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The field of cryoEM has quickly advanced in last years with the new biochemical, technological, methodological and computational developments. It has allowed significant progresses in Structural Biology, typically reaching quasi-atomic resolutions in the reconstructed maps. However, this rapid advance has also generated new questions relevant to resolution estimates. The global resolution metrics and their criteria have been deeply discussed in the last decade, but despite that, it remains as an important issue in the field. Recently, the introduction of local resolution measurements has changed how cryoEM reconstructions are interpreted, providing information about the existence of heterogeneity, flexibility, and angular assignment errors, and using it as a tool to aid in modeling. In this review we revisit the concept of local resolution and the different algorithms in the current state of the art. However, the concept of local resolution is not uniquely defined, and each implementation measures different features. This may lead to inappropriate interpretation of local resolution maps. Hence, a set of good practices is provided in this review to avoid misleading and over-interpretation of the reconstructions., HD Tagare and JL Vilas are supported by NIH grant R01GM114051. E Ramirez-Aportela, COS Sorzano and JM Carazo were supported by The Spanish Ministry of Economy and Competitiveness through Grants BIO2016-76400-R(AEI/FEDER, UE), the ‘Comunidad Autónoma de Madrid’ through Grant: S2017/BMD-3817. This work was supported by the Intramural Research Program of the National Institute for Arthritis, Musculoskeletal and Skin Diseases, NIH.

BackgroundHydrocephalus, the pathological expansion of the cerebrospinal fluid (CSF)-filled cerebral ventricles, is a common, deadly disease. In the adult, cardiac and respiratory forces are the main drivers of CSF flow within the brain ventricular system to remove waste and deliver nutrients. In contrast, the mechanics and functions of CSF circulation in the embryonic brain are poorly understood. This is primarily due to the lack of model systems and imaging technology to study these early time points. Here, we studied embryos of the vertebrateXenopuswith optical coherence tomography (OCT) imaging to investigate in vivo ventricular and neural development during the onset of CSF circulation.MethodsOptical coherence tomography (OCT), a cross-sectional imaging modality, was used to study developingXenopustadpole brains and to dynamically detect in vivo ventricular morphology and CSF circulation in real-time, at micrometer resolution. The effects of immobilizing cilia and cardiac ablation were investigated.ResultsIn Xenopus, using OCT imaging, we demonstrated that ventriculogenesis can be tracked throughout development until the beginning of metamorphosis. We found that during Xenopus embryogenesis, initially, CSF fills the primitive ventricular space and remains static, followed by the initiation of the cilia driven CSF circulation where ependymal cilia create a polarized CSF flow. No pulsatile flow was detected throughout these tailbud and early tadpole stages. As development progressed, despite the emergence of the choroid plexus in Xenopus, cardiac forces did not contribute to the CSF circulation, and ciliary flow remained the driver of the intercompartmental bidirectional flow as well as the near-wall flow. We finally showed that cilia driven flow is crucial for proper rostral development and regulated the spatial neural cell organization.ConclusionsOur data support a paradigm in which Xenopus embryonic ventriculogenesis and rostral brain development are critically dependent on ependymal cilia-driven CSF flow currents that are generated independently of cardiac pulsatile forces. Our work suggests that the Xenopus ventricular system forms a complex cilia-driven CSF flow network which regulates neural cell organization. This work will redirect efforts to understand the molecular regulators of embryonic CSF flow by focusing attention on motile cilia rather than other forces relevant only to the adult.

Using a new consensus-based image-processing approach together with principal component analysis, the flexibility and conformational dynamics of the SARS-CoV-2 spike in the prefusion state have been analysed. These studies revealed concerted motions involving the receptor-binding domain (RBD), N-terminal domain, and subdomains 1 and 2 around the previously characterized 1-RBD-up state, which have been modeled as elastic deformations. It is shown that in this data set there are not well defined, stable spike conformations, but virtually a continuum of states. An ensemble map was obtained with minimum bias, from which the extremes of the change along the direction of maximal variance were modeled by flexible fitting. The results provide a warning of the potential image-processing classification instability of these complicated data sets, which has a direct impact on the interpretability of the results., The authors would like to acknowledge financial support from CSIC (PIE/COVID-19 No. 202020E079), the Comunidad de Madrid through grant CAM (S2017/BMD-3817), the Spanish Ministry of Science and Innovation through projects SEV 2017-0712, FPU-2015/264 and PID2019-104757RB-I00/AEI/FEDER, the Instituto de Salud Carlos III [PT17/0009/0010 (ISCIII-SGEFI/ERDF)], and the European Union and Horizon 2020 through grants INSTRUCT–ULTRA (INFRADEV-03-2016-2017, Proposal 731005), EOSC Life (INFRAEOSC-04-2018, Proposal 824087), HighResCells (ERC-2018-SyG, Proposal 810057), IMpaCT (WIDESPREAD-03-2018, Proposal 857203), CORBEL (INFRADEV-1-2014-1, Proposal 654248) and EOSC–Synergy (EINFRA-EOSC-5, Proposal 857647). HDT and BF were supported by NIH grant GM125769 and JSM was supported by NIH grant R01-AI127521.

