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Can atlas-based Auto-segmentation Ever Be Perfect? Insights From Extreme Value Theory

IEEE TRANSACTIONS ON MEDICAL IMAGING 2019年第1期38卷 99-106页

作者： Schipaanboord, Bas Boukerroui, Djamal Peressutti, Devis van Soest, Johan Lustberg, Tim Kadir, Timor Dekker, Andre van Elmpt, Wouter Gooding, Mark Erasmus MC Canc Inst Dept Radiotherapy NL-3015 CE Rotterdam Netherlands Mirada Med Ltd Oxford OX1 1BY England Maastricht Univ Med Ctr GROW Sch Oncol & Dev Biol Dept Radiat Oncol MAASTRO NL-6229 ET Maastricht Netherlands

atlas-based segmentation is used in radiotherapy planning to accelerate the delineation of organs at risk (OARs). atlas selection has been proposed to improve the performance of segmentation, assuming that the more similar the atlas is to the patient, the better the result. It follows that the larger the database of atlases from which to select, the better the results should be. This paper seeks to estimate a clinically achievable expected performance under this assumption. Assuming a perfect atlas selection, an extreme value theory has been applied to estimate the accuracy of single-atlas andmulti-atlas segmentation given a large database of atlases. For this purpose, clinical contours of most common OARs on computed tomography of the head and neck (N = 316) and thoracic (N = 280) cases were used. This paper found that while for most organs, perfect segmentation cannot be reasonably expected, auto-contouring performance of a level corresponding to clinical quality could be consistently expected given a database of 5000 atlases under the assumption of perfect atlas selection.

关键词： Radiotherapy extreme value theory atlas-based segmentation auto-contouring

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atlas-based segmentation in breast cancer radiotherapy: Evaluation of specific and generic-purpose atlases

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BREAST 2017年 32卷 44-52页

作者： Ciardo, Delia Gerardi, Marianna Alessandra Vigorito, Sabrina Morra, Anna Dell'acqua, Veronica Javier Diaz, Federico Cattani, Federica Zaffino, Paolo Ricotti, Rosalinda Spadea, Maria Francesca Riboldi, Marco Orecchia, Roberto Baroni, Guido Leonardi, Maria Cristina Jereczek-Fossa, Barbara Alicja European Inst Oncol Dept Radiat Oncol Via Ripamonti 435 I-20141 Milan Italy European Inst Oncol Unit Med Phys Milan Italy Med Radiat Oncol Mevaterapia Buenos Aires DF Argentina Magna Graecia Univ Catanzaro Dept Expt & Clin Med Catanzaro Italy Politecn Milan Dipartimento Elettron Informaz & Bioingn Milan Italy CNAO Fdn Natl Ctr Oncol Hadrontherapy Bioengn Unit Pavia Italy European Inst Oncol Sci Direct Milan Italy Univ Milan Dept Oncol & Hematooncol Milan Italy

Objectives: atlas-based automatic segmentation (ABAS) addresses the challenges of accuracy and reliability in manual segmentation. We aim to evaluate the contribution of specific-purpose in ABAS of breast cancer (BC) patients with respect to generic-purpose libraries. Materials and methods: One generic-purpose and 9 specific-purpose libraries, stratified according to type of surgery and size of thorax circumference, were obtained from the computed tomography of 200 BC patients. Keywords about contralateral breast volume and presence of breast expander/prostheses were recorded. ABAS was validated on 47 independent patients, considering manual segmentation from scratch as reference. Five ABAS datasets were obtained, testing single-ABAS and multi-ABAS with simultaneous truth and performance level estimation (STAPLE). Center of mass distance (CMD), average Hausdorff distance (AHD) and Dice similarity coefficient (DSC) between corresponding ABAS and manual structures were evaluated and statistically significant differences between different surgeries, structures and ABAS strategies were investigated. Results: Statistically significant differences between patients who underwent different surgery were found, with superior results for conservative-surgery group, and between different structures were observed: ABAS of heart, lungs, kidneys and liver was satisfactory (median values: CMD<2 mm, DSC>0.80, AHD<1.5 mm), whereas chest wall, breast and spinal cord obtained moderate performance (median values: 2 mm < CMD<5 mm, 0.60 < DSC<0.80, 1.5 mm < AHD<4 mm) and esophagus, stomach, brachial plexus and supraclavicular nodes obtained poor performance (median CMD>5 mm, DSC<0.60, AHD>4 mm). The application of STAPLE algorithm generally yields higher performance and the use of keywords improves results for breast ABAS. Conclusion: The homogeneity in the selection of atlases based on multiple anatomical and clinical features and the use of specific-purpose libraries can improve ABAS pe

