Automatic atlasbased threelabel cartilage segmentation from. Evaluation of atlasbased autosegmentation software in. These labels were then mapped onto the termination locations of the streamlines obtained from whole brain tractography. Atlasbased segmentation of medical images enlighten. Interactive segmentation ts well into clinical work ows since physicians must validate any segmentation used for decision making and correct the errors that are inevitable in automatic segmentation. Atlasbased autosegmentation computes estimates of anatomic boundaries contours in a patient ct image series by deformably registering a previously contoured ct imagethe atlasto the patient image.
Pluima a image sciences institute, university medical center utrecht, the netherlands bdepartment of radiotherapy, university medical center utrecht, the netherlands. Mars multiatlas robust segmentation provides the automatic solutions for efficent. The software uses atlases with predefined roi as templates to automatically delineate contours on a new patients computed tomography ct data set. Registrationbased multiatlas segmentation can provide more robustness by using contrastinvariant similarity measures to guide the alignment of atlas to patient data. Augmenting atlasbased liver segmentation for radiotherapy. In this case, a more flexible and adaptive technique can be useful in order to ensure accurate segmentation results. Thompson,d carolyn cidis meltzer,a and yanxi liue aradiology department, university of pittsburgh, b938 puh, 200 lothrop street, pittsburgh, pa 152, usa bpsychiatry department. The documents may come from teaching and research institutions in france or abroad, or from public or private research centers. In this multi atlas based segmentation approach, the unknown ground truth segmentation mask l gt of the mri volume v mri is estimated as l mri by registration of a set of n ct volumes v n and propagating their corresponding segmentations l n. When using atlasbased segmentation, the choice of the atlas is crucial, and several strategies have been proposed.
A dedicated server monitors files acquired on the ct scanner and starts the segmentation algorithm once a new dataset is detected. Atlasbased segmentation methods also aim to segment different targets, such as, for instance, brain structures, brain tissues, or lesions. Quantitative research in neuroimaging often relies on anatomical segmentation of human brain mr images. A widely used method consists to extract this prior knowledge from a reference image often called atlas. Atlas based approachfor the segmentation of infant dti mr brain images mahmoud mostapha 1, amir alansary 1, ahmed soliman 1, fahmi khalifa 1, matthew nitzken 1, rasha khodeir 1, manuel f. Cis has implemented a process for the segmentation of brain image grayscale data into image maps containing labels for each voxel in the volume which identify the structure the voxel belongs to. The purpose of this study was to systematically compare the performance of several competing publicdomain methodologies for atlas based segmentation of adatrophied hippocampi. User guide to multiatlas segmentation, with examples overview. The gc theory has been used in many computer vision problems 11. A fullyautomatic caudate nucleus segmentation of brain. Atlas based segmentation methods also aim to segment different targets, such as, for instance, brain structures, brain tissues, or lesions. Most previous studies used multi atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and isoften computationally expensive. Atlasbased 3d image segmentation segmentation of medical image data ct, mrt. Mabmis is a module for slicer 4 that implements a multiatlas based multiimage method for groupwise segmentation.
Atlas based approaches have been proposed to get automatic delineations of the organs at risk in the brain 1, and automatic delineations of the lymph nodes andor organs at risk in the head and neck region 2,3. We compared the proposed approach with multiatlas segmentation and show the advantage of our method in both effectiveness and ef. Atlasbased segmentation we evaluate atlasbasedtechniques for automated segmentation of subject images. Hybrid atlas based tissue segmentation for neonatal brain mri acquired using a dedicated phased array coil f. In this work, we combine the power of atlasbased segmentation with an adaptive. A map of cortical regions labels was constructed based on the maps of duvernoy 3 by an experienced neuroanatomist nl.
Our contribution is closely related to this idea, comparing atlas based segmentation approaches qualitatively and quantitatively according to their strategy, target and accuracy reported in the literature. The problem of image segmentation is a widely explored topic in the domain of medical image processing. Atlasbased hippocampus segmentation in alzheimers disease and mild cognitive impairment owen t. Multiatlas segmentation using robust featurebased registration. Adaptive registration and atlas based segmentation by hyunjin. I1, in with the corresponding manual segmentations an external file that. Before downloading, you may want to read the release notes and changelog accessible by clicking on the release name.
However, the approach that dominated early atlas guided segmentation was probabilistic atlas based segmentation ashburner and friston, 2005. Whenever the manual or semimanual segmentation is used as a golden. Adaptive registration and atlas based segmentation by hyunjin park cochairs. Multiatlas based segmentation editing tool segediting description. The method combines global anatomical shape information, based on multi atlas registration from a. Learningbased multisource integration framework for. Atlas based segmentation methods can be categorized into three groups 15, namely single atlas based, averageshape atlas based and multi atlas based methods. Because it is the project i have developed during my work at neurostar gmbh, i cannot provide the final version, where i integrate the segmentation with their framework.
