Slice Spacing Research Articles

Ultrafast energy-dispersive soft-x-ray diffraction in the water window with a laser-driven source

Time-resolved soft-x-ray-diffraction experiments give access to microscopic processes in a broad range of solid-state materials by probing ultrafast dynamics of ordering phenomena. While laboratory-based high-harmonic generation (HHG) light sources provide the required photon energies, their limited photon flux is distributed over a wide spectral range, rendering typical monochromatic diffraction schemes challenging. Here, we present a scheme for energy-dispersive soft-x-ray diffraction with femtosecond temporal resolution and photon energies across the water window from 200 to 600 eV. The experiment utilizes the broadband nature of the HHG emission to efficiently probe large slices in reciprocal space. As a proof-of-concept, we study the laser-induced structural dynamics of a Mo/Si superlattice in an ultrafast, non-resonant soft-x-ray diffraction experiment. We extract the underlying strain dynamics from the measured shift of its first order superlattice Bragg peak in reciprocal space at photon energies around 500 eV via soft-x-ray scattering simulations.

Celestial Dual for Maximal Helicity Violating Amplitudes.

It is shown that a 2D conformal field theory consisting of a central charge c Liouville theory, a chiral level one, rank N Kac-Moody algebra, and a weight -3/2 free fermion holographically generate 4D maximal helicity violating tree-level scattering amplitudes. The correlators of this 2D conformal field theory give directly the 4D leaf amplitudes associated to a single hyperbolic slice of flat space. The 4D celestial amplitudes arise in a large-N and semiclassical large-c limit, according to the holographic dictionary, as a translationally invariant combination of leaf amplitudes. A step in the demonstration is showing that the semiclassical limit of Liouville correlators are given by contact 3D anti-de Sitter Witten diagrams.

Machine learning the breakdown of tame effective theories

Effective field theories endowed with a nontrivial moduli space may be broken down by several, distinct effects as the energy scales that are probed increase. These may include the appearance of a finite number of new states, or the emergence of an infinite tower of states, as predicted by the Distance Conjecture. Consequently, the moduli space can be partitioned according to which kind of state first breaks down the effective description, and the effective-theory cutoff has to be regarded as a function of the moduli that may abruptly vary in form across the components of the partition. In this work we characterize such a slicing of the moduli space, induced by the diverse breakdown mechanisms, in a two-fold way. Firstly, employing the recently formulated Tameness Conjecture, we show that the partition of the moduli space so constructed is composed only of a finite number of distinct components. Secondly, we illustrate how this partition can be concretely constructed by means of supervised machine learning techniques, with minimal bottom-up information.

Multiphoton simultaneous multislice imaging.

To develop multiphoton excitation techniques for simultaneous multislice (SMS) imaging and evaluate their performance and specific absorption rate (SAR) benefit. To improve multiphoton SMS reconstruction quality with a novel CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) design. When a conventional single-slice RF field is applied together with an oscillating gradient field, the two can combine to generate multiphoton excitation at multiple discrete spatial locations. Because the conventional RF is reused at multiple spatial locations, multiphoton excitation offers reduced SAR for SMS applications. CAIPIRINHA shifts are often used to improve parallel-imaging acceleration. Interestingly, CAIPIRINHA-type shifts can be obtained for multiphoton SMS by updating the oscillating gradient phase at every phase encode. In this work, both a gradient-echo and a spin-echo sequence with multiphoton CAIPIRINHA-SMS excitation pulses are implemented for in vivo human imaging at 3 T. For three slices, multiphoton SMS provides a 51% reduction in SAR compared with conventional superposition SMS, whereas for five slices, SAR is reduced by 66%. Multiphoton SMS outperforms PINS (power independent of number of slices) and MultiPINS in terms of SAR reduction especially when the pulse duration is short, slices are thin, and/or the slice spacing is large. A custom CAIPIRINHA phase-encoding design for multiphoton SMS significantly improves reconstruction quality. Multiphoton SMS excitation can be obtained by combining conventional single-slice RF pulses with an oscillating gradient and offers significant SAR benefits compared with conventional superposition SMS. A novel CAIPIRINHA design allows higher multiband factors for multiphoton SMS imaging.