关键词： atlas-based segmentation Breast cancer radiotherapy Automatic contouring STAPLE contours

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atlas-based segmentation of Temporal Bone Anatomy

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INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2017年第11期12卷 1937-1944页

作者： Powell, Kimerly A. Liang, Tong Hittle, Brad Stredney, Don Kerwin, Thomas Wiet, Gregory J. Ohio State Univ Dept Biomed Informat Columbus OH 43210 USA Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA Ohio Supercomp Ctr Columbus OH USA Ohio State Univ Dept Otolaryngol Columbus OH 43210 USA Nationwide Childrens Hosp Columbus OH USA

To develop a time-efficient automated segmentation approach that could identify critical structures in the temporal bone for visual enhancement and use in surgical simulation software. An atlas-based segmentation approach was developed to segment the cochlea, ossicles, semicircular canals (SCCs), and facial nerve in normal temporal bone CT images. This approach was tested in images of 26 cadaver bones (13 left, 13 right). The results of the automated segmentation were compared to manual segmentation visually and using DICE metric, average Hausdorff distance, and volume similarity. The DICE metrics were greater than 0.8 for the cochlea, malleus, incus, and the SCCs combined. It was slightly lower for the facial nerve. The average Hausdorff distance was less than one voxel for all structures, and the volume similarity was 0.86 or greater for all structures except the stapes. The atlas-based approach with rigid body registration of the otic capsule was successful in segmenting critical structures of temporal bone anatomy for use in surgical simulation software.

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

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Localized-atlas-based segmentation of breast MRI in a decision-making framework

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AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2017年第1期40卷 69-84页

作者： Fooladivanda, Aida Shokouhi, Shahriar B. Ahmadinejad, Nasrin Iran Univ Sci & Technol Dept Elect Engn Tehran Iran Univ Tehran Med Sci Adv Diagnost & Intervent Radiol Res Ctr ADIR Tehran Iran

Breast-region segmentation is an important step for density estimation and Computer-Aided Diagnosis (CAD) systems in Magnetic Resonance Imaging (MRI). Detection of breast-chest wall boundary is often a difficult task due to similarity between gray-level values of fibroglandular tissue and pectoral muscle. This paper proposes a robust breast-region segmentation method which is applicable for both complex cases with fibroglandular tissue connected to the pectoral muscle, and simple cases with high contrast boundaries. We present a decision-making framework based on geometric features and support vector machine (SVM) to classify breasts in two main groups, complex and simple. For complex cases, breast segmentation is done using a combination of intensity-based and atlas-based techniques;however, only intensity-based operation is employed for simple cases. A novel atlas-based method, that is called localized-atlas, accomplishes the processes of atlas construction and registration based on the region of interest (ROI). atlas-based segmentation is performed by relying on the chest wall template. Our approach is validated using a dataset of 210 cases. based on similarity between automatic and manual segmentation results, the proposed method achieves Dice similarity coefficient, Jaccard coefficient, total overlap, false negative, and false positive values of 96.3, 92.9, 97.4, 2.61 and 4.77%, respectively. The localization error of the breast-chest wall boundary is 1.97 mm, in terms of averaged deviation distance. The achieved results prove that the suggested framework performs the breast segmentation with negligible errors and efficient computational time for different breasts from the viewpoints of size, shape, and density pattern.

