3D Wall Research Articles

SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI.

Diffusion models have emerged as a leading methodology for image generation and have proven successful in the realm of magnetic resonance imaging (MRI) reconstruction. However, existing reconstruction methods based on diffusion models are primarily formulated in the image domain, making the reconstruction quality susceptible to inaccuracies in coil sensitivity maps (CSMs). k-space interpolation methods can effectively address this issue but conventional diffusion models are not readily applicable in k-space interpolation. To overcome this challenge, we introduce a novel approach called SPIRiT-Diffusion, which is a diffusion model for k-space interpolation inspired by the iterative self-consistent SPIRiT method. Specifically, we utilize the iterative solver of the self-consistent term (i.e., k-space physical prior) in SPIRiT to formulate a novel stochastic differential equation (SDE) governing the diffusion process. Subsequently, k-space data can be interpolated by executing the diffusion process. This innovative approach highlights the optimization model's role in designing the SDE in diffusion models, enabling the diffusion process to align closely with the physics inherent in the optimization model-a concept referred to as model-driven diffusion. We evaluated the proposed SPIRiT-Diffusion method using a 3D joint intracranial and carotid vessel wall imaging dataset. The results convincingly demonstrate its superiority over image-domain reconstruction methods, achieving high reconstruction quality even at a substantial acceleration rate of 10. Our code are available at https://github.com/zhyjSIAT/SPIRiT-Diffusion.

Semi-automated minimization of brick-mortar segmentation errors in 3D historical wall reconstruction

In current practices of geometric modeling and building information modeling (BIM) of architectural heritage, point cloud data acquired from site surveys is segmented into parts that correspond to actual building elements. Deep learning methods are used to automate the segmentation processes; however, each historical building presents unique challenges due to distinct construction techniques, irregular applications, deformations, and wear on the surveyed surfaces, and due to these peculiarities, segmented point cloud data may display local errors in the detection of individual architectural elements. This paper presents a method for post-processing segmented point cloud data to semi-automatically detect building elements such as bricks in historical walls. Results show that this approach, which involves testing neighborhoods of points and classified areas to identify and correct misclassified points, diminishes segmentation errors and reconstructs bricks close to their original form.

A rigid free-standing supercapacitor electrode material made from fat coal-based activated carbon foam

A free-standing electrode material is a competitive candidate for supercapacitor due to its excellent capacity and volumetric energy density. Currently, most of the studies are focused on the preparations and performances of flexible free-standing electrode materials, whereas few on the development of rigid free-standing electrode materials. Herein, a vitrinite concentrate of fat coal is used as a raw material and carbon black as an addition agent to prepare a carbon foam by way of high-pressure pyrolysis. The prepared carbon foam is activated by KOH solution to further achieve an activated carbon foam by which we have fabricated a rigid free-standing electrode material. The assembled symmetric device with the rigid free-standing electrode material demonstrates an extremely high areal specific capacitance of 2304.41 mF cm−2 at 4 mA cm−2, an outstanding cycling stability of 100 % after 40 000 cycles, and an excellent volume energy density of 10.23 mWh cm−3 at 31.78 mW cm−3. These fascinating electrochemical performances of the electrode material are attributed to unique 3D interconnected porous structure of the activated carbon foam. The micron-sized 3D interconnected pores facilitate the transport of electrolyte ions within the electrodes. Meanwhile, micropores on the 3D interconnected pore wall provide abundant active sites for electrolyte ions.

Effective Prediction of Concrete Constitutive Models for Reinforced Concrete Shear Walls under Cyclic Loading.

