Accurate Shape Research Articles

Design and navigation method of a soft robot for single-port transvesical radical prostatectomy.

Currently, the rigid instruments used for laparoscopic radical resection of prostate cancer not only have the risk of damage to tissues, blood vessels, and nerves, but their limited freedom will also cause surgical blind areas. Soft robots are expected to solve these issues due to inherent flexibility, compliance, and safe interaction with tissues and organs. In addition, to achieve high surgical accuracy and provide precise guidance for surgeons, the navigation method should be studied for the soft robot. A soft robot system for single-port transvesical radical prostatectomy (STRP) is developed, and a navigation method combining fiber Bragg gratings and electromagnetic tracking is proposed for the soft robot. To validate the soft robot design and the effectiveness of the navigation method, different groups of experiments are conducted. The proposed navigation method can achieve accurate location and shape sensing of the soft manipulator. The experiments show that the maximum tip sensing error is 2.691mm, which is 5.38 of the robot length for static configurations, and that the average tip sensing error is 1.966 mm, which corresponds to 3.93 of the robot length for dynamic scenarios. Additionally, phantom tests demonstrate that the designed soft robot can enter the prostate through navigation guidance in a master-slave control mode and cover the entire prostate space. The designed soft robot system, due to its soft structure, good flexibility, and accurate navigation, is expected to improve surgical safety and precision, thereby exhibiting significant potential for STRP.

Detection and metrology of micro-nano particles through the integration of image and laser modes

Micro-nano particles are an indispensable component in various industrial and scientific applications. Accurate granular information is critical for manufacturing products involving these particles. This study presents a novel detection method that merges image and laser modes to achieve precise size and shape determination of micro-nano particles. The proposed method integrates adaptive image analysis with laser particle size fitting to ensure accurate feature detection. Experimental results using ternary precursor samples demonstrate that the fusion mode outperforms both the laser and image modes in terms of size and shape accuracy. The errors of D10, D50, and D90 of the fusion mode are 4.89%, 1.88%, and 2.94%, respectively, which are significantly lower than those obtained using the laser or image mode alone. Additionally, the fusion mode retains the particle shape information from the image mode. The fusion model offers a promising approach for dual-mode detection of micro-nano particles, demonstrating enhanced robustness compared to single-mode methods. Furthermore, the study introduces an image processing method based on a BP neural network classification model that accurately classifies and detects agglomerated and non-agglomerated particles. The classification accuracy reaches 94.98%, and the particle size information remains within the acceptable range.

Surface structure evolution and measurement analysis of Ti6Al4V titanium alloy by electric arc electrochemical machining

In this study, a theoretical model about the conversion mechanism of material removal by electric arc electrochemical machining (EAECM) was derived. The limiting conversion rate of ECM-EAECM was measured on this basis. The current waveform, surface integrity, shape accuracy and process indexes during machining were measured and evaluated. The results showed that when the limiting conversion rate of ECM was exceeded, the material removal consisted of alternating effects of electric arc machining (EAM) and ECM. The proportion of EAM increased and the surface structure evolved into discharge defects, verifying the correctness of the theory. In addition, parametric crossover experiments were performed to clarify the degree of parametric response to EAECM modulation. Finally, the optimal combination of parameters resulted in a material removal rate of up to 5452 mm3/min, a relative electrode wear rate of 1.39 %, and a surface roughness of only 4.62 μm.

Evaluation of Deviations for Horizontal Thin Walls Determined by Optical and Contact Methods for Milled Samples of Nickel Alloy Inconel 625

The aerospace industry is imposing increasingly strict dimensional tolerances, which is forcing continuous development in component manufacturing. Ensuring tight dimensional tolerances is difficult for thin-walled structures due to their reduced stiffness, which are increasingly used in the aerospace industry, where titanium alloys and nickel alloys, among others, dominate. Developments in this area are causing a search for machining conditions that provide sufficient quality characteristics including dimensional and shape accuracy. We discuss, herewith, thin wall deformations in the horizontal orientation of Inconel 625 nickel alloy samples in cross-sections perpendicular and parallel to the direction of tool feed motion. We measured dimensional and shape accuracy using a 3D optical scanner and also using a coordinate measuring machine to correlate these results. We compared the results obtained by the two methods and obtained the maximum discrepancy of the results equal to around 8%. Samples made with adaptive cylindrical milling had similar values of thin wall deviations, with the smallest deviations observed for the sample made with the tool for high-performance machining using adaptive cylindrical milling.

AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning.

In cardiac cine imaging, acquiring high-quality data is challenging and time-consuming due to the artifacts generated by the heart's continuous movement. Volumetric, fully isotropic data acquisition with high temporal resolution is, to date, intractable due to MR physics constraints. To assess whole-heart movement under minimal acquisition time, we propose a deep learning model that reconstructs the volumetric shape of multiple cardiac chambers from a limited number of input slices while simultaneously optimizing the slice acquisition orientation for this task. We mimic the current clinical protocols for cardiac imaging and compare the shape reconstruction quality of standard clinical views and optimized views. In our experiments, we show that the jointly trained model achieves accurate high-resolution multi-chamber shape reconstruction with errors of <13 mm HD95 and Dice scores of >80%, indicating its effectiveness in both simulated cardiac cine MRI and clinical cardiac MRI with a wide range of pathological shape variations.

Analysis and Basics of Improving the Process of Cutting Electrical Sheet Bundles with a High-Pressure Abrasive Water Jet.

Electrical steels are widely used in the electrical industry in the construction of many devices, e.g., power transformer cores and distribution transformers. An important parameter of electrical components that determines the efficiency of devices is energy loss during remagnetization. These losses are influenced, among other factors, by steel cutting processes. The common techniques for cutting electrical materials on industrial lines are mechanical cutting and laser cutting. High-pressure abrasive water jet (AWJ) cutting, unlike the technologies mentioned above, can ensure higher quality of the cut edge and limit the negative impact of the cutting process on the magnetic properties of sheet metal. However, the correct control of the process and the conditions of its implementation comprise a complex issue and require extensive scientific research. This work presents a new approach to cutting electric sheets, involving bundle cutting, which significantly increases the processing efficiency and the dimensional and shape accuracy of the cut details. The tests were carried out for bundles composed of a maximum of 30 sheets, ready to be joined in a stator and rotor in a motor. The influence of processing conditions on the quality of the cut edges of sheet metal, the width of the deformation zone, and the burr height were analyzed. The detailed analysis of the quality of the cut edges of electrical bundled sheets creates new possibilities for controlling the AWJ cutting process in order to obtain a product with the desired functional and operational properties.

Microstructural Approach Application for Morphological Change Determinations of Grapes during Drying

Grape dehydration is practiced widely in the food industry with large yields of sultanas produced globally. This paper proposes an investigation into the microstructure changes of grapes as they are dried by imaging specimens at intervals during dehydration at two temperatures using scanning electron microscopy. Two main methods were developed to obtain the complex boundaries of cells present in grape tissue in over 36 SEM images. Segmentation of the binary image using an adapted watershed function obtained the most consistent and accurate morphological shape. This was compared to a secondary method which used Canny’s edge detection function, morphological closing and skeletonizing to outline the cellular microstructure. MATLAB was utilised to convert these boundaries into measurable areas so that quantitative data on average cell area, perimeter and cell axis lengths were acquired. It was found that over the drying time, the cell area and perimeter were reduced as expected. Some variability in the data was clear due to only single samples being analysed for each temperature and time combination. Trends in cell perimeter, diameter and shape will be used to demonstrate relationships between morphological structure, drying temperature, and duration. Detailed images of the microstructure were obtained, and a unique image processing algorithm was developed to quantitatively analyse the properties of this microstructure. The development of automatic image processing techniques and algorithms will enable quantitative data to be extracted from any image and extend to any plant/food material.