关键词： Breast MRI Breast segmentation atlas-based segmentation Localized-atlas Geometric features Support vector machine (SVM)

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Multi-atlas-based segmentation of prostatic urethra from planning CT imaging to quantify dose distribution in prostate cancer radiotherapy

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RADIOTHERAPY AND ONCOLOGY 2017年第3期125卷 492-499页

作者： Acosta, Oscar Mylona, Eugenia Le Dain, Mathieu Voisin, Camille Lizee, Thibaut Rigaud, Bastien Lafond, Carolina Gnep, Khemara de Crevoisier, Renaud INSERM U1099 Rennes France Univ Rennes 1 Lab Traitement Signal & Image Rennes France Ctr Eugene Marquis Dept Radiotherapie Rennes France

Background and purpose: segmentation of intra-prostatic urethra for dose assessment from planning CT may help explaining urinary toxicity in prostate cancer radiotherapy. This work sought to: i) propose an automatic method for urethra segmentation in CT, ii) compare it with previously proposed surrogate models and iii) quantify the dose received by the urethra in patients treated with IMRT. Materials and methods: A weighted multi-atlas-based urethra segmentation method was devised from a training data set of 55 CT scans of patients receiving brachytherapy with visible urinary catheters. Leave-one-out cross validation was performed to quantify the error between the urethra segmentation and the catheter ground truth with two scores: the centerlines distance (CLD) and the percentage of centerline within a certain distance from the catheter (PWR). The segmentation method was then applied to a second test data set of 95 prostate cancer patients having received 78 Gy IMRT to quantify dose to the urethra. Results: Mean CLD was 3.25 +/- 1.2 mm for the whole urethra and 3.7 +/- 1.7 mm, 2.52 +/- 1.5 mm, and 3.01 +/- 1.7 mm for the top, middle, and bottom thirds, respectively. In average, 53% of the segmented centerlines were within a radius < 3.5 mm from the centerline ground truth and 83% in a radius < 5 mm. The proposed method outperformed existing surrogate models. In IMRT, urethra DVH was significantly higher than prostate DVH from V74 Gy to V79 Gy. Conclusion: A multi-atlas-based segmentation method was proposed enabling assessment of the dose within the prostatic urethra. (c) 2017 Elsevier B.V. All rights reserved.

关键词： Prostate cancer radiotherapy Urinary toxicity atlas-based segmentation Urethra segmentation Dose computation

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Evaluation of Non-Rigid Registration Parameters for atlas-based segmentation of CT Images of Human Cochlea

Evaluation of Non-Rigid Registration Parameters for Atlas-ba...

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Conference on Medical Imaging - Image Processing

作者： Elfarnawany, Mai Alam, S. Riyahi Agrawal, Sumit K. Ladak, Hanif M. Western Univ Dept Otolaryngol Head & Neck Surg London ON Canada Western Univ Dept Med Biophys London ON Canada Western Univ Dept Elect & Comp Engn London ON Canada

ISBN: (数字)9781510607125

ISBN: (纸本)9781510607118;9781510607125

Cochlear implant surgery is a hearing restoration procedure for patients with profound hearing loss. In this surgery, an electrode is inserted into the cochlea to stimulate the auditory nerve and restore the patient's hearing. Clinical computed tomography (CT) images are used for planning and evaluation of electrode placement, but their low resolution limits the visualization of internal cochlear structures. Therefore, high resolution micro-CT images are used to develop atlas-based segmentation methods to extract these nonvisible anatomical features in clinical CT images. Accurate registration of the high and low resolution CT images is a prerequisite for reliable atlas-based segmentation. In this study, we evaluate and compare different non-rigid B-spline registration parameters using micro-CT and clinical CT images of five cadaveric human cochleae. The varying registration parameters are cost function (normalized correlation (NC), mutual information and mean square error), interpolation method (linear, windowed-sinc and B-spline) and sampling percentage (1%, 10% and 100%). We compare the registration results visually and quantitatively using the Dice similarity coefficient (DSC), Hausdorff distance (HD) and absolute percentage error in cochlear volume. Using MI or MSE cost functions and linear or windowed-sinc interpolation resulted in visually undesirable deformation of internal cochlear structures. Quantitatively, the transforms using 100% sampling percentage yielded the highest DSC and smallest HD (0.828 +/- 0.021 and 0.25 +/- 0.09mm respectively). Therefore, B-spline registration with cost function: NC, interpolation: B-spline and sampling percentage: moments 100% can be the foundation of developing an optimized atlas-based segmentation algorithm of intracochlear structures in clinical CT images.

