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Conference on Medical Imaging - Image Processing

作者： Reaungamornrat, S. Carass, A. He, Y. Saidha, S. Calabresi, P. A. Prince, J. L. Johns Hopkins Univ Hosp Dept Neurol Baltimore MD 21287 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA

ISBN: (数字)9781510616387

ISBN: (纸本)9781510616387

Purpose: OCT offers high in-plane micrometer resolution, enabling studies of neurodegenerative and ocular-disease mechanisms via imaging of the retina at low cost. An important component to such studies is inter-scanner deformable image registration. Image quality of OCT, however, is suboptimal with poor signal-to-noise ratio and through-plane resolution. Geometry of OCT is additionally improperly defined. We developed a diffeomorphic deformable registration method incorporating constraints accommodating the improper geometry and a decentralized-modality-insensitive neighborhood-descriptors (D-MIND) robust against degradation of OCT image quality and inter-scanner variability. Method: The method, called D-MIND demons, estimates diffeomorphisms using D-MINDs under constraints on the direction of velocity fields in a MIND-demons framework. Descriptiveness of D-MINDs with/without denoising was ranked against four other shape/texture-based descriptors. Performance of D-MIND demons and its variants incorporating other descriptors was compared for cross-scanner, intra- and inter-subject deformable registration using clinical retina OCT data. Result: D-MINDs outperformed other descriptors with the difference in mutual descriptiveness between high-contrast and homogenous regions > 0.2. Among demons variants, D-MIND-demons was computationally efficient, demonstrating robustness against OCT image degradation (noise, speckle, intensity-non-uniformity, and poor through plane resolution) and consistent registration accuracy [(4 +/- 4 mu m) and (4 +/- 6 mu m) in cross-scanner intra- and inter-subject registration] regardless of denoising. Conclusions: A promising method for cross-scanner, intra- and inter-subject OCT image registration has been developed for ophthalmological and neurological studies of retinal structures. The approach could assist image segmentation, evaluation of longitudinal disease progression, and patient population analysis, which in turn, facilitate diagnos

关键词： deformable image registration demons algorithm diffeomorphism descriptors optical coherence tomography OCT

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A Less Computation Intensive Non-Rigid Image Registration by Modifying demons Deformation algorithm

A Less Computation Intensive Non-Rigid Image Registration by...

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2nd International Conference on Advances in Electrical Engineering (ICAEE)

作者： Mondal, Pulak Mishra, Ashutosh Banerjee, Swapna IIT Kharagpur E& ECE Dept Kharagpur W Bengal India

ISBN: (纸本)9781479924653

Image registration is the process of aligning two images of different modalities or images acquired at different times using the same modality. Minimization of the alignment error with less computation is a challenging task especially in a medical imaging system. To deform the image for alignment with reference image, the demons deformation algorithm has been used extensively. This paper presents some modification in demons deformation algorithm which helps to reduce alignment error as well as runtime by 25% and 33% respectively.

关键词： demons algorithm Medical Image Processing Non-Rigid Image Registration

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Respiratory motion correction with an improved demons algorithm for PET images

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Chinese Physics C 2012年第10期36卷 1025-1030页

作者：高娟柴培贠明凯刘双全单保慈魏龙 Key Laboratory of Nuclear Analysis Techniques Institute of High Energy Physics Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Respiratory motion is a major factor that affects the quality of PET images of the thoracic area. The diaphragm moves about 15–20 mm due to respiratory motion, which substantially degrades the effective spatial resolution of PET. In this paper, a gated acquisition method is used to correct the motion effects. In this method, an improved demons algorithm is proposed to align the gated images. The experimental results show that the quality of PET images is significantly improved when using our improved method and the proposed method has a faster convergence rate than the original demons algorithm.

关键词： motion correction demons algorithm discontinuity PET

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Evaluation of Free Form Deformation and demons Registration with Discontinuities

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2018年第1期25卷 302-307页

作者： Skejic, Emir Demirovic, Damir Gleich, Dusan Serifovic-Trbalic, Amira Univ Tuzla Fac Elect Engn Franjevacka 2 Tuzla 75000 Bosnia & Herceg Univ Maribor Fac Elect Engn & Comp Sci Smetanova Ulica 17 SLO-2000 Maribor Slovenia

Medical image registration plays an important part in most today's clinical procedures. Registration goal is to find transformation which warps one image into the space of another. Registration of moving organs in human body has a significant part in therapy planning. This task is harder in cases when one organ (tissue) slides along another, i.e. in a case of discontinuities in the motion field. Discontinuities introduce unwanted transformations which often lead to poor or unsatisfied registration results. In this paper we evaluate one form of discontinuities for two well-known and used registration algorithms namely Free Form Deformation and demons.

