3D Model Research Articles

Photo-Cross-linked Gelatin Methacryloyl Hydrogels Enable the Growth of Primary Human Endometrial Stromal Cells and Epithelial Gland Organoids.

In vitro three-dimensional (3D) models are better able to replicate the complexity of real organs and tissues than 2D monolayer models. The human endometrium, the inner lining of the uterus, undergoes complex changes during the menstrual cycle and pregnancy. These changes occur in response to steroid hormone fluctuations and elicit crosstalk between the epithelial and stromal cell compartments, and dysregulations are associated with a variety of pregnancy disorders. Despite the importance of the endometrium in embryo implantation and pregnancy establishment, there is a lack of in vitro models that recapitulate tissue structure and function and as such a growing demand for extracellular matrix hydrogels that can support 3D cell culture. To be physiologically relevant, an in vitro model requires mechanical and biochemical cues that mimic those of the ECM found in the native tissue. We report a semisynthetic gelatin methacryloyl (GelMA) hydrogel that combines the bioactive properties of natural hydrogels with the tunability and reproducibility of synthetic materials. We then describe a simple protocol whereby cells can quickly be encapsulated in GelMA hydrogels. We investigate the suitability of GelMA hydrogel to support the development of an endometrial model by culturing the main endometrial cell types: stromal cells and epithelial cells. We also demonstrate how the mechanical and biochemical properties of GelMA hydrogels can be tailored to support the growth and maintenance of epithelial gland organoids that emerge upon 3D culturing of primary endometrial epithelial progenitor cells in a defined chemical medium. We furthermore demonstrate the ability of GelMA hydrogels to support the viability of stromal cells and their function measured by monitoring decidualization in response to steroid hormones. This study describes the first steps toward the development of a hydrogel matrix-based model that recapitulates the structure and function of the native endometrium and could support applications in understanding reproductive failure.

Development of a 3D printed perfusable in vitro blood-brain barrier model for use as a scalable screening tool.

Despite recent technological advances in drug discovery, the success rate for neurotherapeutics remains alarmingly low compared to treatments for other areas of the body. One of the biggest challenges for delivering therapeutics to the central nervous system (CNS) is the presence of the blood-brain barrier (BBB). In vitro blood-brain barrier models with high predictability are essential to aid in designing parameters for new therapeutics, assess their ability to cross the BBB, and investigate therapeutic strategies that can be employed to enhance transport. Here, we demonstrate the development of a 3D printable hydrogel blood-brain barrier model that mimics the cellular composition and structure of the blood-brain barrier with human brain endothelial cells lining the surface, pericytes in direct contact with the endothelial cells on the abluminal side of the endothelium, and astrocytes in the surrounding printed bulk matrix. We introduce a simple, static printed hemi-cylinder model to determine design parameters such as media selection, co-culture ratios, and cell incorporation timing in a resource-conservative and high-throughput manner. Presence of cellular adhesion junction, VE-Cadherin, efflux transporters, P-glycoprotein (P-gp) and Breast cancer resistance protein (BCRP), and receptor-mediated transporters, Transferrin receptor (TfR) and low-density lipoprotein receptor-related protein 1 (LRP1) were confirmed via immunostaining demonstrating the ability of this model for screening in therapeutic strategies that rely on these transport systems. Design parameters determined in the hemi-cylinder model were translated to a more complex, perfusable vessel model to demonstrate its utility for determining barrier function and assessing permeability to model therapeutic compounds. This 3D-printed blood-brain barrier model represents one of the first uses of projection stereolithography to fabricate a perfusable blood-brain barrier model, enabling the patterning of complex vessel geometries and precise arrangement of cell populations. This model demonstrates potential as a new platform to investigate the delivery of neurotherapeutic compounds and drug delivery strategies through the blood-brain barrier, providing a useful in vitro screening tool in central nervous system drug discovery and development.

