matching bone structures of the knee joint femur tibia patella fuzzy connectedness

来源：评论

学校读者我要写书评

暂无评论

Comparison of commercial atlas-based automatic segmentation software for prostate radiotherapy treatment planning

引用

PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE 2024年第3期47卷 881-894页

作者： Hizam, Diyana Afrina Tan, Li Kuo Saad, Marniza Muaadz, Asyraf Ung, Ngie Min Univ Malaya Fac Med Clin Oncol Unit Kuala Lumpur Malaysia Univ Malaya Dept Biomed Imaging Kuala Lumpur Malaysia Univ Malaya Med Ctr Dept Clin Oncol Kuala Lumpur Malaysia

This study aims to assess the accuracy of automatic atlas-based contours for various key anatomical structures in prostate radiotherapy treatment planning. The evaluated structures include the bladder, rectum, prostate, seminal vesicles, femoral heads and penile bulb. CT images from 20 patients who underwent intensity-modulated radiotherapy were randomly chosen to create an atlas library. atlas contours of the seven anatomical structures were generated using four software packages: ABAS, Eclipse, MIM, and RayStation. These contours were then compared to manual delineations performed by oncologists, which served as the ground truth. Evaluation metrics such as dice similarity coefficient (DSC), mean distance to agreement (MDA), and volume ratio (VR) were calculated to assess the accuracy of the contours. Additionally, the time taken by each software to generate the atlas contour was recorded. The mean DSC values for the bladder exhibited strong agreement (>0.8) with manual delineations for all software except for Eclipse and RayStation. Similarly, the femoral heads showed significant similarity between the atlas contours and ground truth across all software, with mean DSC values exceeding 0.9 and MDA values close to zero. On the other hand, the penile bulb displayed only moderate agreement with the ground truth, with mean DSC values ranging from 0.5 to 0.7 for all software. A similar trend was observed in the prostate atlas contours, except for MIM, which achieved a mean DSC of over 0.8. For the rectum, both ABAS and MIM atlases demonstrated strong agreement with the ground truth, resulting in mean DSC values of more than 0.8. Overall, MIM and ABAS outperformed Eclipse and RayStation in both DSC and MDA. These results indicate that the atlas-based segmentation employed in this study produces acceptable contours for the anatomical structures of interest in prostate radiotherapy treatment planning.

关键词： atlas-based segmentation Automatic contouring Prostate radiotherapy

来源：评论

学校读者我要写书评

暂无评论

Technical Note: Efficient and accurate MRI-only based treatment planning of the prostate using bulk density assignment through atlas-based segmentation

引用

MEDICAL PHYSICS 2020年第10期47卷 4758-4762页

作者： McCallum, Hazel Mhairi Andersson, Sebastian Wyatt, Jonathan James Richmond, Neil Walker, Christopher Paul Svensson, Stina Newcastle Upon Tyne Hosp NHS Fdn Trust Northern Ctr Canc Care Newcastle Upon Tyne NE7 7DN Tyne & Wear England RaySearch Labs AB PUBL POB 3297 SE-10365 Stockholm Sweden

Purpose This study investigates the dosimetric accuracy as well as the robustness of a bulk density assignment approach to magnetic resonance imaging (MRI)-only based treatment planning of the prostate, with bulk density regions automatically identified using atlas-based segmentation (ABS). Methods Twenty prostate radiotherapy patients received planning computed tomography (CT) and MRI scans and were treated with volumetric modulated arc therapy (VMAT). Two bulk densities were set, one for bone and one for soft tissue. The bone contours were created by using ABS followed by manual modification if considered necessary. A range of soft tissue and bone density pairs, between 0.95 and 1.03 g/cm(3)with increments of 0.01 for soft tissue, and between 1.15 and 1.65 g/cm(3)with increments of 0.05 for bone, were evaluated. Using the density pair giving the lowest dose difference compared to the CT-based dose, dose differences were calculated using both the manually modified bone contours and the bone contours from ABS. Contour overlap measurements between the ABS contours and the manually modified contours were calculated. Results The dose comparison shows a very good agreement with the CT when using 0.98 g/cm(3)for soft tissue and 1.20 g/cm(3)for bone, with a dose difference less than 1 % in average dose in all regions of interest. The mean Dice similarity coefficient for bone was 0.94 and the Mean Distance to Agreement was Using bulk density assignment on MR images with suitable densities for bone and soft tissue results in clinically acceptable dose differences compared to dose calculated on the CT, for both atlas-based and manual bone contours. This demonstrates that an integrated MRI-only pathway utilizing a bulk density assignment for two tissue types is a feasible and robust approach for patients with prostate cancer treated with VMAT.

