A cortical locus for the processing of contrast-defined contours

Object boundaries in the natural environment are often defined by changes in luminance; in other cases, however, there may be no difference in average luminance across the boundary, which is instead defined by more subtle 'second-order' cues, such as changes in the contrast of a fine-grained texture. The detection of luminance boundaries may be readily explained in terms of visual cortical neurons, which compute the linear sum of the excitatory and inhibitory inputs to different parts of their receptive field. The detection of second-order stimuli is less well understood, but is thought to involve a separate nonlinear processing stream, in which boundary detectors would receive inputs from many smaller subunits. To address this, we have examined the properties of cortical neurons which respond to both first- and second-order stimuli. We show that the inputs to these neurons are also oriented, but with no fixed orientational relationship to the neurons they subserve. Our results suggest a flexible mechanism by which the visual cortex can detect object boundaries regardless of whether they are defined by luminance or texture.     

Frontal cortex lesion prior to hyperglycemic ischemia: no decrease in ensuing substantia nigra pars reticulata damage or fatal post-ischemic seizures

Summary Preischemic hyperglicemia worsens brain damage after ischemia, and characteristically leads to post-ischemic seizures and a pan-necrotic lesion in substantia nigra pars reticulata (SNPR). The excitatory input to SNPR could contribute to the damage observed. By performing a unilateral frontal cortex lesion 6–19 days prior to the ischemia, we wanted to explore whether a decrease in excitatory input to the ipsilateral SNPR ameliorate the seizures or alter the light microscopical damage in SNPR. Our results demonstrate that unilateral frontal cortex lesion did not alter the development of fatal post-ischemic seizures after 10 min of ischemia in hyperglycemic subjects. Thus, 7/8 animals developed seizures and died within 20 h of recovery. This study also failed to show any difference between the left and right side in post-ischemic SNPR damage after 15 h of recovery in animals with preischemic unilateral frontal cortex lesion. Furthermore, no side difference was observed in any other brain region evaluated. The results thus suggest that the pan-necrotic lesion in SNPR after hyperglicemic ischemia is not caused by excessive excitatory input from frontal cortex. A decrease in the GABA-ergic inhibitory input from caudoputamen to SNPR may be a more important mechanism for the ensuing excitotoxic post-ischemic SNPR damage, and for seizure development.     

Detection performance analysis for time-of-flight PET

In this paper, we investigate the performance of time-of-flight (TOF) positron emission tomography (PET) in improving lesion detectability. We present a theoretical approach to compare lesion detectability of TOF versus non-TOF systems and perform computer simulations to validate the theoretical prediction. A single-ring TOF PET tomograph is simulated using SimSET software, and images are reconstructed in 2D from list-mode data using a maximum a posteriori method. We use a channelized Hotelling observer to assess the detection performance. Both the receiver operating characteristic (ROC) and localization ROC curves are compared for the TOF and non-TOF PET systems. We first studied the SNR gains for TOF PET with different scatter and random fractions, system timing resolutions and object sizes. We found that the TOF information improves the lesion detectability and the improvement is greater with larger fractions of randoms, better timing resolution and bigger objects. The scatters by themselves have little impact on the SNR gain after correction. Since the true system timing resolution may not be known precisely in practice, we investigated the effect of mismatched timing kernels and showed that using a mismatched kernel during reconstruction always degrades the detection performance, no matter whether it is narrower or wider than the real value. Using the proposed theoretical framework, we also studied the effect of lumpy backgrounds on the detection performance. Our results indicated that with lumpy backgrounds, the TOF PET still outperforms the non-TOF PET, but the improvement is smaller compared with the uniform background case. More specifically, with the same correlation length, the SNR gain reduces with bigger number of lumpy patches and greater lumpy amplitudes. With the same variance, the SNR gain reaches the minimum when the width of the Gaussian lumps is close to the size of the tumor.     