Near-Infrared Emissive Super Penetrating Conjugated Polymer Dots for Intratumoral Imaging in 3D Tumor Spheroid Models.

This study describes the formation of single-chain polymer dots (Pdots) via ultrasonic emulsification of nonionic donor-acceptor-donor type (D-A-D) alkoxy thiophene-benzobisthiadiazole-based conjugated polymers (Poly BT) with amphiphilic cetyltrimethylammonium bromide (CTAB). The methodology yields Pdots with a high cationic surface charge (+56.5mV ± 9.5) and average hydrodynamic radius of 12nm. Optical characterization reveals that these Pdots emit near-infrared (NIR) light at a maximum wavelength of 860nm owing to their conjugated polymer backbone consisting of D-A-D monomers. Both colloidal and optical properties of these Pdots make them promising fluorescence emissive probes for bioimaging applications. The significant advantage of positively charged Pdots is demonstrated in diffusion-limited mediums such as tissues, utilizing human epithelial breast adenocarcinoma, ATCC HTB-22 (MCF-7), human bone marrow neuroblastoma, ATCC CRL-2266 (SH-SY5Y), and rat adrenal gland pheochromocytoma, CRL-1721 (PC-12)tumor spheroid models. Fluorescence microscopy analysis of tumor spheroids from MCF-7, SH-SY5Y, and PC-12 cell lines reveals the intensity profile of Pdots, confirming extensive penetration into the central regions of the models. Moreover, a comparison with mitochondria staining dye reveals an overlap between the regions stained by Pdots and the dye in all three tumor spheroid models. These results suggest that single-chain D-A-D type Pdots, cationized via CTAB, exhibit long-range mean free path of penetration (≈1µm) in dense mediums and tumors.

Digital Documentation and Architectural Heritage Restoration with 3-D Geometry: The Ambulatory of the Cathedral of Santiago de Compostela

ABSTRACT The SFM photogrammetry (Structure from Motion) is a technique developed in the field of computer vision that allows obtaining 3D models from images taken from different angles. Despite its extensive development, this technique faces methodological challenges when applied to complex heritage environments. Typically, heritage restoration documentation focuses on the initial and final stages when works have not yet begun or have already concluded, and the object of study is free of obstacles and workers, with its use in intermediate stages being uncommon. The aim of this article is to present geometric documentation using SFM-MVS photogrammetry across multiple stages of the roof restoration of the Cathedral of Santiago de Compostela (Spain), showcasing an expert application of this technique in a real working scenario with multiple challenges, adapting to complex scenes without interfering with project timelines and providing high-quality outcomes at a low cost, even in areas temporarily obscured by scaffolding or plastic coverings. It provides essential data for geometric assistance in restoration design, adaptation, and stakeout. Moreover, continuous 3D documentation enables the creation of 3D stop-motion models, offering an innovative perspective for understanding and communicating a wide range of restoration and construction projects.

Sampling globally and locally correct RNA 3D structures using Ernwin, SPQR and experimental SAXS data.

The determination of the three-dimensional structure of large RNA macromolecules in solution is a challenging task that often requires the use of several experimental and computational techniques. Small-angle X-ray scattering can provide insight into some geometrical properties of the probed molecule, but this data must be properly interpreted in order to generate a three-dimensional model. Here, we propose a multiscale pipeline which introduces SAXS data into modelling the global shape of RNA in solution, which can be hierarchically refined until reaching atomistic precision in explicit solvent. The low-resolution helix model (Ernwin) deals with the exploration of the huge conformational space making use of the SAXS data, while a nucleotide-level model (SPQR) removes clashes and disentangles the proposed structures, leading the structure to an all-atom representation in explicit water. We apply the procedure on four different known pdb structures up to 159 nucleotides with promising results. Additionally, we predict an all-atom structure for the Plasmodium falceparum signal recognition particle ALU RNA based on SAXS data deposited in the SASBDB, which has an alternate conformation and better fit to the SAXS data than the previously published structure based on the same data but other modelling methods.