EPSSNet

Fast and accurate segmentation is important for robot judgement, e.g. robot detection, segmentation, and control. Most researchers have focused on deploying lightweight semantic segmentation models into robot services. The problem is that the critical interaction between semantic segmentation and boundaries is ignored. In this chapter, the authors propose a lightweight parallel execution model (EPSSNet) based on semantic flow branch (SFB), edge flow branch (EFB) and self-adapting weighting fusion (SAWF) for mobile robot service projects. The semantic flow branching module is used to obtain accurate object shape features. The boundary constraint module uses multiple convolution and upsampling to distinguish boundary features from semantic features. In order to adaptively fuse boundary features with semantic segmentation features, the SAWF is proposed. It adaptively fuses semantic and boundary features by learning boundary and semantic feature fusion weights. Detailed experimental results on Cityscapes, Pascal VOC 2012 and ADE20k datasets demonstrate the superior performance of our approach.

Enhance watershed algorithms using principal component analysis capabilities

Traditional image segmentation algorithms have many drawbacks, such as over-segmentation and image distortion due to reflected light. The Watershed algorithm is one of the most popular image segmentation algorithms. Over-segmentation errors caused by overlapping targets in the image, as well as noise and glare, must be removed. In this article, we apply image processing using the watershed algorithm and propose to improve the algorithm based on principal component analysis. PCA is a popular technique for analyzing large datasets with many advantages per observation. PCA improves data interpretability while maximizing information content, enabling visualization of multidimensional data by finding image component gradients in a new space called the principle component that is unaffected by noise and reflected light. In contrast, the components mainly containing noise will eliminate with negligible information. This paper introduces three primary steps. The process involves applying the watershed algorithm to the image in the first phase, using the proposed approach (applying the watershed algorithm and suggesting an improvement based on principal component analysis) to the image in the second step, and comparing the outcomes of the two previous processes. Test results show that the suggested technique can achieve accurate and durable target shapes.

Research on improving the structural stability of surimi 3D printing through laser cooking techniques

At present, research on 3D printing technology for meat protein food is still in its early stages, and improving the molding stability and accuracy of products has always been a key challenge. Here, we take surimi protein as an example and achieve its localized thermal gelation quickly and precisely by incorporating laser sintering technology. And based on the thermal denaturation and solidification of proteins during the printing process, the structural instability problem of meat protein food 3D printing is solved. In this study, we used a CO2 laser with a power of 50 W to locally heat cure surimi during the printing process. The results show that under the conditions of 1 mm laser spot diameter, 500 mm/s scanning speed and 0.25 mm scanning interval, the shape accuracy and gel strength of surimi products with 1.5 mm layer thickness are significantly improved, and this combination parameter shows the best effect in the experiment. This study provides a theoretical basis and reference for real-time solidification in meat protein food printing.

Technical refinements of the scapular tip-free flap for mandibular reconstruction.

The use of scapular tip chimeric free flaps (STFFs) for reconstructing mandibular defects has recently become popular, but its utility relative to other bone-containing free flaps remains debatable. The aim of the report is to describe how technical modification of STFF impacted in its use for mandibular reconstruction also commenting results obtained in a unicentric series of patients. Patients undergoing mandibular reconstruction using an STFF from January 1, 2014 to June 1, 2022 were retrospectively enrolled in this report. We collected data on chimeric flap type, bone management, vascular pedicles, and the final outcomes. In total, 31 patients (13 men and 18 women) with a mean age of 68 years were enrolled. According to the classification system of Urken, 15 patients had body defects, while 7 had ramus defects, another 7 had symphysis defects, and 2 had both ramus and bodily defects. STFF was always harvested working in two equips simultaneously, in supine position. Dissection included preparation of chimeric components of the flap as latissimus dorsi, serratus and scapular tip. After pedicle dissection scapular bone was cut basing on reconstructive needing with a rectangular (stick) shape including the border of the scapula. In cases of longer bone harvesting, circumflex pedicle was also included to perfuse the upper portion of the scapular border. In five cases, the STFF was harvested with only the scapular angle component, and was thus a composite osteomuscular flap; for the remaining 26 cases, a chimeric STFF was used. Circumflex pedicle was included for eight patients. Six of the seven patients with symphyseal defects underwent a single osteotomy. The average length of the harvested was 69.92 mm (maximum length = 104 mm). The average height of transplanted bone was 26.78 mm (maximum height = 44.2 mm). Mouth-opening was normal in 25 patients, limited in 6 patients, and severely impaired in no patients. The cosmetic results were rated as excellent by 20 patients, good by 8 patients, and poor by 3 patients. The STFF is an excellent option for mandibular reconstruction when other flaps are not available and for patients in poor general condition. Technical innovations here presented made possible to harvest long bone segments with accurate shape thanks to osteotomies if needed and with adequate soft tissues components of the chimeric flap, ensuring satisfactory functional and cosmetic results.

