Anatomical Feature Segmentation of Femur Point Cloud Based on Medical Semantics

Feature segmentation is an essential phase for geometric modeling and shape processing in anatomical study of human skeleton and clinical digital treatment of orthopedics. Due to various degrees of freedom of bone surface, the existing segmentation algorithms can hardly meet specific medical need. To address this, a novel segmentation methodology for anatomical features of femur model based on medical semantics is put forward. First, anatomical reference objects (ARO) are created to represent typical characteristics of femur anatomy by 3D point fitting in combination with medical priori knowledge. Then, local point clouds between adjacent anatomies are selected according to the AROs to extract boundary feature point (BFP)s. Finally, the complete model of femur is divided into anatomical regions by executing the enhanced watershed algorithm guided with BFPs. Experimental results show that the proposed method has the advantages of automatic segmentation of femoral head, neck and other complex areas, and the segmentation results have better medical semantics. In addition, the slight modification of segmentation results can be achieved by adjusting a few threshold parameter values, which improves the convenience of modification for ordinary users.     

An Algorithm to Automate Yeast Segmentation and Tracking

Our understanding of dynamic cellular processes has been greatly enhanced by rapid advances in quantitative fluorescence microscopy. Imaging single cells has emphasized the prevalence of phenomena that can be difficult to infer from population measurements, such as all-or-none cellular decisions, cell-to-cell variability, and oscillations. Examination of these phenomena requires segmenting and tracking individual cells over long periods of time. However, accurate segmentation and tracking of cells is difficult and is often the rate-limiting step in an experimental pipeline. Here, we present an algorithm that accomplishes fully automated segmentation and tracking of budding yeast cells within growing colonies. The algorithm incorporates prior information of yeast-specific traits, such as immobility and growth rate, to segment an image using a set of threshold values rather than one specific optimized threshold. Results from the entire set of thresholds are then used to perform a robust final segmentation.     

Accuracy of cancellous bone volume fraction measured by micro-CT scanning

Volume fraction, the single most important parameter in describing trabecular microstructure, can easily be calculated from three-dimensional reconstructions of micro-CT images. This study sought to quantify the accuracy of this measurement. One hundred and sixty human cancellous bone specimens which covered a large range of volume fraction (9.8-39.8%) were produced. The specimens were micro-CT scanned, and the volume fraction based on Archimedes' principle was determined as a reference. After scanning, all micro-CT data were segmented using individual thresholds determined by the scanner supplied algorithm (method I). A significant deviation of volume fraction from method I was found: both the y-intercept and the slope of the regression line were significantly different from those of the Archimedes-based volume fraction (p < 0.001). New individual thresholds were determined based on a calibration of volume fraction to the Archimedes-based volume fractions (method II). The mean thresholds of the two methods were applied to segment 20 randomly selected specimens. The results showed that volume fraction using the mean threshold of method I was underestimated by 4% (p = 0.001), whereas the mean threshold of method II yielded accurate values. The precision of the measurement was excellent. Our data show that care must be taken when applying thresholds in generating 3-D data, and that a fixed threshold may be used to obtain reliable volume fraction data. This fixed threshold may be determined from the Archimedes-based volume fraction of a subgroup of specimens. The threshold may vary between different materials, and so it should be determined whenever a study series is performed.     

Objective identification of cell cycle phases and subphases by automated image analysis.

Frequency distributions of integrated optical density, perimeter, projection, area, form factor, average optical density, and mean dispersion path of nuclear images of Feulgen-stained HeLa S3 cells were obtained by automated image analysis at the base threshold of 0.04 OD. The mean values and standard deviations of these geometric parameters were then computed versus increasing values of threshold (0.08--0.32 OD). There is clear evidence of differential chromatin dispersion and convolution during the cycle of synchronized HeLa S3 cells at different times after selective mitotic detachment. The combination of average OD, form factor, and mean dispersion path at base threshold with the threshold dependence of nuclear morphometric parameters permits objective identification of cell cycle phases and their subphases, by characterizing variations in chromatin geometry within and between phases, regardless of whether DNA content remains constant (early G1, middle G1, late G1), varies only slightly (late G1-early S or late S-G2 transitions), or varies significantly (early S-middle S).     