Fabrication of heterocellular spheroids with controllable core-shell structure using inertial focusing effect for scaffold-free 3D cell culture models.

Three-dimensional (3D) cell culture models capable of emulating the biological functions of natural tissues are pivotal in tissue engineering and regenerative medicine. Despite progress, the fabrication of in vitro heterocellular models that mimic the intricate structures of natural tissues remains a significant challenge. In this study, we introduce a novel, scaffold-free approach leveraging the inertial focusing effect in rotating hanging droplets for the reliable production of heterocellular spheroids with controllable core-shell structures. Our method offers precise control over the core-shell spheroid's size and geometry by adjusting the cell suspension density and droplet morphology. We successfully applied this technique to create hair follicle organoids, integrating dermal papilla cells within the core and epidermal cells in the shell, thereby achieving markedly enhanced hair inducibility compared to mixed-structure models. Furthermore, we have developed melanoma tumor spheroids that accurately mimic the dynamic interactions between tumor and stromal cells, showing increased invasion capabilities and altered expressions of cellular adhesion molecules and proteolytic enzymes. These findings underscore the critical role of cellular spatial organization in replicating tissue functionality in vitro. Our method represents a significant advancement towards generating heterocellular spheroids with well-defined architectures, offering broad implications for biological research and applications in tissue engineering.

Microfluidic system for generating a three-dimensional (3D) vascularized islet-on-a-chip model

Diabetes is a disease associated with the insufficiency of pancreatic endocrine part, consisting mainly of pancreatic islets. Currently, diabetes is considered the fastest growing civilization disease. Globally, over 440 million people suffer from diabetes, and it is estimated that this number will increase to 700 million by 2045. Pancreatic islets are complex, highly vascularized mini-organs, and only the development of a fully functional vascularized pancreatic islet model could lead to the progress of knowledge about diabetes evolution, new therapeutic strategies, and the islet generation for applications in regenerative medicine. Therefore, the main goal of our study was to develop a microfluidic system for the simultaneous culture of two three-dimensional (3D) research models. The device presented in this article was used to simultaneously culture a model of a blood vessel composed of endothelial cells (HUVEC) developed using the Viscous Finger Patterning (VFP) technique and a model of the pancreatic islet, which was developed using a co-culture of α and β cells. During the research, device production method was optimized, and for this purpose, the most precise micro-milling technique was compared with the rapid prototyping technique - 3D printing. The spatial arrangement of cells in the developed models, their morphology, and viability were visualized using fluorescence staining and confocal microscopy analysis. This article presents preliminary research to develop a long-term culture of a complex model imitating the connection between the microvessel and the pancreatic islet, which in the future will be used to develop new therapeutic strategies or generate fully functional islets.

Evaluation of ride quality in a passenger car with non-uniform tyre radial stiffness

This study is dedicated to examining the influence of varying radial stiffness along the circumference of tyres on a road vehicle ride quality and with a specific focus on aspects relevant to maintenance. Computer simulations employing a three-dimensional road-vehicle model, developed within commercial multi-body software, were conducted to explore the multifaceted factors influencing vehicle behaviour. These factors encompass road unevenness, driving speed, and the range of radial force variation resulting from harmonic changes in tire radial stiffness. Furthermore, simulation tests were carried out using a model of a diagnostic wheel balancing machine, which holds significance in vehicle maintenance practices. Measurements obtained from a passenger car equipped with standard tires with minimal non-uniformity, served as reference values for assessing the car's vibration levels. Additionally, selected scenarios were examined, involving vehicle with multiple wheels exhibiting non-uniform radial stiffness. The findings underscore that non-uniform radial stiffness can magnify the detrimental effects of road irregularities, potentially leading to amplified vibration levels and a heightened need for maintenance considerations.

