A direction‐selective local‐thresholding method,DSLT, in combination with a dye‐based method for automated three‐dimensional segmentation of cells and airspaces in developing leaves

Quantifying the anatomical data acquired from three‐dimensional (3D) images has become increasingly important in recent years. Visualization and image segmentation are essential for acquiring accurate and detailed anatomical data from images; however, plant tissues such as leaves are difficult to image by confocal or multi‐photon laser scanning microscopy because their airspaces generate optical aberrations. To overcome this problem, we established a staining method based on Nile Red in silicone‐oil solution. Our staining method enables color differentiation between lipid bilayer membranes and airspaces, while minimizing any damage to leaf development. By repeated applications of our staining method we performed time‐lapse imaging of a leaf over 5 days. To counteract the drastic decline in signal‐to‐noise ratio at greater tissue depths, we also developed a local thresholding method (direction‐selective local thresholding, DSLT) and an automated iterative segmentation algorithm. The segmentation algorithm uses the DSLT to extract the anatomical structures. Using the proposed methods, we accurately segmented 3D images of intact leaves to single‐cell resolution, and measured the airspace volumes in intact leaves.     

Micro‐CT evaluation of murine fetal skeletal development yields greater morphometric precision over traditional clear‐staining methods

Traditional techniques for quantification of murine fetal skeletal development (gross measurements, clear‐staining) are severely limited by specimen processing, soft tissue presence, diffuse staining, and unclear landmarks between which to make measurements. Nondestructive microcomputed tomography (micro‐CT) imaging is a versatile, well‐documented tool traditionally used to generate high‐resolution 3‐D images and quantify microarchitectural parameters of trabecular bone. Although previously described as a tool for phenotyping fetal murine specimens, micro‐CT has not previously been used to directly measure individual fetal skeletal structures. Imaging murine fetal skeletons using micro‐CT enables the researcher to nondestructively quantify fetal skeletal development parameters including limb length, total bone volume, and average bone mineral density, as well as identify skeletal malformations. Micro‐CT measurement of fetal limb lengths correlates well with traditional clear‐staining methods (83.98% agreement), decreases variability in measurements (average standard errors: 6.28% for micro‐CT and 10.82% for clear‐staining), decreases data acquisition time by eliminating the need for tissue processing, and preserves the intact fixed fetus for further analysis. Use of the rigorous micro‐CT technique to generate 3‐D images for digital measurement enables isolation of skeletal structures based on degree of mineralization (local radiodensity), eliminating the complications of blurred stain boundaries and soft tissue inclusion that accompany clear‐staining and gross measurement techniques. Microcomputed tomography provides a facile, accurate, and nondestructive method for determining the developmental state of the fetal skeleton using not only limb lengths and identification of malformations, but total skeletal bone volume and average skeletal mineral density as well. Birth Defects Res (Part B) 2008. © 2008 Wiley‐Liss, Inc.     

Small-animal imaging using clinical positron emission tomography/computed tomography and super-resolution

Considering the high cost of dedicated small-animal positron emission tomography/computed tomography (PET/CT), an acceptable alternative in many situations might be clinical PET/CT. However, spatial resolution and image quality are of concern. The utility of clinical PET/CT for small-animal research and image quality improvements from super-resolution (spatial subsampling) were investigated. National Electrical Manufacturers Association (NEMA) NU 4 phantom and mouse data were acquired with a clinical PET/CT scanner, as both conventional static and stepped scans. Static scans were reconstructed with and without point spread function (PSF) modeling. Stepped images were postprocessed with iterative deconvolution to produce super-resolution images. Image quality was markedly improved using the super-resolution technique, avoiding certain artifacts produced by PSF modeling. The 2 mm rod of the NU 4 phantom was visualized with high contrast, and the major structures of the mouse were well resolved. Although not a perfect substitute for a state-of-the-art small-animal PET/CT scanner, a clinical PET/CT scanner with super-resolution produces acceptable small-animal image quality for many preclinical research studies.     