关键词： demons algorithm discontinuities free form deformation medical image registration

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Time-series registration of thermal breast images

Time-series registration of thermal breast images

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作者： Mikko Karjalainen Aalto University

学位级别：硕士

Dynamic infrared imaging (DIRI) is an emerging technology for the early detection of breast cancer. In this method time-series of thermal breast images are obtained. The patient motion in the time-series can distort the DIRI analysis in such a way that the detection of breast cancer becomes impossible. Image registration can be used to eliminate the patient motion from the time-series data. In this thesis, two different registration algorithms were tested: Thirion's demons algorithm and an algorithm based on an affine transformation. Furthermore, a combined method where the affine method is used as a pre-registration step for the demons method was tested. The algorithms were implemented with Matlab and their performance in the task of registering a time-series of thermal breast images was evaluated using four different performance metrics. The registration algorithms were implemented for time-series data of 20 healthy (no malignant lesions) subjects. The demons method outperformed the affine method and is recommended as a suitable tool for time-series registration of thermal breast images. The combined method achieved slightly improved results compared to the demons method but with significantly increased computation time.

关键词： Medical imaging Image registration Breast cancer demons algorithm Dynamic infrared imaging

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Free-Form Deformation Approach for Registration of Visible and Infrared Facial Images in Fever Screening

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SENSORS 2018年第1期18卷 125-125页

作者： Chenna, Yedukondala Narendra Dwith Ghassemi, Pejhman Pfefer, T. Joshua Casamento, Jon Wang, Quanzeng US FDA Ctr Devices & Radiol Hlth Silver Spring MD 20993 USA Univ Maryland Dept Elect & Comp Engn College Pk MD 20740 USA

Fever screening based on infrared (IR) thermographs (IRTs) is an approach that has been implemented during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome. A recently published international standard indicates that regions medially adjacent to the inner canthi provide accurate estimates of core body temperature and are preferred sites for fever screening. Therefore, rapid, automated identification of the canthi regions within facial IR images may greatly facilitate rapid fever screening of asymptomatic travelers. However, it is more difficult to accurately identify the canthi regions from IR images than from visible images that are rich with exploitable features. In this study, we developed and evaluated techniques for multi-modality image registration (MMIR) of simultaneously captured visible and IR facial images for fever screening. We used free form deformation (FFD) models based on edge maps to improve registration accuracy after an affine transformation. Two widely used FFD models in medical image registration based on the demons and cubic B-spline algorithms were qualitatively compared. The results showed that the demons algorithm outperformed the cubic B-spline algorithm, likely due to overfitting of outliers by the latter method. The quantitative measure of registration accuracy, obtained through selected control point correspondence, was within 2.8 +/- 1.2 mm, which enables accurate and automatic localization of canthi regions in the IR images for temperature measurement.

关键词： thermal imaging fever screening temperature measurement canthi detection multi-modality image registration free form deformation demons algorithm cubic B-spline algorithm

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3D dental image registration using exhaustive deformable models: a comparative study

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DENTOMAXILLOFACIAL RADIOLOGY 2017年第7期46卷 20160390-20160390页

作者： Kalla, Maria-Pavlina Economopoulos, Theodore L. Matsopoulos, George K. Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece

Objectives: Image registration is commonly used in dental applications for aligning imaging data sets, which is particularly useful when assessing the progression or regression of particular pathomorphic conditions. However, due to the nature of the processed data or the data acquisition process itself, rigid body registration may be insufficient to accurately align the processed data sets. In such cases, deformable models are employed. This study presents a comparison of four well-established deformable models for aligning CBCT volumes. Methods: The compared models include the original demons algorithm, symmetric forces demons, diffeomorphic demons and level-set motion. The compared techniques are incorporated into a general image registration scheme featuring two distinct stages: a common, fast, rigid-based alignment for pre-registering the data and a finer elastic registration phase, based on the four compared deformation models. Results: The proposed framework was applied to a total of 40 CBCT volume pairs with known and unknown initial differences. Conclusions: After both qualitative and quantitative assessment of the produced aligned data, it was concluded that the level-set motion method outperformed all other techniques for data pairs with both unknown initial differences, as well as with known elastic deviations based on fixed sinusoidal models and B-splines.