Identification of Neonatal White Matter on DTI: Influence of More Inclusive Thresholds for Atlas Segmentation

Purpose

Semi-automated diffusion tensor imaging (DTI) analysis of white matter (WM) microstructure offers a clinically feasible technique to assess neonatal brain development and provide early prognosis, but is limited by variable methods and insufficient evidence regarding optimal parameters. The purpose of this research was to investigate the influence of threshold values on semi-automated, atlas-based brain segmentation in very-low-birth-weight (VLBW) preterm infants at near-term age.

Materials and Methods

DTI scans were analyzed from 45 VLBW preterm neonates at near-term-age with no brain abnormalities evident on MRI. Brain regions were selected with a neonatal brain atlas and threshold values: trace <0.006 mm²/s, fractional anisotropy (FA)>0.15, FA>0.20, and FA>0.25. Relative regional volumes, FA, axial diffusivity (AD), and radial diffusivity (RD) were compared for twelve WM regions.

Results

Near-term brain regions demonstrated differential effects from segmentation with the three FA thresholds. Regional DTI values and volumes selected in the PLIC, CereP, and RLC varied the least with the application of different FA thresholds. Overall, application of higher FA thresholds significantly reduced brain region volume selected, increased variability, and resulted in higher FA and lower RD values. The lower threshold FA>0.15 selected 78±21% of original volumes segmented by the atlas, compared to 38±12% using threshold FA>0.25.

Conclusion

Results indicate substantial and differential effects of atlas-based DTI threshold parameters on regional volume and diffusion scalars. A lower, more inclusive FA threshold than typically applied for adults is suggested for consistent analysis of WM regions in neonates.     

Segmentation of the Clustered Cells with Optimized Boundary Detection in Negative Phase Contrast Images

Cell image segmentation plays a central role in numerous biology studies and clinical applications. As a result, the development of cell image segmentation algorithms with high robustness and accuracy is attracting more and more attention. In this study, an automated cell image segmentation algorithm is developed to get improved cell image segmentation with respect to cell boundary detection and segmentation of the clustered cells for all cells in the field of view in negative phase contrast images. A new method which combines the thresholding method and edge based active contour method was proposed to optimize cell boundary detection. In order to segment clustered cells, the geographic peaks of cell light intensity were utilized to detect numbers and locations of the clustered cells. In this paper, the working principles of the algorithms are described. The influence of parameters in cell boundary detection and the selection of the threshold value on the final segmentation results are investigated. At last, the proposed algorithm is applied to the negative phase contrast images from different experiments. The performance of the proposed method is evaluated. Results show that the proposed method can achieve optimized cell boundary detection and highly accurate segmentation for clustered cells.     

Automated CT bone segmentation using statistical shape modelling and local template matching

Abstract

Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomical correspondences. The method was evaluated on demanding regions: normal and osteoarthritic scapulae, healthy and atrophied mandibles, and orbital bones. On average, results were accurate with surface distances of approximately 0.5?mm and average Dice coefficients >90%. Since anatomical correspondences are propagated during the segmentation process, this approach can directly yield anatomical measurements, provide design parameters for personalized surgical instruments, or determine the bone geometry to manufacture patient-specific implants.     

Objective threshold selection procedure (OTS) for segmentation of scanning laser confocal microscope images

The determination of volumes and interface areas from confocal laser scanning microscopy (CLSM) images requires the identification of component objects by segmentation. An automated method for the determination of segmentation thresholds for CLSM imaging of biofilms was developed. The procedure, named objective threshold selection (OTS), is a three-dimensional development of the approach introduced by the popular robust automatic threshold selection (RATS) method. OTS is based on the statistical properties of local gray-values and gradients in the image. By characterizing the dependence between a volumetric feature and the intensity threshold used for image segmentation, the former can be determined with an arbitrary confidence level, with no need for user intervention. The identification of an objective segmentation procedure renders the possibility for the full automation of volume and interfacial area measurement. Images from two distinct biofilm systems, acquired using different experimental techniques and instrumental setups were segmented by OTS to determine biofilm volume and interfacial area. The reliability of measurements for each case was analyzed to identify optimal procedure for image acquisition. The automated OTS method was shown to reproduce values obtained manually by an experienced operator.     