关键词： atlas-based segmentation bulk density assignment magnetic resonance MRI-only based radiotherapy prostate patients VMAT

来源：评论

学校读者我要写书评

暂无评论

atlas-based segmentation of temporal bone surface structures

引用

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2019年第8期14卷 1267-1273页

作者： Powell, Kimerly A. Kashikar, Tanisha Hittle, Brad Stredney, Don Kerwin, Thomas Wiet, Gregory J. Ohio State Univ Dept Biomed Informat Columbus OH 43210 USA Ohio Univ Heritage Coll Osteopath Athens OH 45701 USA Ohio State Univ Interface Lab Columbus OH 43210 USA Nationwide Childrens Hosp Dept Otolaryngol Columbus OH USA Ohio State Univ Columbus OH 43210 USA

PurposeTo develop a time-efficient automated segmentation approach that could identify surface structures on the temporal bone for use in surgical simulation software and preoperative surgical *** atlas-based segmentation approach was developed to segment the tegmen, sigmoid sulcus, exterior auditory canal, interior auditory canal, and posterior canal wall in normal temporal bone CT images. This approach was tested in images of 20 cadaver bones (10 left, 10 right). The results of the automated segmentation were compared to manual segmentation using quantitative metrics of similarity, Mahalanobis distance, average Hausdorff distance, and volume *** Mahalanobis distance was less than 0.232mm for all structures. The average Hausdorff distance was less than 0.464mm for all structures except the posterior canal wall and external auditory canal for the right bones. Volume similarity was 0.80 or greater for all structures except the sigmoid sulcus that was 0.75 for both left and right bones. Visually, the segmented structures were accurate and similar to that manually traced by an expert *** atlas-based approach using a deformable registration of a Gaussian-smoothed temporal bone image and refinements using surface landmarks was successful in segmenting surface structures of temporal bone anatomy for use in pre-surgical planning and training.

关键词： atlas-based segmentation Image registration Surgical simulation Pre-surgical planning Temporal bone anatomy

来源：评论

学校读者我要写书评

暂无评论

Optimization and comparative evaluation of nonlinear deformation algorithms for atlas-based segmentation of DBS target nuclei

引用

NEUROIMAGE 2019年 184卷 586-598页

作者： Ewert, Siobhan Horn, Andreas Finkel, Francisca Li, Ningfei Kuehn, Andrea A. Herrington, Todd M. Charite Univ Med Berlin Dept Neurol Movement Disorders & Neuromodulat Unit Berlin Germany Harvard Med Sch Massachusetts Gen Hosp Dept Neurol Boston MA 02115 USA Northeastern Univ Program Behav Neurosci Boston MA 02115 USA Tech Univ Berlin Neural Informat Proc Grp Inst Software Engn & Theoret Comp Sci Berlin Germany

Nonlinear registration of individual brain MRI scans to standard brain templates is common practice in neuro-imaging and multiple registration algorithms have been developed and refined over the last 20 years. However, little has been done to quantitatively compare the available algorithms and much of that work has exclusively focused on cortical structures given their importance in the fMRI literature. In contrast, for clinical applications such as functional neurosurgery and deep brain stimulation (DBS), proper alignment of subcortical structures between template and individual space is important. This allows for atlas-based segmentations of anatomical DBS targets such as the subthalamic nucleus (STN) and internal pallidum (GPi). Here, we systematically evaluated the performance of six modern and established algorithms on subcortical normalization and segmentation results by calculating over 11,000 nonlinear warps in over 100 subjects. For each algorithm, we evaluated its performance using T1-or T2-weighted acquisitions alone or a combination of T1-, T2- and PD-weighted acquisitions in parallel. Furthermore, we present optimized parameters for the best performing algorithms. We tested each algorithm on two datasets, a state-of-the-art MRI cohort of young subjects and a cohort of subjects age-and MR-quality-matched to a typical DBS Parkinson's Disease cohort. Our final pipeline is able to segment DBS targets with precision comparable to manual expert segmentations in both cohorts. Although the present study focuses on the two prominent DBS targets, STN and GPi, these methods may extend to other small subcortical structures like thalamic nuclei or the nucleus accumbens.

关键词： Manual segmentation Automated segmentation atlas-based segmentation Subcortical normalization Spatial image deformation DBS

来源：评论

学校读者我要写书评

暂无评论

atlas-based segmentation of neonatal brain MR images using a gray matter enhancing step

引用

SIGNAL IMAGE AND VIDEO PROCESSING 2018年第4期12卷 633-640页

作者： Rodriguez-Dominguez, Ulises Dalmau, Oscar Ocegueda, Omar Bosch-Bayard, Jorge Math Res Ctr Guanajuato Guanajuato Mexico UNAM Inst Neurobiol Santiago De Queretaro Mexico

We propose an atlas-based segmentation framework for brain magnetic resonance images, specially designed to fit neonatal images, which pose additional difficulties due to the poor differentiation between the gray and white matter. The main contribution of our work consists of a gray matter enhancing step, which is applied to either the T1w or T2w modalities after standard preprocessing and alignment steps are carried out. Our enhancing step uses Hessian and box filters for the cortical gray matter and takes advantage of both local and non-local information for the subcortical gray matter. We consider four classes, and our framework has been evaluated using publicly available data from the NeoBrainS12 challenge.