Total Ankle Replacement with Built-in Antibiotic Spacer: A Paradigm Shift in the Management of Infected Ankles

Introduction/Purpose: Infection of an ankle fracture is a devastating complication that can lead to chronic pain, limited motion or amputation. Traditional treatment strategies after infection involve aggressive surgical debridement, implant removal and prolonged antibiotic therapy. Non-anatomic cement spacers for the tibiotalar joint have previously been described with mixed results. Articulating spacers have shown improved outcomes and may be used as definitive treatment. Currently, there are no prefabricated TAR spacers on the market. The use of 3D printing to create custom implants is emerging, however, there is a paucity of literature regarding their use. We present a case of post-infectious ankle arthritis in 14 year old patient treated with a 3D printed total ankle replacement with built in antibiotic spacer (TAR-AS). Methods: A CT scan was performed in accordance with computer aided design (CAD) parameters. Bilateral lower extremities were scanned to allow the unaffected side to be mirrored and be the basis for implant design. Slice spacing less than 1.25mm with pixel size of 0.5mm. The studies were in DICOM files and within a timeframe where no significant change in patient anatomy had occurred. The implants were fabricated by selective laser melting (SLM) of cobalt chrome alloy (CoCrMo) by Restor3d (Durham, NC). Our design incorporated a stacked gyroid component to facilitate antibiotic cement impregnation. In terms of surgical technique, the custom TAR-AS followed a similar approach to a patient specific TAR procedure. Prior to implantation, the gyroid component of the TAR-AS was filled with Simplex bone cement with tobramycin (Stryker). Results: At six months postoperatively, our patient reported no limitation in activities. AOFAS scores improved from 46/100 preoperatively to 83/100 at six months postoperatively. Radiographic parameters showed no signs of implant failure, loosening or change in alignment. Intraoperative cultures remained negative. Conclusion: We present a case demonstrating the utilization of 3D generated prostheses for treatment of post-infection ankle arthritis. The TAR-AS represents a significant advancement in the management of ankle infections. This innovative approach combines the benefits of joint replacement and continued antibiotic elution. With further research and continued technological advancements, the TAR-AS has the potential to become the gold standard for the treatment of infected TAR. Despite the promising results, challenges remain in the implementation of TAR-AS. Long term follow up studies are needed to evaluate the durability and longevity of the implant. Total ankle with built in antibiotic spacer Superior view of tibial tray with antibiotic cement packed in gyroid

Spatial attention-based implicit neural representation for arbitrary reduction of MRI slice spacing

Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resolution. Super-resolution technique can enhance the through-plane resolution of MR images to facilitate downstream visualization and computer-aided diagnosis. However, most existing works train the super-resolution network at a fixed scaling factor, which is not friendly to clinical scenes of varying inter-slice spacing in MR scanning. Inspired by the recent progress in implicit neural representation, we propose a Spatial Attention-based Implicit Neural Representation (SA-INR) network for arbitrary reduction of MR inter-slice spacing. The SA-INR aims to represent an MR image as a continuous implicit function of 3D coordinates. In this way, the SA-INR can reconstruct the MR image with arbitrary inter-slice spacing by continuously sampling the coordinates in 3D space. In particular, a local-aware spatial attention operation is introduced to model nearby voxels and their affinity more accurately in a larger receptive field. Meanwhile, to improve the computational efficiency, a gradient-guided gating mask is proposed for applying the local-aware spatial attention to selected areas only. We evaluate our method on the public HCP-1200 dataset and the clinical knee MR dataset to demonstrate its superiority over other existing methods.