Noise properties of reconstructed images in a kilo-voltage on-board imaging system with iterative reconstruction techniques: A phantom study

X-ray computed tomography (CT) images obtained with a kilo-voltage (kV) on-board imaging (OBI) system improve the accuracy of patient setup and treatment planning. The use of iterative reconstruction techniques (IRTs) for CT imaging can also reduce radiation dose compared to analytic reconstruction techniques. Despite these improvements, the image quality varies with IRTs, and the noise structure of reconstructed images can be distorted by IRTs. In this study, the noise properties and spatial resolution of the images reconstructed by IRTs were evaluated in terms of conventional noise metrics, high-order statistics, noise spectral density (NSD) and modulation transfer function (MTF) at different radiation doses. A kV OBI system mounted on a Varian Trilogy machine and a CATPHAN600 phantom were used to obtain projections, and the projections were reconstructed by Feldkamp (FDK), algebraic reconstruction technique (ART), maximum-likelihood expectation–maximization (MLEM) and total variation (TV) minimization algorithms. The reconstructed images were compared according to mean, standard deviation, skewness, kurtosis, NSD and MTF at different radiation doses. The results demonstrated that the noise properties and spatial resolution of reconstructed images depend on the type of IRT and the radiation dose. The noise structures are altered by IRTs and can be characterized by high-order statistics and NSD, as well as conventional noise metrics. In conclusion, high-order statistics and NSD should be considered in order to provide detailed information for the images reconstructed by IRTs. Also, trade-off among noise properties, spatial resolution and contrast is important to optimize image quality obtained using IRTs.     

Segmentation improvement through denoising of PET images with 3D-context modelling in wavelet domain

Positron emission tomography (PET) images have been incorporated into the radiotherapy process as a powerful tool to assist in the contouring of lesions, leading to the emergence of a broad spectrum of automatic segmentation schemes for PET images (PET-AS). However, not all proposed PET-AS algorithms take into consideration the previous steps of image preparation. PET image noise has been shown to be one of the most relevant affecting factors in segmentation tasks. This study demonstrates a nonlinear filtering method based on spatially adaptive wavelet shrinkage using three-dimensional context modelling that considers the correlation of each voxel with its neighbours. Using this noise reduction method, excellent edge conservation properties are obtained. To evaluate the influence in the segmentation schemes of this filter, it was compared with a set of Gaussian filters (the most conventional) and with two previously optimised edge-preserving filters. Five segmentation schemes were used (most commonly implemented in commercial software): fixed thresholding, adaptive thresholding, watershed, adaptive region growing and affinity propagation clustering. Segmentation results were evaluated using the Dice similarity coefficient and classification error. A simple metric was also included to improve the characterisation of the filters used for induced blurring evaluation, based on the measurement of the average edge width. The proposed noise reduction procedure improves the results of segmentation throughout the performed settings and was shown to be more stable in low-contrast and high-noise conditions. Thus, the capacity of the segmentation method is reinforced by the denoising plan used.     

It’s noisy out there! A review of denoising techniques in cryo-electron tomography

Cryo-electron tomography is the only technique that can provide sub-nanometer resolved images of cell regions or even whole cells, without the need of labeling or staining methods. Technological advances over the past decade in electron microscope stability, cameras, stage precision and software have resulted in faster acquisition speeds and considerably improved resolution. In pursuit of even better image resolution, researchers seek to reduce noise – a crucial factor affecting the reliability of the tomogram interpretation and ultimately limiting the achieved resolution. Sub-tomogram averaging is the method of choice for reducing noise in repetitive objects. However, when averaging is not applicable, a trade-off between reducing noise and conserving genuine image details must be achieved. Thus, denoising is an important process that improves the interpretability of the tomogram not only directly but also by facilitating other downstream tasks, such as segmentation and 3D visualization. Here, I review contemporary denoising techniques for cryo-electron tomography by taking into account noise-specific properties of both reconstruction and detector noise. The outcomes of different techniques are compared, in order to help researchers select the most appropriate for each dataset and to achieve better and more reliable interpretation of the tomograms.     

