Multiatlas segmentation of thoracic and abdominal anatomy. To address the limitations of these recentlydeveloped 3d fcn. Due to the nature of medical images the task of segmentation can be tedious, timeconsuming and. Original article probabilistic atlasbased segmentation of. Segmentation of neonatal brain mr images using patch. This bash scripts is created for multiatlas based automatic brain structural parcellation, mainly for mouse brain mri. Mars multiatlas robust segmentation provides the automatic solutions for efficent. Due to the nature of medical images the task of segmentation can be tedious, timeconsuming and may involve manual guidance. Comparison of multiatlas based segmentation techniques for. User guide to multi atlas segmentation, with examples overview.
This bash scripts is created for multi atlas based automatic brain structural parcellation, mainly for mouse brain mri. Multi atlasbased muscle segmentation in abdominal ct. Atlas based segmentation methods also aim to segment different targets, such as, for instance, brain structures, brain tissues, or lesions. Atlasbased automatic segmentation of head and neck organs at risk. Medical image computing mic is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. Multiatlas segmentation using robust featurebased registration 3 the fused segmentation proposal can be further re. Evaluation of atlasbased autosegmentation software in. Furthermore, atlas based approaches are among the easiest to implement since they only require the user to align the atlas and subject images. User guide to multiatlas segmentation, with examples overview. This suggests that optimal atlas selection is not made for these structures. This thesis present an automatic method for the segmentation of the lungs from chest ct scans based on multi atlas registration and graph cuts. Whenever the manual or semimanual segmentation is used as a golden.
Full paper multiatlas and label fusion approach for patientspecific mri based skull estimation angel torradocarvajal,1,2 joaquin l. Each gyrus was divided into either one, two or three regions. These labels were then mapped onto the termination locations of the streamlines obtained from whole brain tractography. We compared the proposed approach with multiatlas segmentation and show the advantage of our method in both effectiveness and ef. Transforming the deformed atlas contours onto the patient image produces the desired segmentation. Augmenting atlasbased liver segmentation for radiotherapy. The documents may come from teaching and research institutions in france or abroad, or from public or private research centers. 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. Mabmis is a module for slicer 4 that implements a multiatlas based multiimage method for groupwise segmentation. Department of electronic systems and information processing, faculty of electrical engineering and computing, universiy of zagreb, unska 3, 0 zagreb, croatia phone. Lung segmentation using multi atlas registration and. Atlasbased segmentation methods also aim to segment different targets, such as, for instance, brain structures, brain tissues, or lesions. 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.
Casanova 2 and ayman elbaz 1 1 bioimaging laboratory, bioengineering department, universityof louisville, louisville, ky, usa. Rc maps from the atlasbased technique also demonstrated improvement in the pet data compared to the dute method, both globally as well as regionally. Quantitative research in neuroimaging often relies on anatomical segmentation of human brain mr 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. 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. Adaptive registration and atlas based segmentation by hyunjin. Improving label fusion in multiatlas based segmentation by locally combining atlas selection and performance estimationq t. A fullyautomatic caudate nucleus segmentation of brain.
Atlasbased approach for the segmentation of infant dti mr. 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. 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 segmentation methods can be categorized into three groups 15, namely singleatlasbased, averageshape atlasbased and multiatlasbased methods.
However, the approach that dominated early atlasguided segmentation was probabilistic atlasbased segmentation ashburner and friston, 2005. The registration between the narrow band regions is fast than the whole liver region. 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. Hongjun jia, pewthian yap, dinggang shen, iterative multiatlasbased multiimage segmentation with treebased registration, accepted for neuroimage. Automatic atlasbased threelabel cartilage segmentation. The method combines global anatomical shape information, based on multi atlas registration from a. Comparative advantage of the atlasbased segmentation with respect to the other. When using atlasbased segmentation, the choice of the atlas is crucial, and several strategies have been proposed. Introduction atlasbased registration has been ubiquitous in medical image analysis in the last decade 15, 2. The overall goal of atlasbased segmentation is to assist radiologists in the detection and diagnosis of diseases. We present a patch based 3,6 interactive segmentation method that provides accurate wholeheart segmentation in chd.
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. By extracting the relevant anatomy from medical images and presenting it in an. Atlasbased segmentation we evaluate atlasbasedtechniques for automated segmentation of subject images. When multiple atlases are available, they are each aligned to a target volume, and the warped atlas labels are fused 36. 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. This is the first version of the atlas segmentation. An atlasbased segmentation propagation framework 427 2. Tocope with theselimitations, inthispaper, wepropose a novellearningbasedmultisource integration frameworkfor.
Atlas based segmentation methods can be categorized into three groups 15, namely single atlas based, averageshape atlas based and multi atlas based methods. 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. Interactive wholeheart segmentation in congenital heart disease. 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. Atlasbased segmentation of medical images enlighten. Multiatlas based multiimage segmentation 1 an algorithm for effective atlasbased groupwise segmentation, which has been published as. 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. When using atlas based segmentation, the choice of the atlas is crucial, and several strategies have been proposed. 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. A fullyautomatic caudate nucleus segmentation of brain mri. Automatic atlasbased threelabel cartilage segmentation from. 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. Before downloading, you may want to read the release notes and changelog accessible by clicking on the release name. A widely used method consists to extract this prior knowledge from a reference image often called atlas.