Particle tracking velocimetry (PTV) gives quantitative estimates of fluid flow velocities from images. But particle tracking is a complicated problem, and it often produces results that need substantial post-processing. We propose a novel Gaussian process regression-based post-processing step for PTV: The method smooths (“denoises”) and densely interpolates velocity estimates while rejecting track irregularities. The method works under a large range of particle densities and fluid velocities. In addition, the method calculates standard deviances (error bars) for the velocity estimates, opening the possibility of propagating the standard deviances through subsequent processing and analysis. The accuracy of the method is experimentally evaluated using Optical Coherence Tomography images of particles in laminar flow in a pipe phantom. Following this, the method is used to quantify cilia-driven fluid flow and vorticity patterns in a developing Xenopus embryo.

Structural heterogeneity of particles can be investigated by their three-dimensional principal components. This paper addresses the question of whether, and with what algorithm, the three-dimensional principal components can be directly recovered from cryo-EM images. The first part of the paper extends the Fourier slice theorem to covariance functions showing that the three-dimensional covariance, and hence the principal components, of a heterogeneous particle can indeed be recovered from two-dimensional cryo-EM images. The second part of the paper proposes a practical algorithm for reconstructing the principal components directly from cryo-EM images without the intermediate step of calculating covariances. This algorithm is based on maximizing the (posterior) likelihood using the Expectation-Maximization algorithm. The last part of the paper applies this algorithm to simulated data and to two real cryo-EM data sets: a data set of the 70S ribosome with and without Elongation Factor-G (EF-G), and a data set of the inluenza virus RNA dependent RNA Polymerase (RdRP). The first principal component of the 70S ribosome data set reveals the expected conformational changes of the ribosome as the EF-G binds and unbinds. The first principal component of the RdRP data set reveals a conformational change in the two dimers of the RdRP.

Single particle reconstruction methods based on the maximum-likelihood principle and the expectation–maximization (E–M) algorithm are popular because of their ability to produce high resolution structures. However, these algorithms are computationally very expensive, requiring a network of computational servers. To overcome this computational bottleneck, we propose a new mathematical framework for accelerating maximum-likelihood reconstructions. The speedup is by orders of magnitude and the proposed algorithm produces similar quality reconstructions compared to the standard maximum-likelihood formulation. Our approach uses subspace approximations of the cryo-electron microscopy (cryo-EM) data and projection images, greatly reducing the number of image transformations and comparisons that are computed. Experiments using simulated and actual cryo-EM data show that speedup in overall execution time compared to traditional maximum-likelihood reconstruction reaches factors of over 300.

Cigarette smoking is a major public health danger. Women and men smoke for different reasons and cessation treatments, such as the nicotine patch, are preferentially beneficial to men. The biological substrates of these sex differences are unknown. Earlier PET studies reported conflicting findings but were each hampered by experimental and/or analytical limitations. Our new image analysis technique, lp-ntPET (Normandin et al., 2012; Morris et al., 2013; Kim et al., 2014), has been optimized for capturing brief (lasting only minutes) and highly localized dopaminergic events in dynamic PET data. We coupled our analysis technique with high-resolution brain scanning and high-frequency motion correction to create the optimal experiment for capturing and characterizing the effects of smoking on the mesolimbic dopamine system in humans. Our main finding is that male smokers smoking in the PET scanner activate dopamine in the right ventral striatum during smoking but female smokers do not. This finding—men activating more ventrally than women—is consistent with the established notion that men smoke for the reinforcing drug effect of cigarettes whereas women smoke for other reasons, such as mood regulation and cue reactivity. lp-ntPET analysis produces a novel multidimensional endpoint: voxel-level temporal patterns of neurotransmitter release (“DA movies”) in individual subjects. By examining these endpoints quantitatively, we demonstrate that the timing of dopaminergic responses to cigarette smoking differs between men and women. Men respond consistently and rapidly in the ventral striatum whereas women respond faster in a discrete subregion of the dorsal putamen.

Purpose Nonlinear spatial encoding magnetic (SEM) field strategies such as O-space imaging have previously reported dispersed artifacts during accelerated scans. Compressed sensing (CS) has shown a sparsity-promoting convex program allows image reconstruction from a reduced data set when using the appropriate sampling. The development of a pseudo-random center placement (CP) O-space CS approach optimizes incoherence through SEM field modulation to reconstruct an image with reduced error. Theory and Methods The incoherence parameter determines the sparsity levels for which CS is valid and the related transform point spread function measures the maximum interference for a single point. The O-space acquisition is optimized for CS by perturbing the Z2 strength within 30% of the nominal value and demonstrated on a human 3T scanner. Results Pseudo-random CP O-space imaging is shown to improve incoherence between the sensing and sparse domains. Images indicate pseudo-random CP O-space has reduced mean squared error compared with a typical linear SEM field acquisition method. Conclusion Pseudo-random CP O-space imaging, with a nonlinear SEM field designed for CS, is shown to reduce mean squared error of images at high acceleration over linear encoding methods for a 2D slice when using an eight channel circumferential receiver array for parallel imaging. Magn Reson Med 73:2212–2224, 2015. © 2014 Wiley Periodicals, Inc.