Relationships between bone mass and micro-architecture at the mandible and iliac bone in edentulous subjects: a dual X-ray absorptiometry, computerised tomography and microcomputed tomography study

doi: 10.1111/j.1741‐2358.2011.00527.x Relationships between bone mass and micro‐architecture at the mandible and iliac bone in edentulous subjects: a dual X‐ray absorptiometry, computerised tomography and microcomputed tomography study Objectives: To compare bone volume, bone mineral density, cortical thickness and bone micro‐architecture in a series of paired mandibular and iliac bone samples analysed by various imagery techniques to see whether relationships exist between the various techniques and between mandibular and iliac bone. Materials and methods: Bone samples from the mandible and ilium were harvested in 20 cadavers and analysed by dual energy X‐ray absorptiometry (DXA), computerised tomography (CT) on a conventional hospital machine and microCT. Results: Significant correlations were found between Hounsfield density obtained by CT, and bone mass determined by microCT but not with DXA values. Cortical thickness measurements were well correlated between CT and microCT. No relationships were found between mandibular and iliac bone, when considering mineral density, cortical thickness, bone volume or micro‐architecture. Conclusion: In clinical practice, CT remains the most appropriate routine means for bone qualitative and quantitative evaluation at the mandible. In this ex vivo study, these results confirm that mandibular bone status does not reflect the axial skeletal one and assist in the placement of implants with dental prostheses in old or osteoporotic patients.     

Morphological analysis of pore size and connectivity in a thick mixed‐culture biofilm

Morphological parameters are commonly used to predict transport and metabolic kinetics in biofilms. Yet, quantification of biofilm morphology remains challenging because of imaging technology limitations and lack of robust analytical approaches. We present a novel set of imaging and image analysis techniques to estimate internal porosity, pore size distributions, and pore network connectivity to a depth of 1 mm at a resolution of 10 µm in a biofilm exhibiting both heterotrophic and nitrifying activities. Optical coherence tomography (OCT) scans revealed an extensive pore network with diameters as large as 110 µm directly connected to the biofilm surface and surrounding fluid. Thin‐section fluorescence in situ hybridization microscopy revealed that ammonia‐oxidizing bacteria (AOB) distributed through the entire thickness of the biofilm. AOB were particularly concentrated in the biofilm around internal pores. Areal porosity values estimated from OCT scans were consistently lower than those estimated from multiphoton laser scanning microscopy, though the two imaging modalities showed a statistically significant correlation (r = 0.49, p < 0.0001). Estimates of areal porosity were moderately sensitive to gray‐level threshold selection, though several automated thresholding algorithms yielded similar values to those obtained by manually thresholding performed by a panel of environmental engineering researchers (±25% relative error). These findings advance our ability to quantitatively describe the geometry of biofilm internal pore networks at length scales relevant to engineered biofilm reactors and suggest that internal pore structures provide crucial habitat for nitrifier growth.     

An iterative region-growing process for cell image segmentation based on local color similarity and global shape criteria

An image segmentation process was derived from an image model that assumed that cell images represent objects having characteristic relationships, limited shape properties and definite local color features. These assumptions allowed the design of a region-growing process in which the color features were used to iteratively aggregate image points in alternation with a test of the convexity of the aggregate obtained. The combination of both local and global criteria allowed the self-adaptation of the algorithm to segmentation difficulties and led to a self-assessment of the adequacy of the final segmentation result. The quality of the segmentation was evaluated by visual control of the match between cell images and the corresponding segmentation masks proposed by the algorithm. A comparison between this region-growing process and the conventional gray-level thresholding is illustrated. A field test involving 700 bone marrow cells, randomly selected from May-Grünwald-Giemsa-stained smears, allowed the evaluation of the efficiency, effectiveness and confidence of the algorithm: 96% of the cells were evaluated as correctly segmented by the algorithm's self-assessment of adequacy, with a 98% confidence. The principles of the other major segmentation algorithms are also reviewed.     