Analytical Design of Gaussian Anisotropic 2D FIR Filters and Their Implementation Using the Block Filtering Approach

This work proposes an analytical design procedure for a particular class of 2D filters, namely anisotropic Gaussian FIR filters. The design is achieved in the frequency domain and starts from a low-pass Gaussian 1D prototype with imposed specifications, whose frequency response is efficiently approximated by a factored trigonometric polynomial using the Chebyshev series. Then, using specific 1D to 2D frequency mappings applied to the prototype, the frequency response for a 2D anisotropic filter with a specified orientation angle is directly derived in two versions, namely with a straight or elliptical shape in the frequency plane. The resulting filters have an accurate shape with low distortion. Several design examples for specified parameters (angle and selectivity) are provided. Then, simulations of directional filtering on various test images are given, which show their capability of extracting oriented lines or other various oriented objects from synthetic or real-life images. Finally, a computationally efficient implementation at the system level is proposed, based on a polyphase decomposition and block-filtering approach, which yields a 2D filter with a high degree of parallelism and low arithmetic complexity.

ShapeBoost: Boosting Human Shape Estimation with Part-Based Parameterization and Clothing-Preserving Augmentation

Accurate human shape recovery from a monocular RGB image is a challenging task because humans come in different shapes and sizes and wear different clothes. In this paper, we propose ShapeBoost, a new human shape recovery framework that achieves pixel-level alignment even for rare body shapes and high accuracy for people wearing different types of clothes. Unlike previous approaches that rely on the use of PCA-based shape coefficients, we adopt a new human shape parameterization that decomposes the human shape into bone lengths and the mean width of each part slice. This part-based parameterization technique achieves a balance between flexibility and validity using a semi-analytical shape reconstruction algorithm. Based on this new parameterization, a clothing-preserving data augmentation module is proposed to generate realistic images with diverse body shapes and accurate annotations. Experimental results show that our method outperforms other state-of-the-art methods in diverse body shape situations as well as in varied clothing situations.

MICRO-EDD OF INCONEL 800 USING ELECTROMAGNETIC FIELD

Micro-electro-discharge drilling ([Formula: see text]EDD) is a type of non-traditional machining process used for drilling micro-holes of desired dimensions with a high aspect ratio. But, there are no such research works that could have explained the desired accurate circular shape of micro-holes. The need for a more advanced hybrid machining process to improve the overall efficiency in terms of mainly desired circular shape and radial overcut is evolved. In this research work, an electromagnetic field force-assisted micro-EDM process has been carried out on Inconel 800 with a copper tool of 450[Formula: see text][Formula: see text]m. Experimental results showed that measured metal removal rate and tool wear rate decreased for ascending values of magnetic flux density, peak current and gap voltage, whereas circularity increases linearly with an increase in magnetic flux density and also the effects of magnetic field on circularity of micro-holes on Inconel 800 are more predominant than other parameters.

Preserving shape details of pulse signals for video-based blood pressure estimation.