齿状突几何参数、骨密度与生物力学性质的相关性研究

目的:齿状突骨折是颈椎的严重损伤,其中大部分需要行前路螺钉内固定术治疗,齿状突的几何参数对螺钉的选择起决定性作用,其骨密度则影响螺钉对骨质的把持力,齿状突固有的生物力学性质对齿状突骨折固定效果进而对骨折愈合有较大影响,基于以上考虑,本课题分析并比较了几何参数、骨密度与生物力学性质的相关性,评价其指导临床应用的意义。方法:将15例经福尔马林浸泡的国人枢椎标本剔除周围软组织,分别测量并分析各个标本的几何参数、骨密度以及扭转刚度、剪切刚度、拉伸刚度等生物力学性质的特点,并比较它们之间的相关性。结果:齿状突为一椭球形结构,难以容纳两枚内固定螺钉,齿状突的几何参数、骨密度和生物力学性质之间没有相关性。结论:临床上在对齿状突骨折采用螺钉内固定前需要了解齿状突的解剖结构并据此选取适当尺寸的螺钉,应根据齿状突基底部的横径选择螺钉的直径,根据基底部到前唇的距离选择螺钉光滑段的长度,根据枢椎高度选择螺钉长度,齿状突的几何参数、骨密度和齿状突的生物力学性质之间并无相关性,并不能根据齿状突几何参数、骨密度来预测其生物力学强度进而预测内固定的初始稳定性。     

Portable optical fiber probe-based spectroscopic scanner for rapid cancer diagnosis: a new tool for intraoperative margin assessment

There continues to be a significant clinical need for rapid and reliable intraoperative margin assessment during cancer surgery. Here we describe a portable, quantitative, optical fiber probe-based, spectroscopic tissue scanner designed for intraoperative diagnostic imaging of surgical margins, which we tested in a proof of concept study in human tissue for breast cancer diagnosis. The tissue scanner combines both diffuse reflectance spectroscopy (DRS) and intrinsic fluorescence spectroscopy (IFS), and has hyperspectral imaging capability, acquiring full DRS and IFS spectra for each scanned image pixel. Modeling of the DRS and IFS spectra yields quantitative parameters that reflect the metabolic, biochemical and morphological state of tissue, which are translated into disease diagnosis. The tissue scanner has high spatial resolution (0.25 mm) over a wide field of view (10 cm × 10 cm), and both high spectral resolution (2 nm) and high spectral contrast, readily distinguishing tissues with widely varying optical properties (bone, skeletal muscle, fat and connective tissue). Tissue-simulating phantom experiments confirm that the tissue scanner can quantitatively measure spectral parameters, such as hemoglobin concentration, in a physiologically relevant range with a high degree of accuracy (<5% error). Finally, studies using human breast tissues showed that the tissue scanner can detect small foci of breast cancer in a background of normal breast tissue. This tissue scanner is simpler in design, images a larger field of view at higher resolution and provides a more physically meaningful tissue diagnosis than other spectroscopic imaging systems currently reported in literatures. We believe this spectroscopic tissue scanner can provide real-time, comprehensive diagnostic imaging of surgical margins in excised tissues, overcoming the sampling limitation in current histopathology margin assessment. As such it is a significant step in the development of a platform technology for intraoperative management of cancer, a clinical problem that has been inadequately addressed to date.     

Accurate Construction of Photoactivated Localization Microscopy (PALM) Images for Quantitative Measurements

Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (t_Thresh and d_Thresh) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.     

Critical thresholds in sea lice epidemics: evidence, sensitivity and subcritical estimation

Host density thresholds are a fundamental component of the population dynamics of pathogens, but empirical evidence and estimates are lacking. We studied host density thresholds in the dynamics of ectoparasitic sea lice (Lepeophtheirus salmonis) on salmon farms. Empirical examples include a 1994 epidemic in Atlantic Canada and a 2001 epidemic in Pacific Canada. A mathematical model suggests dynamics of lice are governed by a stable endemic equilibrium until the critical host density threshold drops owing to environmental change, or is exceeded by stocking, causing epidemics that require rapid harvest or treatment. Sensitivity analysis of the critical threshold suggests variation in dependence on biotic parameters and high sensitivity to temperature and salinity. We provide a method for estimating the critical threshold from parasite abundances at subcritical host densities and estimate the critical threshold and transmission coefficient for the two epidemics. Host density thresholds may be a fundamental component of disease dynamics in coastal seas where salmon farming occurs.     