A spatial analysis of genetic structure of human populations in China reveals distinct difference between maternal and paternal lineages

Analyses of archeological, anatomical, linguistic, and genetic data suggested consistently the presence of a significant boundary between the populations of north and south in China. However, the exact location and the strength of this boundary have remained controversial. In this study, we systematically explored the spatial genetic structure and the boundary of north-south division of human populations using mtDNA data in 91 populations and Y-chromosome data in 143 populations. Our results highlight a distinct difference between spatial genetic structures of maternal and paternal lineages. A substantial genetic differentiation between northern and southern populations is the characteristic of maternal structure, with a significant uninterrupted genetic boundary extending approximately along the Huai River and Qin Mountains north to Yangtze River. On the paternal side, however, no obvious genetic differentiation between northern and southern populations is revealed.     

Multi-Resolution Level Sets with Shape Priors: A Validation Report for 2D Segmentation of Prostate Gland in T2W MR Images

The level set approach to segmentation of medical images has received considerable attention in recent years. Evolving an initial contour to converge to anatomical boundaries of an organ or tumor is a very appealing method, especially when it is based on a well-defined mathematical foundation. However, one drawback of such evolving method is its high computation time. It is desirable to design and implement algorithms that are not only accurate and robust but also fast in execution. Bresson et al. have proposed a variational model using both boundary and region information as well as shape priors. The latter can be a significant factor in medical image analysis. In this work, we combine the variational model of level set with a multi-resolution approach to accelerate the processing. The question is whether a multi-resolution context can make the segmentation faster without affecting the accuracy. As well, we investigate the question whether a premature convergence, which happens in a much shorter time, would reduce accuracy. We examine multiple semiautomated configurations to segment the prostate gland in T2W MR images. Comprehensive experimentation is conducted using a data set of a 100 patients (1,235 images) to verify the effectiveness of the multi-resolution level set with shape priors. The results show that the convergence speed can be increased by a factor of ≈?2.5 without affecting the segmentation accuracy. Furthermore, a premature convergence approach drastically increases the segmentation speed by a factor of ≈?17.9.     

Investigation of basic imaging properties in digital radiography. 13. Effect of simple structured noise on the detectability of simulated stenotic lesions

We investigated the effects of structured background noise on the detectability of stenotic lesions. Digital subtraction angiographic (DSA) images of stenotic blood vessels were simulated and superimposed onto uniform noise samples. Eighteen-alternative forced choice (18-AFC) experiments were employed to determine the detectability of the stenotic lesion in the structured-noise background of a blood vessel. In this study, the dependence of detectability on lesion size, vessel size, and incident x-ray exposure was examined. Our results indicate that the presence of structured noise in an image will reduce the detectability of a lesion. However, the relative performance of an observer when the lesion size and incident exposure were varied was the same with and without the presence of the structured background. Thus, conclusions obtained previously with regard to changes in the detectability of a lesion in the presence of uniform background noise can be applied directly to conditions in which simple structured anatomic background is present.     

Primary retroperitoneal acinar cell cystadenoma

In this report, we describe a case of hitherto unreported primary retroperitoneal acinar cell cystadenoma that morphologically and immunophenotypically resembled pancreatic acinar cell cystadenoma. Pancreatic acinar cell cystadenoma is a very uncommon benign lesion characterized by acinar cell differentiation, the evidence of pancreatic exocrine enzyme production, and the absence of cellular atypia. Our case occurred in a 55-year-old woman presenting a 10-cm multilocular cystic lesion in the retroperitoneum thought to be a mucinous cystic neoplasm. At laparotomy, the cystic mass, which showed no connection with any organ, was completely resected with a clinical diagnosis of cystic lymphangioma. The diagnosis of retroperitoneal acinar cell cystadenoma was based on the recognition of morphological acinar differentiation, the immunohistochemical demonstration of the acinar marker trypsin, and the absence of cellular atypia. These peculiar features can be used in the differential diagnosis with all the other cystic lesions of the retroperitoneum.     