2D and 3D numerical modelling for preliminary assessment of long-term deterioration in Irish glacial till geotechnical slopes

ABSTRACT Long-term geotechnical slope deterioration, influenced by weathering and meteorological factors, presents stability challenges to infrastructure. Wetting and drying cycles lead to pore water pressure variations, causing deformations and slope failure. Studies on glacial tills which investigate deterioration in geotechnical slopes focus on variables like pore water pressure, soil water retention, compaction, freeze–thaw cycles and cracking. This research conducts a preliminary assessment of an Irish glacial till-cut slope, establishing a data-driven foundation for long-term slope behaviour studies. Data analysis, geospatial modelling and numerical simulations were performed on a cut slope in Castleblayney (Ireland), considering short-term/undrained and long-term/drained conditions. FLAC/Slope and Scoops3D were used for 2D and 3D slope stability analyses, applying the First-Order Second Moment (FOSM) probabilistic approach to assess how minor soil property changes affect slope stability, including long-term deterioration scenarios. The study underscores the importance of precise instrument placement within Irish glacial till geotechnical cut slopes, particularly at the uppermost part where shallow and deep failures coincide under long-term and short-term scenarios. This informs strategic instrument positioning for accurate slope deterioration investigations. This research lays the groundwork for understanding mechanisms driving geotechnical slope deterioration and provides insights for future studies on geotechnical asset deterioration models in Irish glacial tills.

Computational 3D Models of Fe2+/3+-Aβ1-42 Complexes Associated with Alzheimer's Disease.

The interaction between iron and amyloid-beta (Aβ) peptides has received significant attention in Alzheimer's disease (AD) research due to its potential implications in developing this pathology. However, the coordination preferences of iron and Aβ1-42 have not been thoroughly investigated or remain unknown. This study employs a computational protocol that combines homology modeling techniques with quantum mechanics (DTF-xTB) calculations to build and evaluate several 3D models of Fe2+/3+-Aβ1-42. Our results reveal well-defined complexes for both the metal and peptide moieties, and we discuss the molecular interactions stabilizing these complexes by elucidating the coordinating environments and binding preferences. These proposed models offer valuable insights into the role of iron in Alzheimer's disease (AD) pathology.

Simulation and training for pediatric colorectal surgery and anorectal malformation: a scoping review.

To study the published literature for various models used for simulation and training in the field of pediatric colorectal surgery. A PubMed search was conducted for studies of simulation models in anorectal malformation on 24 March 2024 with the search words 'simulation pediatric colorectal surgery' followed by another search on 'simulation AND anorectal malformation' that gave 22 and 14 results, respectively (total 36). After removing 4 duplicate publications, 12 were found relevant to simulation and training in colorectal diseases. One publication relevant to the topic was added from literature, thirteen articles were studied. Of these, 5; 1; 4; and 3 were on inanimate models; animate model; 3D reconstructions; and training, respectively. Simulation models are available for posterior sagittal anorectoplasty. The same inanimate model was used in five articles. The animate model was based on a chicken cadaver. 3D models have been made for personalized preoperative assessment and to understand the imaging in anorectal malformation. One 3D model was made by regeneration of organoid epithelium. Training modules were made to evaluate surgical dissection, standardize surgical techniques, and improve proficiency. Simulation models are an important tool for teaching the steps of surgery and discussing the nuances of operative complications among mentors and peers. With advances in this field, the development of high-fidelity models, more training modules, and consensus on surgical techniques will benefit surgical training.

Head and neck tumor segmentation from [18F]F-FDG PET/CT images based on 3D diffusion model