Quantitative comparison of freeware software for bone mesh from DICOM files

Musculo-skeletal modelling, 3D printing of bone models and also custom design of relevant prostheses starts from accurate STL files. These are obtained from medical imaging after careful segmentation and 3D reconstruction using specialized software, but most of these are very expensive. The aim of the present study is to assess and compare alternative software available for free. Three freeware software were selected from the most popular, and one standard platform was made available at the institute of the authors. Using each of these four software and starting from available DICOM files obtained previously by a CT scanner, three different bone models were reconstructed from each of five different human anatomical areas for a total of 60 bone model reconstructions. A young radiographer performed the bone reconstruction without specific technical training. 3D spatial matching of corresponding anatomical models was also performed to determine distance-maps for the assessment of final surface quality. In all four software many valuable features were available, with minimum differences, and bone models of good quality were obtained. Large differences in file sizes (mean range over the five anatomical models 66-338) and in the number of triangles (870-1350 thousands) were found, with triangles for MByte ratio ranging from about 4 to 20 thousands. The distance-map analysis revealed that root mean square deviation averaged over the five anatomical models ranged from 0.13 to 2.21 mm for the six spatial matches between the four software. These software are suitable for 3D bone model reconstruction, and do not require special training, and as such these can open up opportunities for biomechanical modelling and medical education.     

Segmentation of stained blood cell images measured at high scanning density with high magnification and high numerical aperture optics

In hematological morphology, it is necessary to resolve and analyze the smallest possible cellular details appearing in the light microscope. A prerequisite for computer-aided analysis of subtle morphological features is measuring the cells at a high scanning density with high magnification and high numerical aperture optics. Contrary to visual observations, the information content in a measured picture can be increased by setting the condensor's numerical aperture (NA) greater than the objective's NA. The complexity and heterogeneity of such cell images necessitate a new segmentation method that conserves the morphological information required in the subsequent image analysis, feature extraction, and cell classification. In our segmentation strategy, characteristic color difference thresholds for each nucleus and cytoplasm are combined with geometric operations, probability functions, and a cell model. All thresholds are repeatedly recalculated during the successive improvements of the image masks. None of the thresholds are fixed. This strategy segments blood cell images containing touching cells and large variations in staining, texture, size, and shape. Biological inconsistencies in the calculated cell masks are eliminated by comparing each mask with the cell model criteria integrated into the entire segmentation process. All 20,000 leukocyte images from 120 smears in our leukemia project were segmented with this method.     

Examining the developing bone: What do we measure and how do we do it?

The clinical tools available to evaluate bone development in children are often ambiguous, and difficult to interpret. Unfortunately bone densitometry methods (i.e., dual energy X-ray absorptiometry, DXA) which have a relatively straightforward application in adult osteoporosis, are far more difficult to evaluate in the growing skeleton. Even with adequate "adjustment" for bone size or maturity, bone "density" (areal or volumetric) alone often gives an inaccurate assessment of bone strength--especially in children. Ideally, we would like to measure both material and geometric properties of bone to accurately estimate "strength". Mechanically meaningful measures of bone geometry (bone cross-sectional area, cortical thickness) and estimates of bending strength (section modulus, or SSI) are available with non-invasive techniques such as (p)QCT and some DXA software. With new technology it might be possible to also measure bone material properties, which will be especially important in some pediatric disorders. In children, we also need to know something about the loads imposed on a child's bone and consider not only absolute bone strength, but also the strength of bone relative to the physiologic loads. Interpreting bone strength in light of the loads imposed (particularly muscle force) is critical for an accurate diagnosis of the developing bone.     