In recent years, imaging photoplethysmograph (iPPG) pulse signals have been widely used in the research of non-contact blood pressure (BP) estimation, in which BP estimation based on pulse features is the main research direction. Pulse features are directly related to the shape of pulse signals while iPPG pulse signals are easily disturbed during the extraction process. To mitigate the impact of pulse feature distortion on BP estimation, it is necessary to eliminate interference while retaining valuable shape details in the iPPG pulse signal. Contact photoplethysmograph (cPPG) pulse signals measured at rest can be considered as the undisturbed reference signal. Transforming the iPPG pulse signal to the corresponding cPPG pulse signal is a method to ensure the effectiveness of shape details. However, achieving the required shape accuracy through direct transformation from iPPG to the corresponding cPPG pulse signals is challenging. We propose a method to mitigate this challenge by replacing the reference signal with an average cardiac cycle (ACC) signal, which can approximately represent the shape information of all cardiac cycles in a short time. A neural network using multi-scale convolution and self-attention mechanisms is developed for this transformation. Our method demonstrates a significant improvement in the maximal information coefficient (MIC) between pulse features and BP values, indicating a stronger correlation. Moreover, pulse signals transformed by our method exhibit enhanced performance in BP estimation using different model types. Experiments are conducted on a real-world database with 491 subjects in the hospital, averaging 60 years of age.

The Development of the Stress-Free Polishing System Based on the Positioning Error Analysis for the Deterministic Polishing of Jet Electrochemical Machining.

Deterministic polishing based on jet electrochemical machining (Jet-ECM) is a stress-free machining method for low-rigidity and ultra-precision workpieces. The nozzle is equivalent to a special tool in deterministic polishing, and the workpiece material is removed using the mechanism of electrochemical dissolution at the position where the nozzle passes. By precisely regulating the nozzle's movement speed and dwell time, the quantity of material removed from the workpiece at a designated position can be finely adjusted. With this mechanism, the improvement of the workpiece shape accuracy can be achieved by planning the nozzle trajectory and nozzle movement speed. However, due to the positioning errors of the polishing device, the actual position of the nozzle may deviate from the theoretical position, resulting in errors in material removal amount, which affects the accuracy and stability of the polishing process. This study established a mathematical model to analyze the influence of nozzle positioning errors in deterministic polishing based on Jet-ECM. This model has been used to design a specific deterministic polishing device based on Jet-ECM. With the proposed deterministic polishing device, the surface shape of the workpiece is converged. The surface peak-to-valley (PV) value of the φ 50 mm workpiece (valid dimensions = 90% of the central region) indicated that the shape error of the surface was reduced from 2.67 μm to 1.24 μm in 34 min. The power spectral density (PSD) method was used to evaluate the height distribution and height characteristics of the workpiece surface. The results show that the low frequency spatial error is reduced significantly after processing. This study improves the accuracy of the stress-free deterministic polishing methods and further expands the use of deterministic polishing in industry.

ScribbleCDNet: Change detection on high-resolution remote sensing imagery with scribble interaction

Change detection on high-resolution remote sensing imagery using end-to-end deep learning methods has attracted considerable attention in recent years. Nevertheless, the performance of end-to-end models on complicated scenarios still is limited. Interactive deep-learning models have proven to be a valuable technique for enhancing model performance with minimal human interaction. For instance, the clicks-based interactive models have attracted much attention recently, however, their performance on large regions or complex areas still can be further improved, because they cannot provide accurate semantics or shape prior information of the change regions for the interactive models, as we know that the shape and semantic features of changed regions in remote sensing imagery are typically irregular and complex. Scribble-based interactive form, which can accurately represent the shape or semantic features of the changed regions, thus it is quite suitable for change detection tasks in remote sensing imagery. Therefore, we proposed a novel interactive deep learning model called ScribbleCDNet in this manuscript, which pioneered the use of scribble as an interactive form for detecting change in bi-temporal high-resolution remote sensing imageries. Compared with the widely used clicks-based interactive deep learning models, the proposed ScribbleCDNet acquired superior results on four open-sourced change detection datasets. Last but not least, we also developed an interactive change detection tool with a user-friendly graphical interface, and it can aid researchers in conducting change detection or generating training samples conveniently. Moreover, the proposed ScribbleCDNet can also inspire researchers to develop other interactive deep-learning models related to semantic segmentation, landcover classification, or object extraction in high-resolution remote sensing imageries.