Objective. Head and neck (H&N) cancers are among the most prevalent types of cancer worldwide, and [18F]F-FDG PET/CT is widely used for H&N cancer management. Recently, the diffusion model has demonstrated remarkable performance in various image-generation tasks. In this work, we proposed a 3D diffusion model to accurately perform H&N tumor segmentation from 3D PET and CT volumes. Approach. The 3D diffusion model was developed considering the 3D nature of PET and CT images acquired. During the reverse process, the model utilized a 3D UNet structure and took the concatenation of 3D PET, CT, and Gaussian noise volumes as the network input to generate the tumor mask. Experiments based on the HECKTOR challenge dataset were conducted to evaluate the effectiveness of the proposed diffusion model. Several state-of-the-art techniques based on U-Net and Transformer structures were adopted as the reference methods. Benefits of employing both PET and CT as the network input, as well as further extending the diffusion model from 2D to 3D, were investigated based on various quantitative metrics and qualitative results. Main results. Results showed that the proposed 3D diffusion model could generate more accurate segmentation results compared with other methods (mean Dice of 0.739 compared to less than 0.726 for other methods). Compared to the diffusion model in 2D form, the proposed 3D model yielded superior results (mean Dice of 0.739 compared to 0.669). Our experiments also highlighted the advantage of utilizing dual-modality PET and CT data over only single-modality data for H&N tumor segmentation (with mean Dice less than 0.570). Significance. This work demonstrated the effectiveness of the proposed 3D diffusion model in generating more accurate H&N tumor segmentation masks compared to the other reference methods.

Chinese dragon modeling based on Openscad

Nowadays, 3D modeling technology has become a vital link between modern technology and traditional culture. The question of how to replicate and innovate traditional cultural elements using advanced computer graphics (CG) technology has become a topic worthy of exploration. Therefore, this paper aims to discuss how to construct a dragon model rich in Chinese traditional characteristics through the powerful 3D modeling tool OpenSCAD, to demonstrate the potential of integrating modern modeling technology with Chinese traditional cultural elements. The paper first introduces the basic features of OpenSCAD and its potential applications in constructing complex 3D models, followed by a detailed discussion on the design concept, modeling process, and technical details of the Chinese dragon model, including the dragon's posture, detail depiction, and color coordination. Ultimately, a digitally rendered Chinese dragon with profound traditional aesthetic sensibilities was successfully created. The experimental evaluation results garnered widespread recognition from evaluators, particularly in terms of appearance.

Concordance of left ventricular volumes and function measurements between two human readers, a fully automated AI algorithm, and the 3D heart model

BackgroundEchocardiography is essential in cardiovascular medicine for screening, diagnosis, and monitoring. Artificial intelligence (AI) has the potential to improve echocardiography by reducing variability and analysis time. While 3D echocardiography is becoming more accurate, 2D imaging still dominates clinical care. We aimed to evaluate agreement in measures of left ventricular (LV) volumes and function between human readers, a fully automated AI 2D algorithm, and the 3D Heart Model.MethodsA retrospective analysis was conducted on 109 patients who underwent 2D and 3D transthoracic echocardiography. LV end-diastolic and end-systolic volumes (LVEDV, LVESV) and ejection fraction (LVEF) were measured by two operators, a commercially available AI algorithm (US2ai), and the 3D Heart Model. Global longitudinal strain (GLS) was measured by the integrated semi-automated software and the AI algorithm. Outcomes included measures of agreement [bias, limit of agreement and Pearson's correlation (R)]ResultsFor LV volume measurements, the AI algorithm was strongly correlated with the average of the human operators (r = 0.89 for LVEDV and r = 0.92 for LVESV), which was higher than between the operators (r = 0.74 and r = 0.84, respectively, p < 0.01). The same trend was seen for measures of reliability with respect to LVEDV, but not LVESV. AI demonstrated comparable performance to human operators in measuring LVEF, while the 3D Heart Model had a weaker correlation and reliability compared with human operators and AI measurements. The correlation between human operators and AI for GLS was only moderate.ConclusionThis study demonstrates AI-based echocardiography as a promising tool for accurately assessing LV volumes and LVEF in clinical practice. AI-based measures demonstrated a significantly lower inter-operator variability, thereby improving the consistency and reliability of these assessments. Moreover, AI may prove particularly effective for conducting retrospective bulk analyses, offering a valuable tool for comprehensive evaluations of past data.