More than one way to skin a dose volume: the impact of dose-surface map calculation approach on study reproducibility

Objective. Dose-surface maps (DSMs) provide spatial representations of the radiation dose to organ surfaces during radiotherapy and are a valuable tool for identifying dose deposition patterns that are predictive of radiation toxicities. Over the years, many different DSM calculation approaches have been introduced and used in dose-outcome studies. However, little consideration has been given to how these calculation approaches may be impacting the reproducibility of studies in the field. Therefore, we conducted an investigation to determine the level of equivalence of DSMs calculated with different approaches and their subsequent impact on study results. Approach. Rectum and bladder DSMs were calculated for 20 prostate radiotherapy patients using combinations of the most common slice orientation and spacing styles in the literature. Equivalence of differently calculated DSMs was evaluated using pixel-wise comparisons and DSM features (rectum only). Finally, mock cohort comparison studies were conducted with DSMs calculated using each approach to determine the level of dosimetric study reproducibility between calculation approaches. Main results. We found that rectum DSMs calculated using the planar and non-coplanar orientation styles were non-equivalent in the posterior rectal region and that equivalence of DSMs calculated with different slice spacing styles was conditional on the choice of inter-slice distance used. DSM features were highly sensitive to choice of slice orientation style and DSM sampling resolution. Finally, while general result trends were consistent between the comparison studies performed using different DSMs, statisitically significant subregions and features could vary greatly in position and magnitude. Significance. We have determined that DSMs calculated with different calculation approaches are frequently non-equivalent and can lead to differing conclusions between studies performed using the same dataset. We recommend that the DSM research community work to establish consensus calculation approaches to ensure reproducibility within the field.

Robust semi-automatic segmentation method: an expert assistant tool for muscles in CT and MR data

ABSTRACT Image muscle segmentation is useful to quantitatively assess musculoskeletal diseases by extracting biomarkers such as shape, texture and water diffusivity metrics. Although volumetric manual segmentation is time consuming and a bottleneck in practice, fully automatic approaches are still in progress to reach an acceptable accuracy. In this paper, we provide a robust semi-automated tool to segment two musculoskeletal systems, i.e. thigh and shoulder in MRI and CT modalities, respectively. The tool only needs a few manually labelled cross-sections to build a directed graph-structure of corresponding points between the successive spaced slices. The boundaries of each muscle are obtained by performing a spline interpolation based on the directed graph-structure. Each muscle label and its corresponding 3D mesh are deduced using post-processing techniques. We evaluated the tool on 26 MRI thighs and 16 CT shoulders. Three metrics along with inter-muscle overlapping were employed to evaluate the tool by comparison to an expert manual segmentation and a publicly available tools (ITK-SNAP, 3D Slicer). The results showed a mean Dice 0.988 ± 0.003 , and Hausdorff Distance 4.86 ± 1.67 mm in comparison to the manual reference for thigh muscle segmentation, and a mean Dice 0.961 ± 0.005 and Hausdorff Distance 2.42 ± 0.79 mm for shoulder muscle segmentation, outperformed the other methods. The tool is proposed as slicer module available at https://github.com/latimagine/SlicerSpline.

A Practical Method for Slice Spacing Measurement Using the American Association of Physicists in Medicine Computed Tomography Performance Phantom.

The slice spacing has a crucial role in the accuracy of computed tomography (CT) images in sagittal and coronal planes. However, there is no practical method for measuring the accuracy of the slice spacing. This study proposes a novel method to automatically measure the slice spacing using the American Association of Physicists in Medicine (AAPM) CT performance phantom. The AAPM CT performance phantom module 610-04 was used to measure slice spacing. The process of slice spacing measurement involves a pair of axial images of the module containing ramp aluminum objects located at adjacent slice positions. The middle aluminum plate of each image was automatically segmented. Next, the two segmented images were combined to produce one image with two stair objects. The centroid coordinates of two stair objects were automatically determined. Subsequently, the distance between these two centroids was measured to directly indicate the slice spacing. For comparison, the slice spacing was calculated by accessing the slice position attributes from the DICOM header of both images. The proposed method was tested on phantom images with variations in slice spacing and field of view (FOV). The results showed that the automatic measurement of slice spacing was quite accurate for all variations of slice spacing and FOV, with average differences of 9.0% and 9.3%, respectively. A new automated method for measuring the slice spacing using the AAPM CT phantom was successfully demonstrated and tested for variations of slice spacing and FOV. Slice spacing measurement may be considered an additional parameter to be checked in addition to other established parameters.