关键词： cochlear implant atlas-based segmentation non-rigid registration micro-computed tomography human cochlea three-dimensional model optimization cost-function

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A joint Snake and atlas-based segmentation of plantar foot thermal images 7

A joint Snake and Atlas-based segmentation of plantar foot t...

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7th International Conference on Image Processing Theory, Tools and Applications (IPTA)

作者： Bougrine, Asma Harba, Rachid Canals, Raphael Ledee, Roger Jabloun, Meryem Univ Orleans PRISME Lab Orleans France

ISBN: (纸本)9781538618424

The aim of the present study is to propose a new joint segmentation method dedicated to plantar foot thermal images. The proposed method is based on a modified active contour method (Snake) that includes a prior shape information, namely an atlas of the plantar foot contour, as an extra term in the Snake energy function. This term guides the Snake to the targeted contours during the deformation process, by calculating a curvature difference between the Snake curve and the atlas curve of the plantar foot surface. The proposed method was validated using a database of 50 plantar foot thermal images. Results showed the proposed method to outperform the classical Snake method and seven other recent methods. The comparison was done using two evaluation metrics, the root-mean-square error (RMSE) and the dice similarity coefficient (DSC). When compared to ground truth, the best average RMSE of 6 pixels and DSC score of 93% were obtained using the proposed method.

关键词： Infrared image segmentation atlas-based segmentation Active contours Plantar foot thermal images Diabetic foot

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Assessment of fully-automated atlas-based segmentation of novel oral mucosal surface organ-at-risk

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RADIOTHERAPY AND ONCOLOGY 2016年第1期119卷 166-171页

作者： Dean, Jamie A. Welsh, Liam C. McQuaid, Dualta Wong, Kee H. Aleksic, Aleksandar Dunne, Emma Islam, Mohammad R. Patel, Anushka Patel, Priyanka Petkar, Imran Phillips, Iain Sham, Jackie Newbold, Kate L. Bhide, Shreerang A. Harrington, Kevin J. Gulliford, Sarah L. Nutting, Christopher M. Inst Canc Res Joint Dept Phys London SW3 6JB England Royal Marsden NHS Fdn Trust London England Inst Canc Res Div Radiotherapy & Imaging London SW3 6JB England

Background and purpose: Current oral mucositis normal tissue complication probability models, based on the dose distribution to the oral cavity volume, have suboptimal predictive power. Improving the delineation of the oral mucosa is likely to improve these models, but is resource intensive. We developed and evaluated fully-automated atlas-based segmentation (ABS) of a novel delineation technique for the oral mucosal surfaces. Material and methods: An atlas of mucosal surface contours (MSC) consisting of 46 patients was developed. It was applied to an independent test cohort of 10 patients for whom manual segmentation of MSC structures, by three different clinicians, and conventional outlining of oral cavity contours (OCC), by an additional clinician, were also performed. Geometric comparisons were made using the dice similarity coefficient (DSC), validation index (VI) and Hausdorff distance (HD). Dosimetric comparisons were carried out using dose-volume histograms. Results: The median difference, in the DSC and HD, between automated-manual comparisons and manual-manual comparisons were small and non-significant (-0.024;p = 0.33 and -0.5;p = 0.88, respectively). The median VI was 0.086. The maximum normalised volume difference between automated and manual MSC structures across all of the dose levels, averaged over the test cohort, was 8%. This difference reached approximately 28% when comparing automated MSC and OCC structures. Conclusions: Fully-automated ABS of MSC is suitable for use in radiotherapy dose-response modelling. (C) 2016 The Authors. Published by Elsevier Ireland Ltd.