Due to the nature of medical images the task of segmentation can be tedious, timeconsuming and. Original article probabilistic atlasbased segmentation of. Interactive wholeheart segmentation in congenital heart disease. Atlasbased approaches have been proposed to get automatic delineations of the organs at risk in the brain 1, and automatic delineations of the lymph nodes andor organs at risk in the head and neck region 2,3. Pdf on apr 25, 2007, torsten rohlfing and others published quo vadis, atlas based segmentation. Atlasbased segmentation of medical images is an image analysis task which involves labelling a desired anatomy or set of anatomy from images generated by medical imaging modalities. Full paper multiatlas and label fusion approach for patientspecific mri based skull estimation angel torradocarvajal,1,2 joaquin l. Improving label fusion in multiatlas based segmentation by locally combining atlas selection and performance estimationq t. Our contribution is closely related to this idea, comparing atlasbased segmentation approaches qualitatively and quantitatively according to their strategy, target and accuracy reported in the literature. Each gyrus was divided into either one, two or three regions.
Shen 1department of radiology and bric, university of north carolina, chapel hill, nc, united states, 2a. Atlasbased automatic segmentation of head and neck organs at risk. Lung segmentation using multi atlas registration and graph cuts. As we will see below, this can be viewed as a special case of multi atlas segmentation, since all atlases are consulted for segmentation. Multiatlas based multiimage segmentation 1 an algorithm for effective atlasbased groupwise segmentation, which has been published as. The overall goal of atlas based segmentation is to assist radiologists in the detection and diagnosis of diseases. Multiatlas segmentation of thoracic and abdominal anatomy.
Specifically, this software has integrated several stateoftheart multi atlas based segmentation methods, such as majority. When multiple atlases are available, they are each aligned to a target volume, and the warped atlas labels are fused 36. We present a patch based 3,6 interactive segmentation method that provides accurate wholeheart segmentation in chd. Atlasbased segmentation methods can be categorized into three groups 15, namely singleatlasbased, averageshape atlasbased and multiatlasbased methods. This is the first version of the atlas segmentation. Hybrid atlas based tissue segmentation for neonatal brain. This bash scripts is created for multi atlas based automatic brain structural parcellation, mainly for mouse brain mri. Comparative advantage of the atlasbased segmentation with respect to the other.
Multi atlasbased muscle segmentation in abdominal ct images. Multi atlas based segmentation is a segmentation method that allows fully automatic segmentation of image populations that exhibit a large variability in shape and image quality. Atlas based segmentation of white matter tracts of the human. Recent multi atlas based approaches provide highly accurate structural segmentations of the brain by propagating manual delineations from multiple atlases in a database to a query subject and combining them. We present a patchbased 3,6 interactive segmentation method that provides accurate wholeheart segmentation in chd. Fessler with the rapid developments in image registration techniques, registrations are applied not only as linear transforms but also as warping transforms with increasing frequency. Atlasbased approach for the segmentation of infant dti mr. An atlasbased segmentation propagation framework 427 2. Learningbased multisource integration framework for segmentation of infant brain images li wanga,yaozonggaoa,b,fengshia,ganglia, john h. Atlas based 3d image segmentation segmentation of medical image data ct, mrt.
As we will see below, this can be viewed as a special case of multiatlas segmentation, since all atlases are consulted for segmentation. Hongjun jia, pewthian yap, dinggang shen, iterative multiatlasbased multiimage segmentation with treebased registration, accepted for neuroimage. The atlas based auto segmentation software program abas. Improving label fusion in multiatlas based segmentation by. Theuseofasinglelabeledvolume atlas islimitedin registrationbased segmentation because it is hard for one atlas to represent the whole data population, especially if input images observe large variation. Improving label fusion in multiatlas based segmentation. Casanova 2 and ayman elbaz 1 1 bioimaging laboratory, bioengineering department, universityof louisville, louisville, ky, usa. Introduction atlasbased registration has been ubiquitous in medical image analysis in the last decade 15, 2. Tocope with theselimitations, inthispaper, wepropose a novellearningbasedmultisource integration frameworkfor. It is useful when you would like to correct large errors with a few user interactions such as dots or rough scribbles using one or multiple reference labels of the target object. For a comprehensive survey of multiatlas segmentation methods and their applications, see 12.
The initial contour is near around the liver region boundary. Comparison of multiatlas based segmentation techniques for. The key components are a special reference image called the atlas image, an atlas mask, i. Multiatlas segmentation atlas 1 atlas 2 dir warped contours. This suggests that optimal atlas selection is not made for these structures. Shen, iterative multiatlasbased multiimage segmentation with treebased registration, neuroimage, 59. We propose a method for brain atlas deformation in presence of large spaceoccupying tumors or lesions, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its central point. This bash scripts is created for multiatlas based automatic brain structural parcellation, mainly for mouse brain mri. Recent multiatlas based approaches provide highly accurate structural segmentations of the brain by propagating manual delineations from multiple atlases in a database to a query subject and combining them. A fullyautomatic caudate nucleus segmentation of brain mri.