Celestial holography and AdS3/CFT2 from a scaling reduction of twistor space

Celestial amplitudes obtained from Mellin transforming 4d momentum space scattering amplitudes contain distributional delta functions, hindering the application of conventional CFT techniques. In this paper, we propose to bypass this problem by recognizing Mellin transforms as integral transforms projectivizing certain components of the angular momentum. It turns out that the Mellin transformed wavefunctions in the conformal primary basis can be regarded as representatives of certain cohomology classes on the minitwistor space of the hyperbolic slices of 4d Minkowski space. Geometrically, this amounts to treating 4d Minkowski space as the embedding space of AdS3. By considering scattering of such on-shell wavefunctions on the projective spinor bundle ℙ\U0001d54a of Euclidean AdS3, we bypass the difficulty of the distributional properties of celestial correlators using the traditional AdS3/CFT2 dictionary and find conventional 2d CFT correlators for the scaling reduced Yang-Mills theory living on the hyperbolic slices. In the meantime, however, one is required to consider action functionals on the auxiliary space ℙ\U0001d54a, which introduces additional difficulties. Here we provide a framework to work on the projective spinor bundle of hyperbolic slices, obtained from a careful scaling reduction of the twistor space of 4d Minkowski spacetime.

Research on the measurement method of crankshaft coaxiality error based on three-dimensional point cloud

Aiming at the demand of rapid detection for coaxiality of crankshaft journal, a method of visual measurement of coaxiality error based on 3D point cloud is proposed. In this research, a laser scanner is utilized to obtain a 3D point cloud model of the part to be measured, and a circular method of rotary cutting is put forward to obtain equally spaced optimal slices of the journal. The center of the slice is then obtained using the Pratt circle fitting method optimized in this paper. After that, the center of the slice is used to obtain the common reference axis using the least squares method, which finally realizes the measurement of the coaxiality error. The experimental results show that the proposed method of getting the slices is more accurate, the maximum absolute error of the circle fitting method compared with the results of the coordinate measuring machine (CMM) is no more than 4.2 μm, and the maximum absolute error of the coaxiality detection results and the results of the CMM is 5.5 μm, which can satisfy the practical needs of fast and efficient measurement of the coaxiality error of crankshafts.

Entanglement Negativity in de Sitter Biverse from Stringy Axionic Bell Pair: An Analysis Using Bunch‐Davies Vacuum

AbstractIn this work, signatures of quantum entanglement by computing entanglement negativity between two causally unrelated regions in 3 + 1 dimensional global de Sitter space are studied. A bipartite quantum field theoretic setup for this purpose, driven by an axionic Bell pair resulting from Type IIB string compactification on a Calabi‐Yau three fold is investigated. A spherical surface that divides the spatial slice of the global de Sitter space into exterior and interior causally unrelated sub regions is taken into account. For the computational purpose, the simplest possible initial choice of quantum vacuum, which is Bunch‐Davies state is used. The quantitative quantum information theoretic measure for entanglement negativity turns out be consistent with the results obtained for entanglement entropy, even it is better than that from quantum information theoretic point of view. The problem in a hyperbolic open chart where one of the causally unrelated observers remains constrained and the scale dependence enters to the corresponding quantum information theoretic entanglement measure for axionic Bell pair is designed. From the analysis it is found that in the large scales, initially maximally entangled Bunch‐Davies state turns out to be strongly entangled or weakly entangled depending on the axionic decay constant and the supersymmetry breaking scale. It is also found that at the small scales the initial entanglement can be perfectly recovered. The possibility of having a biverse picture, which is a mini version of the multiverse in the present theoretical set up is discussed. Last but not the least, the necessary criteria for generating non vanishing quantum entanglement measures within the framework of quantum field theory of global de Sitter space as well as well as in primordial cosmology due to the axion derived from string theory are provided.