PET image reconstruction with anatomical edge guided level set prior

Acquiring both anatomical and functional images during one scan, PET/CT systems improve the ability to detect and localize abnormal uptakes. In addition, CT images provide anatomical boundary information that can be used to regularize positron emission tomography (PET) images. Here we propose a new approach to maximum a posteriori reconstruction of PET images with a level set prior guided by anatomical edges. The image prior models both the smoothness of PET images and the similarity between functional boundaries in PET and anatomical boundaries in CT. Level set functions (LSFs) are used to represent smooth and closed functional boundaries. The proposed method does not assume an exact match between PET and CT boundaries. Instead, it encourages similarity between the two boundaries, while allowing different region definition in PET images to accommodate possible signal and position mismatch between functional and anatomical images. While the functional boundaries are guaranteed to be closed by the LSFs, the proposed method does not require closed anatomical boundaries and can utilize incomplete edges obtained from an automatic edge detection algorithm. We conducted computer simulations to evaluate the performance of the proposed method. Two digital phantoms were constructed based on the Digimouse data and a human CT image, respectively. Anatomical edges were extracted automatically from the CT images. Tumors were simulated in the PET phantoms with different mismatched anatomical boundaries. Compared with existing methods, the new method achieved better bias-variance performance. The proposed method was also applied to real mouse data and achieved higher contrast than other methods.     

Multiple variations of the coeliac axis,hepatic and renal vasculature as incidental findings illustrated by MDCTA

Vascular anatomical variations are not uncommon and may affect any organ’s arterial or venous vasculature. The coexistence of variations in different organic systems is less commonly found, but of great clinical significance in a series of clinical conditions like organ transplantation and surgical preoperative planning. Multidetector computed tomography angiography (MDCTA) has emerged as a valuable alternative to the conventional angiography for accurate evaluation of vascular anatomy and pathology. Radiologists should be familiar with each organ’s vascular variations and always report them to the clinician, even if they represent an incidental finding. This case report presents a 52-year-old female patient undergoing abdominal MDCTA for characterization of a renal lesion. This examination revealed the presence of three hilar arteries on the left kidney, a main renal vein in combination with an additional renal vein in both sides along with a replaced right hepatic artery originating from the superior mesenteric artery. Moreover, both inferior phrenic arteries were found originating from the coeliac axis. 3D volume rendering technique images were used in the evaluation of vascular anatomy as illustrated in this case report.     

Non-interventional background corrections for scintigrams

A method is presented for the interpolation of optimally 'smooth' background correction matrices within arbitrarily shaped boundaries. Practical means of implementing this technique are discussed, along with series expansions for the special cases of square and round boundaries. This class of interpolation methods has the advantages over previous techniques of providing a unique mathematical solution, connecting exactly to count rates on the boundary, and containing no singularities. Clinical scintigraphic images and mathematically generated surfaces are used to test the different cases of the method, and it is shown that confining the boundary to a circle produces the most rapid convergence with the minimum deviation from ideal surfaces. Under common clinical conditions, these techniques lend themselves well to automated, non-interventional computer processing.     

A lesion detectability simulation method for digital x-ray imaging

A simulation method is described in this work that aids in quantifying the upper limits of lesion detectability as a function of lesion size, lesion contrast, pixel size, and x-ray exposure for digital x-ray imaging systems. The method entails random lesion placement with subsequent simulated imaging on idealized x-ray detectors with no additive noise and 100% quantum detective efficiency. Lesions of different size and thickness were simulated. Mean (expectation) lesion signal-to-noise ratios (LSNRs) were calculated and receiver operating characteristic (ROC) curves were constructed based on LSNR ensembles. Mean (expectation) values of the areas under the ROC curves were calculated for lesions of varying size on pixel arrays of varying size at different exposures. Analyses were performed across several parameters, including lesion size, pixel size, and exposure levels representative of various areas of radiography. As expected, lesion detectability increased with lesion size, contrast, pixel size, and exposure. The model suggests that lesion detectability is strongly dependent on the relative alignment (phase) of the lesion with the pixel matrix for lesions on the order of the pixel size.     