Atlasbased 3d image segmentation zuse institute berlin. 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. I1, in with the corresponding manual segmentations an external file that. 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. 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.
Brain segmentation based on multiatlas guided 3d fully. Moreover, the choice of volume to label biases the algorithm. Lung segmentation using multi atlas registration and graph cuts. Atlasbased segmentation methods can be categorized into three groups 5, namely singleatlasbased, averageshape atlasbased and multiatlasbased methods. Atlasbased hippocampus segmentation in alzheimers disease. Various brain dti segmentation methods have been employed in the past few years. 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. What is the meaning of atlas in atlasbased segmentation. Pdf on apr 25, 2007, torsten rohlfing and others published quo vadis, atlas based segmentation. 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. In this case, a more flexible and adaptive technique can be useful in order to ensure accurate segmentation results. For example, it can be seen that the populationbased atlas shown in the 2nd row of fig.
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. Shen 1department of radiology and bric, university of north carolina, chapel hill, nc, united states, 2a. As we will see below, this can be viewed as a special case of multiatlas segmentation, since all atlases are consulted for segmentation. Atlasbased segmentation using a model of lesion growth. Multiatlas based segmentation editing tool segediting description. In some cases, the metrics indicated a better result when a smaller range of atlases was available. Atlasbased 3d image segmentation segmentation of medical image data ct, mrt. Specifically, this software has integrated several stateoftheart multi atlas based segmentation methods, such as majority. 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. The gc theory has been used in many computer vision problems 11. A map of cortical regions labels was constructed based on the maps of duvernoy 3 by an experienced neuroanatomist nl. An overview of our multi atlas and label fusion skull segmentation pipeline is shown in figure 2.
The method combines global anatomical shape information, based on multiatlas registration from a. The software uses atlases with predefined roi as templates to automatically delineate contours on a new patients computed tomography ct data set. The atlas based auto segmentation software program abas. In this work, we combine the power of atlasbased segmentation with an adaptive. Hybrid atlas based tissue segmentation for neonatal brain mri acquired using a dedicated phased array coil f. Atlas based 3d image segmentation segmentation of medical image data ct, mrt. However the results for diseased kidneys were unsatisfactory, due to di culties in global localization of the organ. Adaptive registration and atlas based segmentation by hyunjin park cochairs. Learningbased atlas selection for multipleatlas segmentation. However, the approach that dominated early atlas guided segmentation was probabilistic atlas based segmentation ashburner and friston, 2005. The overall goal of atlas based segmentation is to assist radiologists in the detection and diagnosis of diseases. Interactive wholeheart segmentation in congenital heart. 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.
Atlasbased segmentation using a model of lesion growth bach cuadra, m. Atlasbased hippocampus segmentation in alzheimers disease and mild cognitive impairment owen t. 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. We present a patchbased 3,6 interactive segmentation method that provides accurate wholeheart segmentation in chd. Multiatlas segmentation using robust featurebased registration. Learningbased multisource integration framework for segmentation of infant brain images li wanga,yaozonggaoa,b,fengshia,ganglia, john h. We study the widespread, but rarely discussed, tendency of atlasbased segmentation to undersegment the organs of interest. Learningbased multisource integration framework for. This is an important and challenging task in medical applications, where manual annotations are timeconsuming.
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. Pet, mri, attenuation correction, segmentation, atlas introduction. Segediting is a segmentation editing tool using existing labels as references. Improving label fusion in multiatlas based segmentation by. 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. Atlas based segmentation of white matter tracts of the. The initial contour is near around the liver region boundary. Registrationbased multiatlas segmentation can provide more robustness by using contrastinvariant similarity measures to guide the alignment of atlas to patient data.
A dedicated server monitors files acquired on the ct scanner and starts the segmentation algorithm once a new dataset is detected. This thesis present an automatic method for the segmentation of the lungs from chest ct scans based on multiatlas registration and graph cuts. 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. 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. For a comprehensive survey of multiatlas segmentation methods and their applications, see 12.
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. Enhancing atlas based segmentation with multiclass linear classifiers. Multi atlasbased muscle segmentation in abdominal ct images. As we will see below, this can be viewed as a special case of multi atlas segmentation, since all atlases are consulted for segmentation. Pluima a image sciences institute, university medical center utrecht, the netherlands bdepartment of radiotherapy, university medical center utrecht, the netherlands. Atlas based segmentation of white matter tracts of the human. Few labeled atlases are necessary for deeplearningbased. The atlasbased autosegmentation software program abas. Improving label fusion in multiatlas based segmentation. Data augmentation using learned transformations for one. Shen, iterative multiatlasbased multiimage segmentation with treebased registration, neuroimage, 59. Multiatlas based segmentation editing tool segediting.
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. 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. 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. Multiatlas segmentation atlas 1 atlas 2 dir warped contours. Hybrid atlas based tissue segmentation for neonatal brain. 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. Martinos center for biomedical imaging, department of radiology, massachusetts. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care.