Constructions of perfect bases for classes of 3-tensors

A well studied problem in algebraic complexity theory is the determination of the complexity of problems relying on evaluations of bilinear maps. One measure of the complexity of a bilinear map (or 3-tensor) is the optimal number of non-scalar multiplications required to evaluate it. This quantity is also described as its tensor rank, which is the smallest number of rank-1 matrices whose span contains its first slice space. In this paper we derive upper bounds on the tensor ranks of certain classes of 3-tensors and give explicit constructions of sets of rank-1 matrices containing their first slice spaces. We also show how these results can be applied in coding theory to derive upper bounds on the tensor rank of some rank-metric codes. In particular, we compute the tensor rank of some families of Fqm-linear codes and we show that they are extremal with respect to Kruskal's tensor rank bound.

Gravity from holomorphic discs and celestial Lw1+∞\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Lw_{1+\\infty }$$\\end{document} symmetries

The study of physical theories in various signatures has been important for uncovering structures not easily visible or definable in Lorentz signature. In split signature, global twistor constructions for conformally self-dual (SD) gravity and Yang–Mills construct solutions from twistor data that can be expressed in terms of free data without gauge freedom. This is developed for asymptotically flat SD gravity to give a fully nonlinear encoding of the asymptotic gravitational data in terms of a real homogeneous generating function h on the real twistor space. The recently discovered Lw1+∞\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Lw_{1+\\infty }$$\\end{document} celestial symmetries, when real, act locally as passive Poisson diffeomorphisms on the real twistor space. The twistor data, h, generates an imaginary such Poisson transformation that then generates the gravitational field by shifting the real slice of the twistor space. The twistor chiral sigma models, whose correlators yield the Einstein gravity tree-level S-matrix, are reformulated as theories of holomorphic discs in twistor space whose boundaries lie on the deformed real slice determined by h. The real Lw1+∞\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Lw_{1+\\infty }$$\\end{document} symmetries act on the corresponding formula for the S-matrix geometrically with vanishing Noether currents, but imaginary generators yield graviton vertex operators that generate gravitons in the perturbative expansion. A generating function for the all plus 1-loop amplitude, the analogous framework for Yang–Mills, possible interpretations in Lorentz signature and similar open string formulations of twistor and ambitwistor strings in 4d in split signature, are briefly discussed.

A half de Sitter holography

A long-standing and intriguing question is: does the holographic principle apply to cosmologies like de Sitter spacetime? In this work, we consider a half dS spacetime wherein a timelike boundary encloses the bulk spacetime, presenting a version of de Sitter holography. By analyzing the holographic entanglement entropy in this space and comparing it with that in AdS/CFT, we argue that gravity on a half dSd+1 is dual to a highly non-local field theory residing on dSd boundary. This non-locality induces a breach in the subadditivity of holographic entanglement entropy. Remarkably, this observation can be linked to another argument that time slices in global de Sitter space overestimate the degrees of freedom by redundantly counting the same Hilbert space multiple times.

Femurs segmentation by machine learning from CT scans combined with autonomous finite elements in orthopedic and endocrinology applications