Gap Measurement Method Based on Projection Lines and Convex Analysis of 3D Points Cloud

Abstract Accurate measurement of the gap between the lower surface of the relay and the ground is critical for ensuring the quality of the finished product. Traditional gap measurement methods have some shortcomings, such as low accuracy, poor robustness, and loss of depth clues in obscured areas. In this study, a novel gap measurement method based on computer vision is proposed, which includes a projection line model based on guided filtering and a 3D surface point cloud model based on a three dimensional plane reference.- The relay gap was measured by calculating the projection lines of the upper and lower surfaces of the gap with an error of ±0.016 mm. A 3D point cloud model captures the key features of the underside of the relay through image processing techniques, and combines convex hull and centroid estimation to construct a three-dimensional reference plane for the gap, which could achieve high-precision, real-time measurement of the gap (with an error less than ±0.0087 mm). The experimental measurement results show that the proposed method is better than the SelfConvNet method, which has a high measurement accuracy and strong anti-interference ability, and an accuracy rate of up to 99.5% in factory relay quality inspection experiments.

Narrative review of patient-specific 3D visualization and reality technologies in skull base neurosurgery: enhancements in surgical training, planning, and navigation

Recent advances in medical imaging, computer vision, 3-dimensional (3D) modeling, and artificial intelligence (AI) integrated technologies paved the way for generating patient-specific, realistic 3D visualization of pathological anatomy in neurosurgical conditions. Immersive surgical simulations through augmented reality (AR), virtual reality (VR), mixed reality (MxR), extended reality (XR), and 3D printing applications further increased their utilization in current surgical practice and training. This narrative review investigates state-of-the-art studies, the limitations of these technologies, and future directions for them in the field of skull base surgery. We begin with a methodology summary to create accurate 3D models customized for each patient by combining several imaging modalities. Then, we explore how these models are employed in surgical planning simulations and real-time navigation systems in surgical procedures involving the anterior, middle, and posterior cranial skull bases, including endoscopic and open microsurgical operations. We also evaluate their influence on surgical decision-making, performance, and education. Accumulating evidence demonstrates that these technologies can enhance the visibility of the neuroanatomical structures situated at the cranial base and assist surgeons in preoperative planning and intraoperative navigation, thus showing great potential to improve surgical results and reduce complications. Maximum effectiveness can be achieved in approach selection, patient positioning, craniotomy placement, anti-target avoidance, and comprehension of spatial interrelationships of neurovascular structures. Finally, we present the obstacles and possible future paths for the broader implementation of these groundbreaking methods in neurosurgery, highlighting the importance of ongoing technological advancements and interdisciplinary collaboration to improve the accuracy and usefulness of 3D visualization and reality technologies in skull base surgeries.

Development Diagnostik Of Three Tier Multiple Choice Diagnostic Test Instrument To Assess Learners' Ability On Static Electricity Material

This study aims to determine the feasibility and ability of learners to the instruments developed. This research was conducted at SMA Negeri 6 Pematangsiantarcarriedin the odd semester of the 2023/2024 academic year. The type of research used is R & D (Reaserch and Development) using 3D models. The study was conducted on students who have studied static electricity materials. The samples used in this study were 36 students from Class XII-IPA 3 taken byrandom sampling. Data collection techniques in this study is by way of interviews, tests, and provide a response questionnaire. Data analysis was performed using the person correlation equation with diagnostic tests. The results of this study is a test instrument to measure the ability of students in SMA Negeri 6 Pematangsiantar on static electricity as many as 20 items of diagnostic questionsthree tier multiple choice. The item is already valid measured by the estimated product moment, has a high level of reliability with a value of 0.712, the difficulty level of the item is good. The results of the analysis of the problem items and the analysis of the ability of students showed that the test instruments used are effective in measuring the ability of students in SMA Negeri 6 Pematangsiantar on static electricity.

Neural patient-specific 3D-2D registration in laparoscopic liver resection.