Periodicity and lifetime of orbits around elongated asteroids

This paper presents dynamics and control of orbits around an asteroid that is modelled as a uniformly rotating homogeneous rectangular parallelepiped (HRP). Aside from the non-uniform gravitational field of the asteroid, we include the solar radiation pressure (SRP) as a perturbing force. A simple model based on the polyhedral method is employed for calculating the gravity around the HRP. First, circular periodic orbits are identified both in the presence and absence of solar radiation pressure. Then, families of general non-circular periodic orbits in the presence of SRP are determined and subsequently analysed for stability. Next, for a general orbit in the equatorial plane, its stability against a catastrophic impact of an orbiting spacecraft onto the asteroid’s surface is checked in the presence of SRP. Orbits, where the solar radiation pressure is less/more dominant over the central body’s gravity, are identified with the aim of finding the best orbits for parking a spacecraft. Then, for long-period orbits, SRP is averaged and the time averaged evolution of the orbital elements is obtained. For a special set of initial condition, a closed form solution for the evolution of the orbital eccentricity is obtained. Using this solution, a lower limit for the life-time of a spacecraft that is left uncontrolled is derived in a closed form. Finally, active control strategies are developed for orbit-keeping ofspacecraft for any choice of orbital parameters. A linear-quadratic regulator (LQR) is designed to track a given Keplerian orbit with minimum fuel expenditure. Fuel expenditure on various orbits are calculated and compared to determine the orbits of cheapest operation. The work presented is applicable to small body (asteroids and comets) exploration missions which require online cancellation of the perturbing forces with minimal knowledge of the accurate shape, size, and composition of the small body prior to the mission.

Patient-specific, deliverable, and self-expandable surgical guide development and evaluation using 4D printing for laparoscopic partial nephrectomy

Accurate lesion diagnosis through computed tomography (CT) and advances in laparoscopic or robotic surgeries have increased partial nephrectomy survival rates. However, accurately marking the kidney resection area through the laparoscope is a prevalent challenge. Therefore, we fabricated and evaluated a 4D-printed kidney surgical guide (4DP-KSG) for laparoscopic partial nephrectomies based on CT images. The kidney phantom and 4DP-KSG were designed based on CT images from a renal cell carcinoma patient. 4DP-KSG were fabricated using shape-memory polymers. 4DP-KSG was compressed to a 10 mm thickness and restored to simulate laparoscopic port passage. The Bland–Altman evaluation assessed 4DP-KSG shape and marking accuracies before compression and after restoration with three operators. The kidney phantom’s shape accuracy was 0.436 ± 0.333 mm, and the 4DP-KSG’s shape accuracy was 0.818 ± 0.564 mm before compression and 0.389 ± 0.243 mm after restoration, with no significant differences. The 4DP-KSG marking accuracy was 0.952 ± 0.682 mm before compression and 0.793 ± 0.677 mm after restoration, with no statistical differences between operators (p = 0.899 and 0.992). In conclusion, our 4DP-KSG can be used for laparoscopic partial nephrectomies, providing precise and quantitative kidney tumor marking between operators before compression and after restoration.

Calibration-free structured-light-based 3D scanning system in laparoscope for robotic surgery.

Accurate 3D shape measurement is crucial for surgical support and alignment in robotic surgery systems. Stereo cameras in laparoscopes offer a potential solution; however, their accuracy in stereo image matching diminishes when the target image has few textures. Although stereo matching with deep learning has gained significant attention, supervised learning requires a large dataset of images with depth annotations, which are scarce for laparoscopes. Thus, there is a strong demand to explore alternative methods for depth reconstruction or annotation for laparoscopes. Active stereo techniques are a promising approach for achieving 3D reconstruction without textures. In this study, a 3D shape reconstruction method is proposed using an ultra-small patterned projector attached to a laparoscopic arm to address these issues. The pattern projector emits a structured light with a grid-like pattern that features node-wise modulation for positional encoding. To scan the target object, multiple images are taken while the projector is in motion, and the relative poses of the projector and a camera are auto-calibrated using a differential rendering technique. In the experiment, the proposed method is evaluated by performing 3D reconstruction using images obtained from a surgical robot and comparing the results with a ground-truth shape obtained from X-rayCT.