Efficient, accurate and reliable segmentation of femurs from CT-scans is of major importance for patient-specific autonomous finite element analysis (AFE) to determine bone's stiffness and strength. We present a fully automated segmentation algorithm for whole and partial femurs with or without tumors, and clinical applications of the AFE [1] in clinical practice.The segmentation is based on an U-Net convolutional neural network, resulting a 3D mask representing the desired femur in a CT scan. It is robust, independent of the scanning parameters such as slice spacing, pixel size, scanner manufacturer or the femoral length available in the scan. The U-Net was trained on 178 manually segmented femurs (23,721 images) and tested on 43. The performance evaluation resulted in a Dice similarity score (DSC) of 0.9924, intersection over union (IoU) of 0.9849, Hausdorff distance of 4.3315 mm and symmetric average surface distance (ASD) of 0.1326 mm. The algorithm is competitive with the best state-of-the-art femoral segmentation methodologies available.Based on the segmentation an automatic p-FE mesh is generated and physiological boundary conditions representing sidewise falls or stance are being applied automatically to improve the performance of the AFE described in [1]. New examples of the usage of the AFE in endocrinology and orthopedic oncology demonstrate this disruptive technology in actual clinical practice. We present the use of AFE for predicting hip fracture risk in the elderly population due to a sidewise fall and the identification of patients who require a prophylactic surgery due to metastatic tumors in their femurs.

Automated Small Tumor Segmentation by a Template-Based Global Hierarchical Attention Method.

Accurate segmentation of tumors is significant for radiation therapy treatment planning and clinical decision-making. While deep convolutional neural network-based methods have found valuable applications in automatic medical segmentation, tumor segmentation, especially small tumor segmentation, remains challenging due to deficiencies of current deep learning in convolutional and pooling operations, which often results in the loss of small object information. This research proposes a global hierarchical attention-based method for accurate and automated segmentation of small tumors by exploiting the associations between small tumors and the feature maps of large tumors. This study included 131 patients with liver cancer. The in-plane resolution of the patients' CTs is from 0.55 mm to 1.0 mm and slice spacing from 0.45 mm to 6.0 mm. We randomly selected 100 CT scans as the training set and others as the testing set. Each CT slice of the testing set was separated into groups according to tumor size as follows: 0.1-2.0, 2.1-5.0, 5.1-10.0, and 10.1-20.0 cm. The CT slice without tumor or tumor size > 20 cm were excluded. This work presents a tumor template-based hierarchical attention method to quantify the relation between small and large tumors by computing their feature maps. The relation of small-large tumors can compensate for the information loss of small tumors during the convolutional and pooling operations and improve the performance of small tumor segmentation. Among 20,693 CT slices of the 31 testing patients, 3.0% CT slices with tumors ≤2 cm, 6.7% ≤5 cm, 10.6% ≤10 cm, and 13.4%≤20 cm. We compared our method with six widely used segmentation models. The results show our model outperforms other methods on all sizes of liver tumors, especially for small size tumors: For the 0.1-2.0 cm liver tumor, it achieved 8.4%, 10.0%, 11.3%, 9.1%, 10.9%, and 9.6% improvement compared to Unet, PAN, DeepLabV3, FPN, LinkNet, and PSPNet, respectively. We found that the small-large tumors relation can significantly improve small tumor segmentation, which is valuable for treatment planning, and clinical decision-making. Our experimental results show that our method can significantly improve the accuracy of segmenting small liver tumors compared to existing deep-learning-based models. The method is quite general and can be extended to other types of tumor detection and segmentation. We discovered that the relationship between small and large tumors can significantly enhance the segmentation of small tumors, which has significant value for treatment planning and clinical decision-making. Our experiments demonstrate that our approach significantly improves the accuracy of small liver tumor segmentation compared to existing deep learning-based models. Our method is quite versatile and can be extended to other types of tumor detection and segmentation.

ON THE GEOMETRY OF SPACELIKE MEAN CURVATURE FLOW SOLITONS IMMERSED IN A GRW SPACETIME

Abstract We investigate geometric aspects of complete spacelike mean curvature flow solitons of codimension one in a generalized Robertson–Walker (GRW) spacetime $-I\times _{f}M^n$ , with base $I\subset \mathbb R$ , Riemannian fiber $M^n$ and warping function $f\in C^\infty (I)$ . For this, we apply suitable maximum principles to guarantee that such a mean curvature flow soliton is a slice of the ambient space and to obtain nonexistence results concerning these solitons. In particular, we deal with entire graphs constructed over the Riemannian fiber $M^n$ , which are spacelike mean curvature flow solitons, and we also explore the geometry of a conformal vector field to establish topological and further rigidity results for compact (without boundary) mean curvature flow solitons in a GRW spacetime. Moreover, we study the stability of spacelike mean curvature flow solitons with respect to an appropriate stability operator. Standard examples of spacelike mean curvature flow solitons in GRW spacetimes are exhibited, and applications related to these examples are given.