Technical note: Terahertz imaging of ancient mummies and bone

Ancient mummified soft‐tissues are a unique source to study the evolution of disease. Diagnostic imaging of such historic tissues is of foremost interest in paleoanthropology or paleopathology, with conventional x‐ray and computed tomography (CT) being the gold‐standard. Longer wavelength radiation in the far‐infrared or Terahertz region allows diagnostic close‐to‐surface tissue differentiation of bone morphology while being harmless to human cells. The aim of this study is to show the feasibility and the morpho‐diagnostic impact of THz imaging of historic remains. Images of an artificially embalmed ancient Egyptian human mummy hand, an artificially embalmed ancient Egyptian mummified fish and a macerated human lumbar vertebra were obtained by THz‐pulse imaging and compared with conventional X‐ray and CT images. Although conventional x‐ray imaging provides higher spatial resolution, we found that THz‐imaging is well‐suited for the investigation of ancient mummified soft tissue and embalming‐related substances / wrappings. In particular, bone and cartilaginous structures can be well differentiated from surrounding soft‐tissues and bandage‐wrappings by THz imaging. Furthermore, THz‐pulse imaging also measures the time‐delay of the pulsed signal when passing through the sample, which provides supplementary information on the optical density of the sample that is not obtained by X‐ray and CT. Terahertz radiation provides a completely non‐invasive diagnostic imaging modality for historic dry specimens. We anticipate this modality also to be used for detection of hidden objects in historic samples such as funerary amulets still in situ in wrapped mummies, as well as potentially for the identification of spectral signatures from chemical substances, e.g., in embalming essences.. Am J Phys Anthropol, 2010. © 2010 Wiley‐Liss, Inc.     

Hominin brain evolution--new century, new directions

The study of hominin brain evolution focuses on the interiors of fossilized braincases. Applications of recent three-dimensional computed tomography (CT) and magnetic resonance imaging (MRI) techniques for visualizing and measuring >virtual endocasts< from braincases in combination with advances in computer graphics and software for acquiring relevant data are transforming the way in which fossil skulls are analyzed, and improving the quality of paleoneurological investigations. Although CT imaging is preferred for fossil skulls, a novel method that combines high-resolution MRI of physical endocasts, electronic reconstruction of their missing parts, and warping of the resulting virtual endocasts is currently being developed and has great potential for future studies of hominin brain evolution. Applications of CT and MR techniques have already resulted in surprising new findings, which are briefly outlined. Exciting revelations about hominin brain evolution are expected as the 21st century unfolds.     

Segmentation algorithms for ear image data towards biomechanical studies

In recent years, the segmentation, i.e. the identification, of ear structures in video-otoscopy, computerised tomography (CT) and magnetic resonance (MR) image data, has gained significant importance in the medical imaging area, particularly those in CT and MR imaging. Segmentation is the fundamental step of any automated technique for supporting the medical diagnosis and, in particular, in biomechanics studies, for building realistic geometric models of ear structures. In this paper, a review of the algorithms used in ear segmentation is presented. The review includes an introduction to the usually biomechanical modelling approaches and also to the common imaging modalities. Afterwards, several segmentation algorithms for ear image data are described, and their specificities and difficulties as well as their advantages and disadvantages are identified and analysed using experimental examples. Finally, the conclusions are presented as well as a discussion about possible trends for future research concerning the ear segmentation.     

X‐ray computed tomography and its potential in ecological research: A review of studies and optimization of specimen preparation

Imaging techniques are a cornerstone of contemporary biology. Over the last decades, advances in microscale imaging techniques have allowed fascinating new insights into cell and tissue morphology and internal anatomy of organisms across kingdoms. However, most studies so far provided snapshots of given reference taxa, describing organs and tissues under “idealized” conditions. Surprisingly, there is an almost complete lack of studies investigating how an organism′s internal morphology changes in response to environmental drivers. Consequently, ecology as a scientific discipline has so far almost neglected the possibilities arising from modern microscale imaging techniques. Here, we provide an overview of recent developments of X‐ray computed tomography as an affordable, simple method of high spatial resolution, allowing insights into three‐dimensional anatomy both in vivo and ex vivo. We review ecological studies using this technique to investigate the three‐dimensional internal structure of organisms. In addition, we provide practical comparisons between different preparation techniques for maximum contrast and tissue differentiation. In particular, we consider the novel modality of phase contrast by self‐interference of the X‐ray wave behind an object (i.e., phase contrast by free space propagation). Using the cricket Acheta domesticus (L.) as model organism, we found that the combination of FAE fixative and iodine staining provided the best results across different tissues. The drying technique also affected contrast and prevented artifacts in specific cases. Overall, we found that for the interests of ecological studies, X‐ray computed tomography is useful when the tissue or structure of interest has sufficient contrast that allows for an automatic or semiautomatic segmentation. In particular, we show that reconstruction schemes which exploit phase contrast can yield enhanced image quality. Combined with suitable specimen preparation and automated analysis, X‐ray CT can therefore become a promising quantitative 3D imaging technique to study organisms′ responses to environmental drivers, in both ecology and evolution.     