Purpose To investigate algebraic reconstruction technique (ART) for parallel imaging reconstruction of radial data, applied to accelerated cardiac cine. Methods A graphics processing unit (GPU)-accelerated ART reconstruction was implemented and applied to simulations, point spread functions and in 12 subjects imaged with radial cardiac cine acquisitions. Cine images were reconstructed with radial ART at multiple undersampling levels (192 Nr × Np = 96 to 16). Images were qualitatively and quantitatively analyzed for sharpness and artifacts, and compared to filtered back-projection, and conjugate gradient SENSE. Results Radial ART provided reduced artifacts and mainly preserved spatial resolution, for both simulations and in vivo data. Artifacts were qualitatively and quantitatively less with ART than filtered back-projection using 48, 32, and 24 Np, although filtered back-projection provided quantitatively sharper images at undersampling levels of 48-24 Np (all P

This paper considers the problem of segmenting the endocardium in 2-D short-axis echocardiographic images from rats by using the sparse representation of feature vectors over learned dictionaries during classification. We highlight important aspects of the application of the theory of sparse representation and dictionary learning to the problem of ultrasound image segmentation. Experiments were conducted following two directions for the generation of dictionaries for myocardium and blood pool regions; by manual extraction of image patches to build untrained dictionaries and by patch extraction followed by training of dictionaries. The results obtained from different learned dictionaries are compared. During classification of an image patch, instead of using features of the patch alone, features of neighboring patches are combined.

Intensity nonuniformity in magnetic resonance (MR) images, represented by a smooth and slowly varying function, is a typical artifact that is a nuisance for many image processing methods. To eliminate the artifact, we have to estimate the nonuniformity as a smooth and slowly varying function and factor it out from the given data. We reformulate the problem as a problem of finding a unique smooth function in a particular set of piecewise smooth functions and propose a variational method for finding it. We deliver the main idea using a simple one-dimensional example first and provide a thorough analysis of the problem in a three-phase scenario in three dimensions whose application can be found in the brain MR images. Experiments with synthetic and real MR images and a comparison with a state-of-the-art method, N3, show our algorithm's satisfactory performance in estimating the nonuniformity with and without noise. An automated procedure is also proposed for practical use.

A comprehensive analysis of the Parkinson's Progression Markers Initiative (PPMI) Dopamine Transporter Single Photon Emission Computed Tomography (DaTscan) images is carried out using a voxel-based logistic lasso model. The model reveals that sub-regional voxels in the caudate, the putamen, as well as in the globus pallidus are informative for classifying images into control and PD classes. Further, a new technique called logistic component analysis is developed. This technique reveals that intra-population differences in dopamine transporter concentration and imperfect normalization are significant factors influencing logistic analysis. The interactions with handedness, sex, and age are also evaluated.

A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the “class mean”, improves the signal-to-noise ratio in single particle reconstruction (SPR). The averaging step is often compromised because of outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods is done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a “w-estimator” of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions (CTFs) is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers.

A general-purpose all-fiber spectrometer is demonstrated to overcome the trade-off between spectral resolution and bandwidth. By integrating a wavelength division multiplexer with five multimode optical fibers, we have achieved 100 nm bandwidth with 0.03 nm resolution at wavelength 1500 nm. An efficient algorithm is developed to reconstruct the spectrum from the speckle pattern produced by interference of guided modes in the multimode fibers. Such algorithm enables a rapid, accurate reconstruction of both sparse and dense spectra in the presence of noise., Comment: 4 pages, 4 figures, in submission

This paper presents an algorithm for segmenting left ventricular endocardial boundaries from RF ultrasound. Our method incorporates a computationally efficient linear predictor that exploits short-term spatio-temporal coherence in the RF data. Segmentation is achieved jointly using an independent identically distributed (i.i.d.) spatial model for RF intensity and a multiframe conditional model that relates neighboring frames in the image sequence. Segmentation using the RF data overcomes challenges due to image inhomogeneities often amplified in B-mode segmentation and provides geometric constraints for RF phase-based speckle tracking. The incorporation of multiple frames in the conditional model significantly increases the robustness and accuracy of the algorithm. Results are generated using between 2 and 5 frames of RF data for each segmentation and are validated by comparison with manual tracings and automated B-mode boundary detection using standard (Chan and Vese-based) level sets on echocardiographic images from 27 3D sequences acquired from six canine studies.