Calibration phantom-based prediction of CT lung nodule volume measurement performance.

A calibration phantom-based method has been developed for predicting small lung nodule volume measurement bias and precision that is specific to a particular computed tomography (CT) scanner and acquisition protocol. The approach involves CT scanning a simple reference object with a specific acquisition protocol, analyzing the scan to estimate the fundamental imaging properties of the CT acquisition system, generating numerous simulated images of a target geometry using the fundamental imaging properties, measuring the simulated images with a standard nodule volume segmentation algorithm, and calculating bias and precision performance statistics from the resulting volume measurements. We evaluated the ability of this approach to predict volume measurement bias and precision of Teflon spheres (diameters =4.76, 6.36, and 7.94 mm) placed within an anthropomorphic chest phantom when using 3M Scotch Magic™ tape as the reference object. CT scanning of the spheres was performed with 0.625, 1.25, and 2.5 mm slice thickness and spacing. The study demonstrated good agreement between predicted volumetric performance and observed volume measurement performance for both volumetric measurement bias and precision. The predicted and observed volume mean for all slice thicknesses was found to be 28% and 13% lower on average than the manufactured sphere volume, respectively. When restricted to 0.625 and 1.25 mm slice thickness scans, which are recommended for small lung nodule volume measurement, we found that the difference between predicted and observed volume coefficient of variation was less than 1.0 %. The approach also showed a resilience to varying CT image acquisition protocols, a critical capability when deploying in a real-world clinical setting. This is the first report of a calibration phantom-based method's ability to predict both small lung nodule volume measurement bias and precision. Volume measurement bias and precision for small lung nodules can be predicted using simple low-cost reference objects to estimate fundamental CT image characteristics and modeling and simulation techniques. The approach demonstrates an improved method for predicting task specific, clinically relevant measurement performance using advanced and fully automated image analysis techniques and low-cost reference objects.

Effects of bubble cutting dynamic behaviors on microalgal growth in bubble column photobioreactor with a novel aeration device.

Introduction: Carbon sequestration by microalgae is an effective approach for achieving carbon neutrality owing to its high carbon capture efficiency and environmental friendliness. To improve microalgae CO2 fixation efficiency, various methods to enhance CO2 transfer at the gas-liquid interface have resulted in high energy consumption. Methods: In this study, a novel aeration device with bubble cutting slices was installed in a photobioreactor for CO2 supply, which could precisely separate bubbles into sizes on the way to rising after departure, achieving CO2 transfer enhancement without extra energy consumption. Subsequently, the bubble cutting dynamic behaviors in the photobioreactor were studied, and the effects of thickness, hydrophilicity, and arrangement of cutting slices on microalgal growth were analyzed. Results: It was found that bubble cutting caused the maximum dry weight and biomass productivity of microalgae to improve by 6.99% and 33.33%, respectively, compared with those of the bioreactor without cutting units, owing to a 27.97% and 46.88% decrease in bubble size and rising velocity, respectively, and an 84.55% prolongation of bubble residence time. Discussion: Parallel cut slices with a thickness and spacing of less than 3mm successfully cut the bubbles. The hydrophobic slice surface prevented daughter bubble departure and prolonged the bubble residence time, impeding microalgae growth owing to bubble coalescence with subsequent bubbles. The optimal cutting slice parameters and culture conditions for microalgal growth were 1mm slice thickness, less than 1mm slice spacing, 5% inlet CO2 concentration, and 70mL/min gas flow rate.