Moreover, the choice of volume to label biases the algorithm. Assuming a perfect atlas selection, an extreme value theory has been applied to estimate the accuracy of single atlas and multi atlas segmentation given a large database of atlases. One limitation is that the populationbased atlas may not be representative of a single subject in the regions with high intersubject variability and thus leads to a low capability for guiding the tissue segmentation. Multiatlas segmentation mas, first introduced and popularized by the pioneering work of rohlfing, brandt, menzel and maurer jr 2004, klein, mensh, ghosh, tourville and hirsch 2005, and heckemann, hajnal, aljabar, rueckert and hammers 2006, is becoming one of the most widelyused and successful image segmentation techniques in biomedical applications. Various brain dti segmentation methods have been employed in the past few years. Multiatlas based segmentation editing tool segediting. However, the approach that dominated early atlasguided segmentation was probabilistic atlasbased segmentation ashburner and friston, 2005. Assuming a perfect atlas selection, an extreme value theory has been applied to estimate the accuracy of singleatlas and multiatlas segmentation given a large database of atlases.
This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care. Data augmentation using learned transformations for one. Atlasbased segmentation using a model of lesion growth. Martinos center for biomedical imaging, department of radiology, massachusetts.
Atlasbased hippocampus segmentation in alzheimers disease. The updated brainlab atlasbased automatic segmentation tool for. Interactive wholeheart segmentation in congenital heart. Workflow of the automated atlassegmentation approach. Atlas based segmentation of white matter tracts of the. Atlas based segmentation of medical images is an image analysis task which involves labelling a desired anatomy or set of anatomy from images generated by medical imaging modalities. Learningbased atlas selection for multipleatlas segmentation. Few labeled atlases are necessary for deeplearningbased. Elekta instrument ab stockholm, stockholm, sweden provides a computerised autocontouring functionality. Enhancing atlas based segmentation with multiclass linear classifiers.
Automatic atlasbased threelabel cartilage segmentation. The atlasbased autosegmentation software program abas. Although these approaches have enhanced the performance of automated segmentation through extracting different kinds of pixel and region features, they still have some common defects. Lung segmentation using multi atlas registration and. Furthermore, atlas based approaches are among the easiest to implement since they only require the user to align the atlas and subject images. Multi atlasbased muscle segmentation in abdominal ct. A process of label fusion is applied to segment the psoas major muscle in the atlas datasets, by using the ground truth muscle labels from the atlas datasets. What is the meaning of atlas in atlasbased segmentation. A common tendency of atlasbased segmentation to undersegment has largely. The method combines global anatomical shape information, based on multiatlas registration from a. Rc maps from the atlasbased technique also demonstrated improvement in the pet data compared to the dute method, both globally as well as regionally.
Medical image computing mic is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. Segmentation of neonatal brain mr images using patch. Multi atlas segmentation mas, first introduced and popularized by the pioneering work of rohlfing, brandt, menzel and maurer jr 2004, klein, mensh, ghosh, tourville and hirsch 2005, and heckemann, hajnal, aljabar, rueckert and hammers 2006, is becoming one of the most widelyused and successful image segmentation techniques in biomedical applications. This thesis present an automatic method for the segmentation of the lungs from chest ct scans based on multi atlas registration and graph cuts. We study the widespread, but rarely discussed, tendency of atlasbased segmentation to undersegment the organs of interest. To address the limitations of these recentlydeveloped 3d fcn. However the results for diseased kidneys were unsatisfactory, due to di culties in global localization of the organ. When using atlas based segmentation, the choice of the atlas is crucial, and several strategies have been proposed. In the atlas based segmentation step, the center of the nar row band atlas is regarded as the initial contour to initialize level set function.
This thesis present an automatic method for the segmentation of the lungs from chest ct scans based on multiatlas registration and graph cuts. In previous work, automatic kidney segmentation was achieved for healthy cases, based on the use of a probabilistic atlas and a multilevel statistical shape model 1. Atlasbased segmentation methods can be categorized into three groups 5, namely singleatlasbased, averageshape atlasbased and multiatlasbased methods. By extracting the relevant anatomy from medical images and presenting it in an. Due to the nature of medical images the task of segmentation can be tedious, timeconsuming and may involve manual guidance. The overall goal of atlasbased segmentation is to assist radiologists in the detection and diagnosis of diseases. User guide to multi atlas segmentation, with examples overview. Transforming the deformed atlas contours onto the patient image produces the desired segmentation. Pet, mri, attenuation correction, segmentation, atlas introduction. In this work, we combine the power of atlas based segmentation with an adaptive energy based scheme based on the graph cut gc framework, to obtain a globally optimal segmentation of the caudate structure in mri. In some cases, the metrics indicated a better result when a smaller range of atlases was available. Brain segmentation based on multiatlas guided 3d fully. Hernandeztamames,1,2 raul san joseestepar,2,4 yigitcan eryaman,2,3,5 yves rozenholc,6,7 elfar adalsteinsson,2,8,9,10 lawrence l.
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