This paper addresses the problem of indexing shapes in medical image databases. Shapes of organs are often indicative of disease, making shape similarity queries important in medical image databases. Mathematically, shapes with landmarks belong to shape spaces which are curved manifolds with a well defined metric. The challenge in shape indexing is to index data in such curved spaces. One natural indexing scheme is to use metric trees, but metric trees are prone to inefficiency. This paper proposes a more efficient alternative. We show that it is possible to optimally embed finite sets of shapes in shape space into a Euclidean space. After embedding, classical coordinate-based trees can be used for efficient shape retrieval. The embedding proposed in the paper is optimal in the sense that it least distorts the partial Procrustes shape distance. The proposed indexing technique is used to retrieve images by vertebral shape from the NHANES II database of cervical and lumbar spine X-ray images maintained at the National Library of Medicine. Vertebral shape strongly correlates with the presence of osteophytes, and shape similarity retrieval is proposed as a tool for retrieval by osteophyte presence and severity. Experimental results included in the paper evaluate (1) the usefulness of shape similarity as a proxy for osteophytes, (2) the computational and disk access efficiency of the new indexing scheme, (3) the relative performance of indexing with embedding to the performance of indexing without embedding, and (4) the computational cost of indexing using the proposed embedding versus the cost of an alternate embedding. The experimental results clearly show the relevance of shape indexing and the advantage of using the proposed embedding.

Purpose: In external beam radiation therapy of pelvic sites, patient setup errors can be quantified by registering 2D projection radiographs acquired during treatment to a 3D planning computed tomograph (CT). We present a 2D-3D registration framework based on a statistical model of the intensity values in the two imaging modalities. Methods: The model assumes that intensity values in projection radiographs are independently but not identically distributed due to the nonstationary nature of photon counting noise. Two probability distributions are considered for the intensity values: Poisson and Gaussian. Using maximum likelihood estimation, two similarity measures, maximum likelihood with a Poisson (MLP) and maximum likelihood with Gaussian (MLG), distribution are derived. Further, we investigate the merit of the model-based registration approach for data obtained with current imaging equipment and doses by comparing the performance of the similarity measures derived to that of the Pearson correlation coefficient (ICC) on accurately collected data of an anthropomorphic phantom of the pelvis and on patient data. Results: Registration accuracy was similar for all three similarity measures and surpassed current clinical requirements of 3 mm for pelvic sites. For pose determination experiments with a kilovoltage (kV) cone-beam CT (CBCT) and kV projection radiographs of the phantom inmore » the anterior-posterior (AP) view, registration accuracies were 0.42 mm (MLP), 0.29 mm (MLG), and 0.29 mm (ICC). For kV CBCT and megavoltage (MV) AP portal images of the same phantom, registration accuracies were 1.15 mm (MLP), 0.90 mm (MLG), and 0.69 mm (ICC). Registration of a kV CT and MV AP portal images of a patient was successful in all instances. Conclusions: The results indicate that high registration accuracy is achievable with multiple methods including methods that are based on a statistical model of a 3D CT and 2D projection images.« less

We define the space of affine shapes of k points in R n to be the topological quotient of (R n ) k modulo the natural action of the affine group of R n . These spaces arise naturally in many image-processing applications, and despite having poor separation properties, have some topological and geometric properties reminiscent of the more familiar Procrustes shape spaces Σ n k in which one identifies configurations related by an orientation-preserving Euclidean similarity transformation. We examine the topology of the connected, non-Hausdorff spaces Sh n k in detail. Each Sh n k is a disjoint union of naturally ordered strata, each of which is homeomorphic in the relative topology to a Grassmannian, and we show how the strata are attached to each other. The top stratum carries a natural Riemannian metric, which we compute explicitly for k>n, expressing the metric purely in terms of "pre-shape" data, i.e. configurations of k points in R n .

Aunque se considera que los aneurismas saculares de la aorta abdominal (AAA) son mas propensos a la rotura que los fusiformes, las tentativas para validar esta observacion han sido limitadas debido a la imposibilidad de definir cuantitativamente la morfologia tridimensional de la aorta. Un modelo cuantitativo de su estructura geometrica podria distinguir entre clases de morfologias y, en ultimo termino, ser util para identificar los aneurismas con riesgo de rotura. Se generaron datos tridimensionales de la superficie luminal de AAA a partir de imagenes tomograficas computarizadas (TC) de 15 pacientes con aneurismas de pequeno tamano (≤ 5,5 cm diametro transverso maximo). Se utilizo una linea central para producir una clasificacion de la morfologia basada en la proyeccion ortografica de la linea central alrededor de su eje central. Se cuantificaron la extension y direccion de las desviaciones individuales como areas en el plano de proyeccion para crear una clasificacion de la morfologia. Para verificar las diferentes clases de forma se uso un analisis de agrupacion jerarquica. Se calculo un indice de tortuosidad y se clasifico en diferentes clases desde mimima a maxima. La existencia de trombomural podria modificar el indice de tortuosidad o su clasificacion morfologica. En diversos pacientes con TC seriadas, el indice de tortuosidad cambio con el tiempo y se correlaciono con la rotura. En tres de ellos; en los que su AAA evoluciono hacia la rotura, la tortuosidad media aumento un 29% mientras que el diametro transverso medio aumento un 3,3%. Los AAA en expansion desarrollan morfologias especificas y cuantificables que pueden expresarse como un indice de tortuosidad cuantitativa que puede ser congruente con su historia natural. Las caracteristicas tridimensionales de este modelo morfologico proporcionan informacion complementaria a la simple medicion del diametro transverso maximo que puede resultar clinicamente adecuado. Se requieren estudios de mayor tamano para correlacionar el indice de tortuosidad con los modelos de elemento finito y la capacidad para predecir la rotura del aneurisma.