A directional distance aided method for medical image segmentation

A challenging problem in image segmentation is preventing boundary leakage through poorly resolved edges because not enough local information can be provided along them. In this article, we propose a new directional distance aided image segmentation method, formulated under the level set framework, to prevent the leakage. At each evolution step, the zero level set is extracted and smoothed. For each point on the zero level set, a new directional distance (DD) term, defined as the vector starting from itself and pointing to its counterpart on the smoothed version of the zero level set, is calculated to measure its "degree of protrusion." The evolution speed of the points that are considered to be protruding out will be penalized. Other terms, e.g., curvature and gradient terms and user specified constraints, are used along with the DD term to influence the level set evolution. Our smoothing technique augments traditional Gaussian smoothing with a new antishrinkage operation. The novelty of our method is that the DD term does not depend on intensity or gradient boundaries to regulate the regional shape and, therefore, help prevent leakage and the method incorporates vertex-based curve/surface smoothing into curve evolution under the level set framework. Experimental results show that the new DDA method achieves promising results and reasonable stability in segmenting simulated objects as well as abdominal aortic aneurysms in computed tomography (CT) angiograms, in both 2D and 3D, by preventing leakage into adjacent structures while preserving local shape details.     

Automatic lung nodule matching on sequential CT images

We propose an automatic segmentation and registration method that provides more efficient and robust matching of lung nodules in sequential chest computed tomography (CT) images. Our method consists of four steps. First, the lungs are extracted from chest CT images by the automatic segmentation method. Second, gross translational mismatch is corrected by optimal cube registration. This initial alignment does not require extracting any anatomical landmarks. Third, the initial alignment is step-by-step refined by hierarchical surface registration. To evaluate the distance measures between lung boundary points, a three-dimensional distance map is generated by narrow-band distance propagation, which drives fast and robust convergence to the optimal value. Finally, correspondences of manually detected nodules are established from the pairs with the smallest Euclidean distances. Experimental results show that our segmentation method accurately extracts lung boundaries and the registration method effectively finds the nodule correspondences.     

基于3D偏差分析的成人桡骨远端解剖对称性研究

目的　通过形态学测量方法评估成人桡骨远端解剖的对称性。 方法　采集15例正常志愿者的双侧前臂薄层CT扫描数据,对桡骨远端1/3的骨性结构进行三维重建,以模型体积和表面积作为目标参数对每一例志愿者左、右侧桡骨的三维模型进行解剖测量;进一步通过3D偏差分析方法完成双侧桡骨模型解剖对称性的定量化和可视化分析。 结果　左、右侧桡骨远端表面积最大差异小于5.6%（P=0.004）,体积差异小于9.1%（P=0.005）;3D偏差分析结果显示,受试者的最大平均负偏差为-0.40 mm,最大平均正偏差为0.34 mm;3D偏差较大的区域主要分布在桡骨远端的非关节面部位。 结论　成人桡骨远端在关节面形态方面具有高度的解剖对称性,临床上对于桡骨远端关节内骨折的外科解剖重建,采用健侧桡骨镜像模型作为参考对象有利于指导桡骨远端骨折的精准复位重建,这对于术后桡腕关节功能的恢复具有重要意义。     

Inferring the impact of linguistic boundaries on population differentiation: application to the Afro-Asiatic-Indo-European case

We present here a quantitative way to assess the impact of language-family boundaries on population differentiation and to evaluate the homogeneity of the genetic processes along these boundaries. Our estimator (delta a) of the impact of the boundary is based on an isolation by distance (IBD) model and measures the added genetic distance between populations located on different sides of the boundary. We compare this statistic with another estimator of group differentiation (F(CT)) computed under an analysis of variance framework that does not assume any particular spatial structure of the populations. Monte Carlo simulations are used to study the behaviour of these statistics under a two-dimensional stepping-stone model. Simulations show that F(CT) can suggest the existence of a frontier when populations only differ because of IBD. This spurious behaviour is much less frequent for the delta a statistic. However, the large variance associated with the delta a statistic, and the fact that it should only be computed in the presence of IBD, may limit the use of this statistic. Overall, the origin and the effect of the boundary is best understood by comparing different statistics and by testing for the presence of IBD on each side of the boundary as well as across the boundary. We illustrate our approach by examining the boundary between Afro-Asiatic and Indo-European populations. These populations are globally genetically differentiated, but the effect of the linguistic boundary on gene flow seems geographically very heterogeneous. This boundary appears to be the result of a secondary contact between two differentiation centres rather than an enhancer of population differentiation.     