关键词： Cone-beam computed tomography image registration elastic deformation models demons algorithm symmetric forces demons diffeomorphic demons level-set motion

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MIND demons: Symmetric Diffeomorphic Deformable Registration of MR and CT for Image-Guided Spine Surgery

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2016年第11期35卷 2413-2424页

作者： Reaungamornrat, Sureerat De Silva, Tharindu Uneri, Ali Vogt, Sebastian Kleinszig, Gerhard Khanna, Akhil J. Wolinsky, Jean-Paul Prince, Jerry L. Siewerdsen, Jeffrey H. Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21205 USA Siemens Healthcare XP D-91052 Erlangen Germany Johns Hopkins Orthopaed Surg Dept Orthopaed Surg Bethesda MD USA Johns Hopkins Univ Hosp Dept Neurosurg Baltimore MD 21205 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA

Intraoperative localization of target anatomy and critical structures defined in preoperative MR/CT images can be achieved through the use of multimodality deformable registration. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality-independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND demons, finds a deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the integrated velocity fields, a modality-insensitive similarity function suitable to multimodality images, and smoothness on the diffeomorphisms themselves. Direct optimization without relying on the exponential map and stationary velocity field approximation used in conventional diffeomorphic demons is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, normalized MI (NMI) demons, and MIND with a diffusion-based registration method (MIND-elastic). The method yielded sub-voxel invertibility (0.008 mm) and nonzero-positive Jacobian determinants. It also showed improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.7 mm compared to 11.3, 3.1, 5.6, and 2.4 mm for MI FFD, LMI FFD, NMI demons, and MIND-elastic methods, respectively. Validation in clinical studies demonstrated realistic deformations with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine.

关键词： deformable image registration demons algorithm symmetric diffeomorphism multimodality image registration MIND CT MRI image-guided surgery

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Regional information entropy demons for infrared image nonrigid registration

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OPTIK 2016年第1期127卷 227-231页

作者： Lu Chaoliang Ma Lihua Yu Min Cui Shumin AFEU Sch Informat & Nav Xian 710077 Shaanxi Peoples R China

Infrared imaging fault detection which was treated as an ideal, noncontact, and nondestructive testing method was applied to the circuit board fault detection. Nonrigid deformation was existed between the fault circuit board infrared image and the well-performance circuit board infrared image. To solve this problem, a new demons algorithm based on regional information entropy was proposed. The new method used regional information entropy instead of image's intensity to overcome the shortcomings of traditional demons algorithm, which was sensitive to the intensity. The inertia parameter was introduced to improve the convergence performance, which was another improvement. In inertia parameter study, the value of inertia parameter was suitable at about 0.6. The simulated study and experiment of realistic infrared image study had shown that the proposed algorithm could match the images whose intensity has difference, while the original active demons algorithm could not. The convergence performance with the inertia parameter had been improved about twice times in experiment. (C) 2015 Elsevier GmbH. All rights reserved.

关键词： Image processing demons algorithm Information entropy Nonrigid registration Regional information entropy

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Modified demons Deformation algorithm for Non-Rigid Image Registration

Modified Demons Deformation Algorithm for Non-Rigid Image Re...

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4th International Conference on Intelligent Human Computer Interaction (IHCI)

作者： Mishra, Ashutosh Mondal, Pulak Banerjee, Swapna Indian Inst Technol Kharagpur Dept Elect & Elect Engn Kharagpur W Bengal India

ISBN: (纸本)9781467343695

Image registration is a technique used for aligning two different images taken at different times and/or from different viewing and different imaging setups/modalities. A key challenge for medical image registration is to minimize computation time and reduce alignment errors. The demons deformation algorithm has been used extensively for deformation medical images for image registration. In this paper we present modifications to demons deformation algorithm that reduce runtime while giving good deformation.

关键词： Deformable Image Registration demons algorithm Medical Image Processing Non-Rigid Image Registration

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