Alors que les anevrysmes de l'aorte abdominale (AAA) sacciformes sont consideres comme davantage enclins a la rupture que les anevrysmes fusiformes, les tentatives pour valider cette observation ont ete limitees par l'incapacite de definir quantitativement la forme tridimensionnelle d'une aorte. Un modele quantitatif tridimensionnel de forme pourrait permettre de distinguer les differentes formes et etre utile pour identifier les anevrysmes a risque de rupture. Les donnees tridimensionnelles d'AAA ont ete generees a partir d'images tomodensitometriques (TDM) chez 15 malades ayant des petits anevrysmes (≤ 5,5 cm de diametre transversal maximum). La ligne centrale a ete utilisee pour construire une classification morphologique basee sur la projection orthogonale de la ligne centrale suivant son axe. L'etendue et la direction des deviations individuelles ont ete quantifiees comme des zones du plan de projection pour creer une classification morphologique. Une analyse en groupes hierarchiques a ete utilisee pour verifier les differentes classes de forme. Un index de tortuosite a ete calcule en fonction de la projection de la ligne centrale. La forme de l'AAA a ete calculee comme un index de tortuosite et classee en differentes classes de tortuosite tridimensionnelle minime ou importante. La presence d'un thrombus pouvait modifier l'index de tortuosite ou la classification morphologique de l'anevrysme. Chez plusieurs malades ayant des TDM repetees, l'index de tortuosite a change au cours du temps et a ete correle a la rupture. Chez trois AAA qui se sont rompus, la tortuosite moyenne a augmente de 29 % alors que le diametre transversal moyen augmentait de 3,3 %. Les AAA en expansion developpent des formes specifiques quantifiables qui peuvent etre exprimees sous la forme d'un index quantitatif de tortuosite qui peut etre interessant pour etudier leur histoire naturelle. Les caracteristiques tridimensionnelles de ce modele de forme fournissent un element nouveau et sans doute interessant cliniquement par rapport au diametre maximum transversal. Des etudes plus larges sont necessaires pour correler l'index de tortuosite avec les modeles proposes et la capacite de prevenir la rupture d'anevrysme.

Active contours that evolve in ultrasound images under gradient descent are often trapped in spurious local minima. This paper presents an evolution strategy called tunneling descent, which is capable of escaping from such minima. The key idea is to evolve the contour by a sequence of constrained minimizations that move the contour in to, and out of, local minima. This strategy is an extension of classical gradient descent. Because tunneling descent does not terminate at a local minima an explicit stopping rule is required. Model-based and model-free stopping rules are presented and formulae for choosing the stopping threshold are given. The algorithm is used to segment the endocardium in 44 short axis cardiac ultrasound images. The energy function of the active contour is derived from a m.a.p. formulation. All segmentations are achieved without tweaking either the energy function or numerical parameters. Experimental evaluation of the segmentations show that the algorithm overcomes multiple local minima to find the endocardium. The accuracy of the algorithm is comparable to that of manual segmentations and significantly better than classical gradient descent active contours. The sensitivity of the segmentation to initialization is also evaluated and it is shown that segmentations from quite different initializations are close to each other. Finally, some limitations of the m.a.p. formulation are discussed.

OCT is a popular cross-sectional microscale imaging modality in medicine and biology. While structural imaging using OCT is a mature technology in many respects, flow and motion estimation using OCT remains an intense area of research. In particular, there is keen interest in maximizing information extraction from the complex-valued OCT signal. Here, we introduce a Bayesian framework into the data workflow in OCT-based velocimetry. We demonstrate that using prior information in this Bayesian framework can significantly improve velocity estimate precision in a correlation-based, model-based framework for Doppler and transverse velocimetry. We show results in calibrated flow phantoms as well as in vivo in a Drosophila melanogaster (fruit fly) heart. Thus, our work improves upon the current approaches in terms of improved information extraction from the complex-valued OCT signal.

This paper proposes a deterministic explanation for mutual-information-based image registration (MI registration). The explanation is that MI registration works because it aligns certain image partitions. This notion of aligning partitions is new, and is shown to be related to Schur- and quasi-convexity. The partition-alignment theory of this paper goes beyond explaining mutual- information. It suggests other objective functions for registering images. Some of these newer objective functions are not entropy-based. Simulations with noisy images show that the newer objective functions work well for registration, lending support to the theory. The theory proposed in this paper opens a number of directions for further research in image registration. These directions are also discussed.

Single Particle Reconstruction (SPR) for Cryogenic Electron Microscopy (cryo-EM) aligns and averages the images extracted from micrographs to improve the Signal-to-Noise ratio (SNR). Outliers compromise the fidelity of the averaging. We propose a robust cross-correlation-like w-estimator for combating the effect of outliers on the average images in cryo-EM. The estimator accounts for the natural variation of signal contrast among the images and eliminates the need for a threshold for outlier rejection. We show that the influence function of our estimator is asymptotically bounded. Evaluations of the estimator on simulated and real cryo-EM images show good performance in the presence of outliers.