关键词： atlas-based segmentation MRI Neonatal brain segmentation

来源：评论

学校读者我要写书评

暂无评论

atlas-based liver segmentation for nonhuman primate research

引用

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2020年第10期15卷 1631-1638页

作者： Solomon, Jeffrey Aiosa, Nina Bradley, Dara Castro, Marcelo A. Reza, Syed Bartos, Christopher Sayre, Philip Lee, Ji Hyun Sword, Jennifer Holbrook, Michael R. Bennett, Richard S. Hammoud, Dima A. Johnson, Reed F. Feuerstein, Irwin Natl Canc Inst Frederick Natl Lab Canc Res Clin Monitoring Res Program Directorate Frederick MD 21702 USA NIH Ctr Infect Dis Imaging Ctr Clin Radiol & Imaging Sci Bldg 10 Bethesda MD 20892 USA NIAID Div Clin Res Integrated Res Facil NIH Frederick MD 21704 USA

Purpose Certain viral infectious diseases cause systemic damage and the liver is an important organ affected directly by the virus and/or the hosts' response to the virus. Medical imaging indicates that the liver damage is heterogenous, and therefore, quantification of these changes requires analysis of the entire organ. Delineating the liver in preclinical imaging studies is a time-consuming and difficult task that would benefit from automated liver segmentation. Methods A nonhuman primate atlas-based liver segmentation method was developed to support quantitative image analysis of preclinical research. A set of 82 computed tomography (CT) scans of nonhuman primates with associated manual contours delineating the liver was generated from normal and abnormal livers. The proposed technique uses rigid and deformable registrations, a majority vote algorithm, and image post-processing operations to automate the liver segmentation process. This technique was evaluated using Dice similarity, Hausdorff distance measures, and Bland-Altman plots. Results Automated segmentation results compare favorably with manual contouring, achieving a median Dice score of 0.91. Limits of agreement from Bland-Altman plots indicate that liver changes of 3 Hounsfield units (CT) and 0.4 SUVmean (positron emission tomography) are detectable using our automated method of segmentation, which are substantially less than changes observed in the host response to these viral infectious diseases. Conclusion The proposed atlas-based liver segmentation technique is generalizable to various sizes and species of nonhuman primates and facilitates preclinical infectious disease research studies. While the image analysis software used is commercially available and facilities with funding can access the software to perform similar nonhuman primate liver quantitative analyses, the approach can be implemented in open-source frameworks as there is nothing proprietary about these methods.

关键词： atlas-based segmentation Liver Computed tomography Nonhuman primate research

来源：评论

学校读者我要写书评

暂无评论

Geodesic registration for interactive atlas-based segmentation using learned multi-scale anatomical manifolds

引用

PATTERN RECOGNITION LETTERS 2018年 112卷 340-345页

作者： Andersson, Thord Borga, Magnus Leinhard, Olof Dahlqvist Linkoping Univ Dept Biomed Engn IMT Linkoping Sweden Swedish Def Res Agcy Dept C4ISR Linkoping Sweden Linkoping Univ Ctr Med Image Sci & Visualizat CMIV Linkoping Sweden Linkoping Univ Dept Med & Hlth Sci Linkoping Sweden

atlas-based segmentation is often used to segment medical image regions. For intensity-normalized data, the quality of these segmentations is highly dependent on the similarity between the atlas and the target under the used registration method. We propose a geodesic registration method for interactive atlas-based segmentation using empirical multi-scale anatomical manifolds. The method utilizes unlabeled images together with the labeled atlases to learn empirical anatomical manifolds. These manifolds are defined on distinct scales and regions and are used to propagate the labeling information from the atlases to the target along anatomical geodesics. The resulting competing segmentations from the different manifolds are then ranked according to an image-based similarity measure. We used image volumes acquired using magnetic resonance imaging from 36 subjects. The performance of the method was evaluated using a liver segmentation task. The result was then compared to the corresponding performance of direct segmentation using Dice Index statistics. The method shows a significant improvement in liver segmentation performance between the proposed method and direct segmentation. Furthermore, the standard deviation in performance decreased significantly. Using competing complementary manifolds defined over a hierarchy of region of interests gives an additional improvement in segmentation performance compared to the single manifold segmentation. (c) 2018 Elsevier B.V. All rights reserved.

关键词： atlas-based segmentation Image registration Manifold learning MRI

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：