Computed tomographic measurement of cortical bone geometry

In this study digital images of bone cross-sections obtained by computed tomography were analyzed with an automated outlining method. It was shown that unbiased cross-sectional geometric measurements of cortical bone could be obtained if the periosteal and endosteal surfaces were defined at separate thresholds. Use of different threshold levels for these two surfaces resulted in errors of 2.6% for periosteal diameters, 7.4% for endosteal diameters and 7.3% for cortical area. If incorrect thresholds were used, cortical thickness measurements can have errors as high as 30%. In addition, simulated variation in medullary fat content did not affect measurement of medullary dimensions.     

Comparison of methods for the demarcation between earlywood and latewood in tree rings of Norway spruce

The precise demarcation between earlywood and latewood is important for the detailed analysis of intra-annual tree ring features. Different techniques based on visual assessment, wood anatomy analysis and X-ray densitometry have been developed and are currently used for this purpose. Depending on the chosen method, tree species and environmental conditions, the results can significantly vary. Thus, it is important to determine the technique optimal for a particular research. Here, we investigated Norway spruce (Picea abies) tree rings to examine the agreement among the following demarcation methods: (1) direct visual assessment, (2) Mork’s index (anatomical definition of the transition from earlywood to latewood based on cell wall-lumen ratio) and (3) fixed and floating density thresholds applied to intra-ring density profiles. The aim was to modify both the Mork’s criterion and density thresholds on the basis of reference values given by visual identification of earlywood/latewood transition. A total of 231 tree rings were analysed by all methods. Our results showed that the usage of floating threshold (defined for each ring separately based on density profiles) is more reliable in comparison with fixed threshold (the same threshold value used for all tree rings and samples). Statistical analysis revealed the best correspondence between visual identification of earlywood/latewood transition and demarcation based on the standard Mork’s index and the floating density threshold derived as 80 % of maximum latewood density. In terms of Mork’s index calibration, the results showed that to determine latewood cells in Norway spruce trees growing in temperate conditions, it is sufficient to use an index value equal to 0.83. The results are applicable for the studied spruce population growing in a temperate climate. The methodology itself, however, is universal and can help to calibrate criteria for earlywood-latewood demarcation under specific conditions.     

Assessment of the bilateral asymmetry of human femurs based on physical,densitometric, and structural rigidity characteristics

The purpose of this study was to perform a comprehensive geometric, densitometric, biomechanical, and statistical analysis of paired femurs for an adult population over a wide age range using three imaging modalities to quantify the departure from symmetry in size, bone mineral density, and cross-sectional structural rigidities.Femur measurements were obtained from 20 pairs of cadaveric femurs. Dimensions of these anatomic sites were measured using calipers directly on the bone and plain radiographs. Dual energy X-ray absorptiometry was used to measure bone mineral density. Bone mineral content and axial and bending rigidities were determined from the CT imaging.No differences were observed between the geometric measurements, DXA based bone mineral density and axial and bending rigidities of left and right femurs (P>0.05 for all cases). Left and right proximal femurs are not significantly different based on geometric, densitometric, and structural rigidity measurements. However, absolute left–right differences for individual patients can be substantial. When using the contralateral femur as a control, the number of femur pairs required to assess significant changes in anatomic dimensions and structural properties induced by a tumor, infection, fracture, or implanted device can range from 3 to 165 pairs depending on the desired effect size or sensitivity (5% or 10% difference).This information is important both for femoral arthroplasty implant design and the use of the contralateral femur as an intra-subject control for clinical assessment and research studies. In addition, our statistical analysis provides sample size estimates for planning future orthopedic research studies.     

Image blurring by thermal diffusion in the observation of hydrated biomolecules with soft X-ray microscopy.

A simple model is presented for the estimation of image blurring in X-ray microscopy of biological specimens in a hydrated environment. The model is essentially based on thermal diffusion of an object to be imaged. The degree of image blurring by diffusion depends on the following situations of the object. The object is free from, is tightly fixed to, or is partially connected to the surrounding structures. The proper imaging time required to achieve a given resolution in X-ray microscopy of biological structures was estimated with the present method. The results suggest that imaging time shorter than 3 msec (free) to 1.4 sec (tightly fixed) is required for the observation of a cell (30 microns in diameter) at the resolution of 100 nm. The model is also applicable to a fragmented object caused by imaging X-rays.