We present a coupled minimization problem for image segmentation using prior shape and intensity profile. One part of the model minimizes a shape related energy and the energy of geometric active contour with a parameter that balances the influence from these two. The minimizer corresponding to a fixed parameter in this minimization gives a segmentation and an alignment between the segmentation and prior shape. The second part of this model optimizes the selection of the parameter by maximizing the mutual information of image geometry between the prior and the aligned novel image over all the alignments corresponding to different parameters in the first part. By this coupling the segmentation arrives at higher image gradient, forms a shape similar to the prior, and captures the prior intensity profile. We also propose using mutual information of image geometry to generate intensity model from a set of training images. Experimental results on cardiac ultrasound images are presented. These results indicate that the proposed model provides close agreement with expert traced borders, and the parameter determined in this model for one image can be used for images with similar properties.

A computer program named ‘ Finscan’ was developed for identifying individual marine animals by comparing new photographic images with a collection of previously identie ed images. The matching process was based on the pattern of nicks and notches commonly found along the trailing edge of the dorsal e n of many delphinid species. The program also allowed the inclusion of other user-dee ned descriptive features, such as leadingedge notches and truncated or irregular shapes. The output of the system was a presentation of images selected from the database, shown in order of similarity to a query image, so that the user could cone rm the match. Two algorithms for representing notch patterns were tested and compared and the system was evaluated with dorsal e n images of several marine vertebrates, as well as e uke images for one species. Using a database of images that were previously identie ed by expert observers, the performance of the system was measured in terms of the number of incorrect matches that were o Vered before the correct match. Since in most cases the correct match was oVered as the e rst or one of the e rst suggestions, the program substantially reduced the amount of eVort required to perform photo-based matching.

In this paper, we report an active contour algorithm that is capable of using prior shapes. The energy functional of the contour is modified so that the energy depends on the image gradient as well as the prior shape. The model provides the segmentation and the transformation that maps the segmented contour to the prior shape. The active contour is able to find boundaries that are similar in shape to the prior, even when the entire boundary is not visible in the image (i.e., when the boundary has gaps). A level set formulation of the active contour is presented. The existence of the solution to the energy minimization is also established. We also report experimental results of the use of this contour on 2d synthetic images, ultrasound images and fMRI images. Classical active contours cannot be used in many of these images.

A mathematical theory for establishing correspondences between curves and for non-rigid shape comparison is developed in this paper. The proposed correspondences, called bimorphisms, are more general than those obtained from one-to-one functions. Their topology is investigated in detail. A new criterion for non-rigid shape comparison using bimorphisms is also proposed. The criterion avoids many of the mathematical problems of previous approaches by comparing shapes non-rigidly from the bimorphism. Geometric invariants are calculated for curves whose shapes can be exactly matched with a bimorphism. The invariants are related to the concave and convex segments of a curve and provide justification for parsing the curve into such segments.

Preeclampsia is one of the leading causes of maternal death in developing and underdeveloped countries. A simple urine test, called the Congo Red Dot Test (CRD Test), was recently proposed to screen for preeclampsia. This paper reports an algorithm for automatically quantifying and interpreting the CRD Test. The algorithm can be easily programmed as an app on a smart phone. When evaluated on a pilot data set, the screening accuracy of the algorithm is high. The CRD Test and the algorithm can be easily deployed in resource-limited countries.

Random spherically-constrained (RSC) reconstruction is a new form of single particle reconstruction (SPR) using cryo-EM images of membrane proteins embedded in spherical lipid vesicles to generate a 3D protein structure. The method has many advantages over conventional SPR, including a more native environment for protein particles and an initial estimate of the particle's angular orientation. These advances allow us to determine structures of membrane proteins such as ion channels and derive more reliable structure estimates. We present an algorithm that relates conventional SPR to the RSC model, and generally, to projection images of particles embedded with an axis parallel to the local normal of a general 2D manifold. We illustrate the performance of this algorithm in the spherical system using synthetic data.

A precise analysis of an entire image is computationally wasteful if one is interested in finding a target object located in a subregion of the image. A useful "attention strategy" can reduce the overall computation by carrying out fast but approximate image measurements and using their results to suggest a promising subregion. The paper proposes a maximum-likelihood attention mechanism that does this. The attention mechanism recognizes that objects are made of parts and that parts have different features. It works by proposing object part and image feature pairings which have the highest likelihood of coming from the target. The exact calculation of the likelihood as well as approximations are provided. The attention mechanism is adaptive, that is, its behavior adapts to the statistics of the image features. Experimental results suggest that, on average, the attention mechanism evaluates less than 2 percent of all part-feature pairs before selecting the actual object, showing a significant reduction in the complexity of visual search.

Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema.