关键词： atlas-based segmentation Contouring Delineation OAR Oral mucosa Oral cavity

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atlas-based segmentation of Abdominal Organs in 3D Ultrasound, and its Application in Automated Kidney segmentation 37

Atlas-Based Segmentation of Abdominal Organs in 3D Ultrasoun...

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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Marsousi, Mahdi Plataniotis, Konstantinos N. Stergiopoulos, Stergios Univ Toronto Elect & Comp Engn Dept Toronto ON M5S 1A1 Canada Def Res & Dev Canada Toronto Toronto ON Canada

ISBN: (纸本)9781424492701

Automated segmentation of abdominal organs in 3D ultrasound images is an important and challenging task toward computer assisted emergency diagnosis. However, speckle noise, low-contrast organ tissues, intensity-profile inhomogeneity, and partial organ visibility are some ultrasound challenges which limits the utility of the automated diagnosis solutions. In this paper, an atlas-based method to automatically segment an organ of interest in abdominal 3D ultrasound images is proposed. The atlas model contains texture information and shape knowledge of the organ, which facilitates an accurate discrimination of organ from non-organ voxels in input 3D ultrasound images. The proposed method offers a mechanism to automatically detect the organ, and therefore, it eliminates the need of manual initialization of organ segmentation. The proposed method is applied to automatically segment the right kidney in 3D ultrasound images. The experimental results indicate that the proposed method provides a higher detection and segmentation accuracy compared to state-of-the-art.

关键词： atlas-based segmentation Abdominal Organs 3D Abdominal organ Organ Three Dimensions segmentation segmentation Ultrasonography Ultrasonic Waves AUTOMATIC

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atlas-based segmentation of brainstem regions in neuromelanin-sensitive magnetic resonance images

Atlas-based segmentation of brainstem regions in neuromelani...

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Computer-Aided Diagnosis (CAD) Conference at the SPIE Medical Imaging Symposium

作者： Puigvert, Marc Castellanos, Gabriel Uranga, Javier Abad, Ricardo Fernandez-Seara, Maria A. Pastor, Pau Pastor, Maria A. Munoz-Barrutia, Arrate Ortiz-de-Solorzano, Carlos Univ Navarra Clin Pamplona Spain Ctr Appl Med Res Imaging Lab Pamplona Spain Ctr Appl Med Res Neuroimaging Lab Pamplona Spain Ctr Appl Med Res Neurogenet Lab Pamplona Spain

ISBN: (纸本)9781628415049

We present a method for the automatic delineation of two neuromelanin rich brainstem structures -substantia nigra pars compacta (SN) and locus coeruleus (LC)- in neuromelanin sensitive magnetic resonance images of the brain. The segmentation method uses a dynamic multi-image reference atlas and a pre-registration atlas selection strategy. To create the atlas, a pool of 35 images of healthy subjects was pair-wise pre-registered and clustered in groups using an affinity propagation approach. Each group of the atlas is represented by a single exemplar image. Each new target image to be segmented is registered to the exemplars of each cluster. Then all the images of the highest performing clusters are enrolled into the final atlas, and the results of the registration with the target image are propagated using a majority voting approach. All registration processes used combined one two-stage affine and one elastic B-spline algorithm, to account for global positioning, region selection and local anatomic differences. In this paper, we present the algorithm, with emphasis in the atlas selection method and the registration scheme. We evaluate the performance of the atlas selection strategy using 35 healthy subjects and 5 Parkinson's disease patients. Then, we quantified the volume and contrast ratio of neuromelanin signal of these structures in 47 normal subjects and 40 Parkinson's disease patients to confirm that this method can detect neuromelanin-containing neurons loss in Parkinson's disease patients and could eventually be used for the early detection of SN and LC damage.

关键词： MRI neuromelanin Parkinson's disease elastic registration atlas-based segmentation affinity propagation

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