Optimal filtering values in renogram deconvolution

The evaluation of the isotopic renogram by means of the renal retention function (RRF) is a technique that supplies valuable information about renal function. It is not unusual to perform a smoothing of the data because of the sensitivity of the deconvolution algorithms with respect to noise. The purpose of this work is to confirm the existence of an optimal smoothing which minimises the error between the calculated RRF and the theoretical value for two filters (linear and non-linear). In order to test the effectiveness of these optimal smoothing values, some parameters of the calculated RRF were considered using this optimal smoothing. The comparison of these parameters with the theoretical ones revealed a better result in the case of the linear filter than in the non-linear case. The study was carried out simulating the input and output curves which would be obtained when using hippuran and DTPA as tracers.     

Ring filter to locate external boundaries in SPECT using scattered radiation

A novel form of filter for SPECT is described, in which, after back projection and summation, the reconstructed signal is a measure of the total activity within a ring of specified radius, centre and width. The filter is applied to the problem of using Compton scattered radiation to locate external boundaries. In the simple case of the determination of the radius of a circular scattering body of known centre, the filter output would identify a transition region and define an appropriate threshold as the boundary was crossed. However it can also be applied to locate the boundaries seen in individual SPECT projections and hence trace out the envelope of the scattering body. Monte Carlo simulation based on 99mTc is used to test the performance of the filter in a range of situations, with encouraging results.     

包含中国人群解剖学差异的Web端三维器官模型可视化系统的构建及应用

目的 数字三维解剖模型对于解剖学教育和临床医疗研究起到了积极的推动作用。现有的中国人数字三维模型多是基于一个标准的人类个体,不包含人与人之间的解剖形态变化差异,不利于使用者了解器官形态在不同人之间的变化。我们提出了1种基于万维网（Web）端的三维可视化人体躯干解剖形变模型,在浏览器网页中展示中国人群的器官解剖形态变化规律。 方法 通过统计形状模型技术,从138例健康中国人计算机断层扫描（CT）影像中学习到器官形态个体差异,并通过Web端浏览器交互展示这种变形差异。 结果 本系统实现了基于网络的操作模式,通过用户交互式操作调整模型参数来展示人体解剖学信息和个体间变化。结论 本研究中的Web端三维可视化解剖形变模型实现了跨平台、跨操作系统,达到了实时操作,为解剖教学与医疗应用提供了个体差异信息。     

Automated anatomical demarcation using an active shape model for videofluoroscopic analysis in swallowing

The current gold standard method in the clinical assessment of swallowing is the visual inspection of videofluoroscopic frames. Specific clinical measurements are estimated based on various anatomical and bolus positional information with respect to time (or frame number). However, due to the subjective nature of visual inspection clinicians face intra- and inter-observer repeatability issues and bias when making these estimations. The correct demarcations of reference lines highlighting the positions of important anatomical landmarks would serve as a visual aid and could also be used in conjunction with bolus detection methods to objectively determine these desirable measurements. In this paper, we introduce and test the reliability of applying a 16-point Active Shape Model as a deformable template to demarcate the boundaries of salient anatomical boundaries with minimal user input. A robust end and corner point detection algorithm is also used to provide image information for the suggested movement of the template during the fitting stage. Results show the model deformation constraints calculated from a training set of images are clinically coherent. The Euclidean distances between the fitted model points against their corresponding target points were measured. Test images were taken from two different data sets from frames acquired using two different videofluoroscopy units. Overall, fitting was found to be more reliable on the vertebrae and inferior points of the larynx compared to the superior laryngeal points and hyoid bone, with the model always fitting the C7 vertebra with discrepancies no higher than a distance of 23 pixels (3.2% of the image width, approximately 7.6 mm).