Interactive Local Super-Resolution Reconstruction of Whole-Body MRI Mouse Data: A Pilot Study with Applications to Bone and Kidney Metastases

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.     

Thresholding technique for accurate analysis of density and geometry in QCT, pQCT and microCT images

Computed tomography (CT) is widely used in the assessment of bone parameters in live patients and animals as well as bone samples. Quantitative analysis requires the segmentation of the bone from the surrounding tissue, and most segmentation methods rely on some type of thresholding technique. The aim of this communication is to highlight the influence of threshold selection on various bone parameters and recommend appropriate thresholds. Two types of information are of interest in bone analysis from images: geometric parameters and density parameters. We know from imaging theory that blurring is an inherent byproduct of all imaging methods. Depending on the threshold used for segmentation, the object boundary moves in space due to the sloping edge. It is, thus, critical to select the threshold that creates an object boundary that reflects the actual object size. Similarly, due to blurring, the imaged density shows erroneous values at the object boundaries. Such values must not be included for an accurate representation of the object density. Using a pQCT scanner and a bone phantom with known density and geometry, we show that the thresholds for geometry and density are different. The threshold for accurate geometric segmentation was 49% of the difference of the density between the adjacent tissues. The threshold for accurate density assessment was 95% of the maximum density value of the bone. These specific thresholds are valid only for the scanner tested; however, the principle for selecting the thresholds is valid across scanner platforms and scale of imaging.     

3-D image analysis system and megakaryocyte quantitation

A quasi-automatic computer image analysis system has been developed for 3-D reconstruction of stained serial sections and implemented on an IBAS system. Some new automatic image analysis techniques have been designed and incorporated into the system. For image segmentation, a transition region determination based thresholding method is introduced. Neither histogram calculation nor empirical parameters are needed in the automatic threshold selection. A two step 3-D reconstruction procedure--symbolic and pictorial reconstructions--is designed to improve the flexibility and the computational capability of the system. The global level registration and local level registration are separated. The former consists of establishing the relationship among a large numbers of profile pairs dispersed in adjacent sections. A pattern matching method based on pattern recognition principles is devised to exploit the information about the statistical character of mismatch caused by deformation of sections and about the relationship of nearby objects. For the latter, an equivalent elliptical approximation method based on the physical theory of the rotation of rigid bodies is proposed. The system has been used for 3-D reconstruction and quantitation of megakaryocytes in human bone marrow tissue. Features about individual 3-D megakaryocyte cell and the spatial distribution of megakaryocytes are determined. The latter is a new contribution to megakaryocyte quantitation and is not possible by using conventional stereologic techniques. These experimental results have demonstrated the ability of the system to perform quantitative analysis.     

Diagnostic value of micro-CT in comparison with histology in the qualitative assessment of historical human skull bone pathologies

Cases of pathologically changed bone might constitute a diagnostic pitfall and frequently need histological methods to be etiologically properly evaluated. With micro‐computed tomography (μCT), a new epoch of 2D and 3D imaging has been launched. We evaluated the diagnostic investigation of this analytical method versus well established histological investigations of historical human bone. Pathological changes due to various etiologies (infectious, traumatic, endocrinological, neoplasia) observed in autopsy‐based macerated human skulls (Galler Collection, Natural History Museum Basel, Switzerland) were investigated by μCT and compared with histological thin ground sections using polarized light. Micro‐CT images visualize the architecture of the bone with high spatial resolution without preparation or destruction of the sample in the area to be sectioned. Changes in the bone surfaces as well as alterations of the diploë can be assessed. However, morphological patterns caused by reactive response, such as typical arrangements of collagen fibers, can only be visualized by the microscopic investigation of thin ground sections using polarized light. A great advantage of μCT is the high number of slices obtained so that spatial differences within the areas of the specimen become visible. Micro‐CT is a valuable tool for the diagnosis of vestiges of skull bone diseases. Its advantages over histology are the fast, automated image acquisition and the fact that the specimen is not completely destroyed. Only excision of the area to be scanned is necessary, if the specimen is too large to be scanned as a whole. Further, the 3D visualization of the micro‐architecture allows an easy orientation within the sample, for example, for the choice of the location of the histological slices. However, the need to differentiate woven from lamellar bone still makes histology an indispensable method. Am J Phys Anthropol, 2007. © 2007 Wiley‐Liss, Inc.     