Augmented reality guidance in laparoscopic liver resection requires the registration of a preoperative 3D model to the intraoperative 2D image. However, 3D-2D liver registration poses challenges owing to the liver's flexibility, particularly in the limited visibility conditions of laparoscopy. Although promising, the current registration methods are computationally expensive and often necessitate manual initialisation. The first neural model predicting the registration (NM) is proposed, represented as 3D model deformation coefficients, from image landmarks. The strategy consists in training a patient-specific model based on synthetic data generated automatically from the patient's preoperative model. A liver shape modelling technique, which further reduces time complexity, is also proposed. The NM method was evaluated using the target registration error measure, showing an accuracy on par with existing methods, all based on numerical optimisation. Notably, NM runs much faster, offering the possibility of achieving real-time inference, a significant step ahead in this field. The proposed method represents the first neural method for 3D-2D liver registration. Preliminary experimental findings show comparable performance to existing methods, with superior computational efficiency. These results suggest a potential to deeply impact liver registration techniques.

Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning

Background: Pancreatic cysts in autosomal dominant polycystic kidney disease (ADPKD) correlate with PKD2 mutations, which have a different phenotype than PKD1 mutations. However, pancreatic cysts are commonly overlooked by radiologists. Here, we automate the detection of pancreatic cysts on abdominal MRI in ADPKD. Methods: Eight nnU-Net-based segmentation models with 2D or 3D configuration and various loss functions were trained on positive-only or positive-and-negative datasets, comprising axial and coronal T2-weighted MR images from 254 scans on 146 ADPKD patients with pancreatic cysts labeled independently by two radiologists. Model performance was evaluated on test subjects unseen in training, comprising 40 internal, 40 external, and 23 test–retest reproducibility ADPKD patients. Results: Two radiologists agreed on 52% of cysts labeled on training data, and 33%/25% on internal/external test datasets. The 2D model with a loss of combined dice similarity coefficient and cross-entropy trained with the dataset with both positive and negative cases produced an optimal dice score of 0.7 ± 0.5/0.8 ± 0.4 at the voxel level on internal/external validation and was thus used as the best-performing model. In the test–retest, the optimal model showed superior reproducibility (83% agreement between scan A and B) in segmenting pancreatic cysts compared to six expert observers (77% agreement). In the internal/external validation, the optimal model showed high specificity of 94%/100% but limited sensitivity of 20%/24%. Conclusions: Labeling pancreatic cysts on T2 images of the abdomen in patients with ADPKD is challenging, deep learning can help the automated detection of pancreatic cysts, and further image quality improvement is warranted.

Modeling and Study of Different Magnet Topologies in Rotor of Low Rating IPMSMs

A study and performance analysis of magnet positions in different topology on the surface of rotor in permanent magnet synchronous motors (PMSMs) based on finite element method is observed here. A 3-phase interior PMSM is numerically simulated with ANSYS Maxwell 2018.1. Differently positioned permanent magnets improve the performance of PMSMs. Apart from handling nonlinear equations, FEM is used for simulation. ANSYS is used to analyze PMSM performance under variable conditions. This proposal examines a three-phase, 0.55 kW PMSM at 220 V, 50 Hz. Here rotor topologies of five types, namely, (i) spoke/tangential, (ii) saturable bridge / u-shape, (iii) V-shape, (iv) radial, and (v) segmented bridge permanent magnet rotor are taken for observation. The motive of this study is to analyze the performance of PMSMs in different rotor designs with different magnet positions. All topologies have been modeled and simulated with ANSYS. Each topology is compared in terms of electromagnetic and mechanical parameters. The 2D model is used to model the distribution of magnetic fields and the performance of operating parameters under transient and steady-state conditions. Magnetic flux, and efficiency are heavily influenced by the rotor shape with the volume of magnet. A study of radial force distribution and mechanical stress across rotor surface is also discussed. Motor performance is affected by the design of PMs.