In this paper a new formulation of the two-dimensional (2-D) deformable template matching problem is proposed. It uses a lower-dimensional search space than conventional methods by precomputing extensions of the deformable template along orthogonal curves. The reduction in search space allows the use of dynamic programming to obtain globally optimal solutions and reduces the sensitivity of the algorithm to initial placement of the template. Further, the technique guarantees that the result is a curve which does not collapse to a point in the absence of strong image gradients and is always nonself intersecting. Examples of the use of the technique on real-world images and in simulations at low signal-to-noise ratios (SNR's) are also provided.

The capacity to retrieve images containing objects with shapes similar to a query shape is desirable in medical image databases. We propose a similarity measure and an indexing mechanism for non-rigid comparison of shape which adds this capability to image databases. The (dis)-similarity measure is based on the observations that: (1) the geometry of the same organ in different subjects is not related by a strictly rigid transformation; and (2) the orientation of the organ plays a key role in comparing shape. We propose a similarity measure that computes a non-rigid mapping between curves and uses this mapping to compare oriented shape. We also show how KD-trees can index curves so that retrieval with our similarity measure is efficient. Experiments with real-world data from a database of magnetic resonance images are provided.

Medical tomographic images are formed by the intersection of the image plane and an object. As the image plane changes, different parts of the object come in view or drop out of view. However, for small changes of the image plane, most parts continue to remain visible and their qualitative embedding in the image remains similar. Therefore, similarity of part embeddings can be used to infer similarity of image planes. Part embeddings are useful features for other vision applications as well. In view of this, a spatial relation called "arrangement" is proposed to describe part embeddings. The relation describes how each part is surrounded by its neighbors. Further, a metric for arrangements is formulated by expressing arrangements in terms of the Voronoi diagram of the parts. Arrangements and their metric are used to retrieve images by image plane similarity in a cardiac magnetic resonance image database. Experiments with the database are reported which (1) validate the observation that similarity of image planes can be inferred from similarity of part embeddings, and (2) compare the performance of arrangement based image retrieval with that of expert radiologists. >

Generation of parametric images of myocardial blood flow (MBF) from dynamic PET requires a reproducible and reliable method to obtain left and right ventricular time-activity curves. We propose the use of Independent Component Analysis (ICA) on PET temporal information to segment the image data into three categories: right ventricle (RV), left ventricle (LV) and myocardium. ICA is an established signal processing technique that assumes that the dynamic signal in each voxel is a linear mixture of signals from statistically independent sources. The mixing process is due to cardiac motion and partial volume effects. Due to its ability to find the intensity of the underlying sources, ICA generates a 3D map of the mixing coefficients that allows the segmentation of structures. Dynamic cardiac PET data were acquired with a Siemens Biograph mCT PET/CT scanner using Rb-82 and [15O]water in nonhuman primate and pigs with injections of different activities. The Dice similarity coefficient (DSC) was used to compare the segmentations between scans of different species with different tracers. The LV and RV regions were used to calculate input functions for kinetic analysis and MBF estimation. Pairwise comparisons of the segmentations between different [15O]water PET scans gave DSC of 0.91 ± 0.09 and 0.92±0.08 for the RV and LV segmentations, respectively. For Rb-82 PET scans, the DSC values were of 0.89 ± 0.09 and 0.85±0.10 for RV and LV. We used contrast CT as a gold standard for the LV and RV segmentations. Pairwise comparisons of the segmentations between different contrast CT and Rb-82 PET scans gave DSC of 0.86 ± 0.09 and 0.85±0.09 for the RV and LV, respectively. Our work shows the reliability and reproducibility of the results of the segmentation algorithm. High quality parametric images of MBF and the kinetic parameters were obtained. These results suggest that ICA may be useful to extract time-activity curves for kinetic MBF analysis. The effects of partial volume on input TAC determination were also evaluated.

Sequences that encode the spatial information of an object using nonlinear gradient fields are a new frontier in MRI, with potential to provide lower peripheral nerve stimulation, windowed fields of view, tailored spatially-varying resolution, curved slices that mirror physiological geometry, and, most importantly, very fast parallel imaging with multichannel coils. The acceleration for multichannel images is generally explained by the fact that curvilinear gradient isocontours better complement the azimuthal spatial encoding provided by typical receiver arrays. However, the details of this complementarity have been more difficult to specify. We present a simple and intuitive framework for describing the mechanics of image formation with nonlinear gradients, and we use this framework to review some the main classes of nonlinear encoding schemes.

Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. This paper proposes a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis adapts to the data, the reconstruction resolution and signal-to-noise ratio (SNR) is improved compared to a reconstruction with a fixed basis. Moreover, the algorithm automatically masks the particle, thereby separating it from the background. This eliminates the need for ad hoc filtering or masking in the refinement loop. The algorithm is formulated in a Bayesian maximum-a-posteriori framework and uses an efficient optimization algorithm for the maximization. Evaluations using simulated and actual cryogenic electron microscopy data show resolution and SNR improvements as well as the effective masking of particle from background.