A new cortical thickness mapping method with application to an in vivo finite element model

Finite element modelling of musculoskeletal systems, with geometrical structures constructed from computed tomography (CT) scans, is a useful and powerful tool for biomechanical studies. The use of CT scans from living human subjects, however, is still limited. Accurate reconstruction of thin cortical bone structures from CT scans of living human subjects is especially problematic, due to low CT resolution that results from mandatory low radiation doses and/or involuntary movements of the subject. In this study, a new method for mapping cortical thickness is described. Using the method, cortical thickness measurements of a coxal (pelvis) bone obtained from CT scans of a cadaver were mapped to the coxal geometry as obtained through CT scans of a live human subject, resulting in accurate cortical thickness while maintaining geometric fidelity of the live subject. The mapping procedure includes shape-preserving parameterisation, mesh movement and interpolation of thickness using a search algorithm. The methodology is applicable to modelling of other bones where accurate cortical thickness is needed and for which such data exist.     

智能期相联合SSF技术改善冠状动脉CTA图像运动伪影

目的:评价智能期相选择(Smart phase)和自动追踪冻结(Snap-Shot-Freeze, SSF)技术联合应用在前门控冠状动脉CT血管成像(Coronary CT angiography, CCTA)改善图像运动伪影中的价值。方法:94例疑似心血管疾病的患者行CCTA检查。所有患者图像均采用smart phase、SSF及smart phase+SSF两种技术联合进行后处理。将原始图像(A组)、smart phase图像(B组)、SSF图像(C组)和smart phase+SSF图像(D组)导入GE AW4.6工作站。对四组患者冠状动脉三大分支(右冠状动脉、左前降支及左旋支)图像质量进行主观评价(5分法)和测量每组图像主动脉根部及前胸壁肌肉CT值和标准差,并计算图像的噪声(Noise,N)、信噪比(Signal-to-noise ratio,SNR)和对比噪声比(Contrast-to-noise ratio,CNR)和比较。结果:经smart phase处理后,A组冠状动脉三大分支图像评分均得到了明显提高(P<0.05)。经SSF矫正的A组和B组冠状动脉三大分支图像质量评分均得到明显提高(P<0.05)。Smart Phase联合SSF技术得到的图像评分在所有组中评分最高,与其他组均存在显著差异(P<0.05)。结论:Smart phase联合SSF技术可明显改善前门控CCTA图像运动伪影,值得临床推广应用。     

CT image segmentation using FEM with optimized boundary condition

The authors propose a CT image segmentation method using structural analysis that is useful for objects with structural dynamic characteristics. Motivation of our research is from the area of genetic activity. In order to reveal the roles of genes, it is necessary to create mutant mice and measure differences among them by scanning their skeletons with an X-ray CT scanner. The CT image needs to be manually segmented into pieces of the bones. It is a very time consuming to manually segment many mutant mouse models in order to reveal the roles of genes. It is desirable to make this segmentation procedure automatic. Although numerous papers in the past have proposed segmentation techniques, no general segmentation method for skeletons of living creatures has been established. Against this background, the authors propose a segmentation method based on the concept of destruction analogy. To realize this concept, structural analysis is performed using the finite element method (FEM), as structurally weak areas can be expected to break under conditions of stress. The contribution of the method is its novelty, as no studies have so far used structural analysis for image segmentation. The method's implementation involves three steps. First, finite elements are created directly from the pixels of a CT image, and then candidates are also selected in areas where segmentation is thought to be appropriate. The second step involves destruction analogy to find a single candidate with high strain chosen as the segmentation target. The boundary conditions for FEM are also set automatically. Then, destruction analogy is implemented by replacing pixels with high strain as background ones, and this process is iterated until object is decomposed into two parts. Here, CT image segmentation is demonstrated using various types of CT imagery.