We propose a level set based deformable model for the segmentation of multiple objects from 3D medical images using shape prior constraints. As an extension to the level set distribution model of object shape presented in previous papers, this paper evaluates the performance of the level set representation of the object shape by comparing it with the point distribution model(PDM) using the Chi-square test. We define a maximum a posteriori (MAP) estimation model using level set based prior information to realize the segmentation of the multiple objects. To achieve this , only one level set function is employed as the representation of the multiple objects of interest within the image. We then define the probability distribution over the variations of objects contained in a set of training images. We found the algorithm to be computationally efficient, robust to noise, able to handle multidimensional data, and avoids the need for explicit point correspondences during the training phase. Results and validation from various experiments on 2D/3D medical images are demonstrated.

We present an approach for left ventricular segmentation of radio-frequency (RF) ultrasound sequences. Our method employs an independent identically distributed (iid) spatial model for RF voxel intensity and a conditional model relating a subsequent frame in the image sequence to the frame being segmented by means of a linear predictor that exploits spatio-temporal coherence in the data. The conditional model overcomes segmentation problems due to image inhomogeneity issues, while the spatial model overcomes a tendency of the conditional model to underestimate the blood pool. The method is validated by comparison with manual tracings, segmentations performed using Chan-Vese level sets, and by segmentations leveraging only the linear predictor.

The carpal regions of ten cadaver extremities were imaged by CT. The images were combined into a 3-dimensional model of the carpus using a technique based on a dynamic programming algorithm to find an optimal estimate of the location of the bone boundaries in the CT images. The resulting set of surface points on each bone was used to compute volumes and principal and antipodal axes for the bones. A spatial coordinate system was established based on the positions of the centroids of three bones in the distal carpal row. The angular orientations of all carpal bones were determined with respect to this system. The principal axes for the same bone among ten wrist specimens proved to be more widely dispersed than the antipodal axes for the same bones. The antipodal axes also correspond more closely to an intuitive notion of the "longest axis" of the bones. We conclude that the antipodal axis is a more reliable and useful measure of bone orientation than the principal axis.

A reflectance map is the transfer function from surface orientation and illumination geometry to the surface normal, and in machine vision it plays a fundamental role in the reconstruction of surface by shape-from-shading and photometric stereo algorithms. While reflectance maps for Lambertain and specular surfaces are well understood, maps for real-world diffusely reflecting surfaces are scant. In this paper, the fundamental mechanisms of reflection from such surfaces are reviewed. Based on this, it is proposed that for point light source illumination, the diffuse component of the reflectance map has three terms: a forescatter term, a normal term, and a backscatter term. The physical origin of the three terms is discussed in detail and useful mathematical expressions are obtained for them. The range of applicability of the proposed reflectance maps is established, and an example of their use in photometric stereo is provided. The mathematical form of the reflectance map obtained from physical theories is amenable to generalization and such a generalization is called the m-lobed reflectance map is proposed.

This paper investigates whether the shape of an object and certain parameters of its reflectance map can be simultaneously estimated using photometric stereo. This problem has been addressed in the literature for the case where the Lambertian and non-Lambertian components in the image can be easily separated. No such separability is assumed in this paper. A class of reflectance maps for modeling diffusely reflecting surfaces is proposed. This class is based on the physics of scattering from real world surfaces. Next, the problem of joint estimation of some parameters of the map along with the surface shape is analyzed. A bound is obtained on the number of light sources necessary for a unique solution to the problem. The analysis also reveals that some of the estimates can be obtained by a nonparametric method. The behavior of the estimates in the presence of noise is also investigated. It is shown that simultaneous estimation is ill-posed. Regularizing the estimates yields good reconstructions from real world data.

In external beam radiation therapy of pelvic sites, patient setup errors can be quantified by registering 2D projection radiographs acquired during treatment to a 3D planning computed tomograph (CT). We present a 2D-3D registration framework based on a statistical model of the intensity values in the two imaging modalities.The model assumes that intensity values in projection radiographs are independently but not identically distributed due to the nonstationary nature of photon counting noise. Two probability distributions are considered for the intensity values: Poisson and Gaussian. Using maximum likelihood estimation, two similarity measures, maximum likelihood with a Poisson (MLP) and maximum likelihood with Gaussian (MLG), distribution are derived. Further, we investigate the merit of the model-based registration approach for data obtained with current imaging equipment and doses by comparing the performance of the similarity measures derived to that of the Pearson correlation coefficient (ICC) on accurately collected data of an anthropomorphic phantom of the pelvis and on patient data.Registration accuracy was similar for all three similarity measures and surpassed current clinical requirements of 3 mm for pelvic sites. For pose determination experiments with a kilovoltage (kV) cone-beam CT (CBCT) and kV projection radiographs of the phantom in the anterior-posterior (AP) view, registration accuracies were 0.42 mm (MLP), 0.29 mm (MLG), and 0.29 mm (ICC). For kV CBCT and megavoltage (MV) AP portal images of the same phantom, registration accuracies were 1.15 mm (MLP), 0.90 mm (MLG), and 0.69 mm (ICC). Registration of a kV CT and MV AP portal images of a patient was successful in all instances.The results indicate that high registration accuracy is achievable with multiple methods including methods that are based on a statistical model of a 3D CT and 2D projection images.