One of the most challenging elements of modeling the behaviour of reinforced concrete (RC) walls is combining realistic material models that can capture the observable behaviour of the physical system. Experiments with realistic loading rates and pressures reveal that steel and concrete display complicated nonlinear behaviour that is challenging to represent in a single constitutive model. To investigate the response of a reinforced concrete structure subjected to dynamic loads, this paper's study is based on many different material models to assess the advantages and disadvantages of the models on 2D and 3D RC walls using the LS-DYNA program. The models consisted of the KCC model and the CDP model, which represented plasticity and distinct tensile/compressive damage models, and the Winfrith model, which represented plasticity and the smeared crack model. Subsequently, the models' performances were assessed by comparing them to experimental data from reinforced concrete structures, in order to validate the accuracy of the overall behaviour prediction. The Winfrith model demonstrated satisfactory results in predicting the behaviour of 2D and 3D walls, including maximum strength, stiffness deterioration, and energy dissipation. The method accurately predicted the maximum strength of the Winfrith concrete model for the 2D wall with an error of 9.24% and for the 3D wall with errors of 3.28% in the X direction and 5.02% in the Y direction. The Winfrith model demonstrated higher precision in predicting dissipation energy for the 3D wall in both the X and Y directions, with errors of 6.84% and 6.62%, correspondingly. Additional parametric analyses were carried out to investigate structural behaviour, taking into account variables such as concrete strength, strain rate, mesh size, and the influence of the element type.

Geometric error self-calibration method of five-axis dispensing machine based on the product of exponentials formula

Geometric error identification and kinematic calibration are common and effective methods for improving the machining accuracy of five-axis machines. Compared with the traditional measurement methods characterized by complicated inspection processes and high cost, this paper proposes a self-calibration method for a five-axis dispensing machine based on monocular vision and the product of the exponentials formula. The proposed method can automatically identify geometric errors and complete kinematic calibration, even for simultaneous five-axis motion. First, a ChArUco marker-based pose detection system is designed to achieve a wide range of calibration space for a five-axis dispensing machine. Based on this, the proposed sub-pixel checkpoint detection framework has higher pose detection performance accuracy at different depths of the field. Then, a general kinematic error model of five-axis machines is established using screw theory to avoid singularities. Moreover, the identification method of its geometric error is proposed for an RRTTT-type five-axis dispensing machine. Finally, an arc-shaped dispensing trajectory for the 3D glasses' inner wall is used for experimental validation. The experimental results show that the average orientation quantization error decreases from 0.0112 rad to 0.0039 rad. In contrast, the average position error decreases from 0.1627 mm to 0.0473 mm before and after the self-calibration, respectively. Thus, the convenience, effectiveness, and accuracy of the self-calibration method are validated on this five-axis dispensing machine.

An extended phase graph-based framework for DANTE-SPACE simulations including physiological, temporal, and spatial variations.

The delay alternating with nutation for tailored excitation (DANTE)-sampling perfection with application-optimized contrasts (SPACE) sequence facilitates 3D intracranial vessel wall imaging with simultaneous suppression of blood and CSF. However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wall, CSF, and blood. This paper introduces a comprehensive DANTE-SPACE simulation framework, with the aim of providing a better understanding of the underlying contrast mechanisms and facilitating improved parameter selection and contrast optimization. An extended phase graph formalism was developed for efficient spin ensemble simulation of the DANTE-SPACE sequence. Physiological processes such as pulsatile flow velocity variation, varying flow directions, intravoxel velocity variation, diffusion, and effects were included in the framework to represent the mechanisms behind the achieved signal levels accurately. Intravoxel velocity variation improved temporal stability and robustness against small velocity changes. Time-varying pulsatile velocity variation affected CSF simulations, introducing periods of near-zero velocity and partial rephasing. Inclusion of diffusion effects was found to substantially reduce the CSF signal. Blood flow trajectory variations had minor effects, but differences along the trajectory reduced DANTE efficiency in low- areas. Introducing low-velocity pulsatility of both CSF and vessel wall helped explain the in vivo observed signal heterogeneity in both tissue types. The presented simulation framework facilitates a more comprehensive optimization of DANTE-SPACE sequence parameters. Furthermore, the simulation framework helps to explain observed contrasts in acquired data.

Inertial Sensing of the Abdominal Wall Kinematics during Diaphragmatic Breathing in Head Standing

Head standing (HS) in concurrence with diaphragmatic breathing is an atypical deviation from daily activity, yet commonly practiced. The study aimed at the inertially sensed effect of diaphragmatic versus normal breathing on the abdomen wall kinematics during HS. Twenty-eight men and women maintained HS and erect standing (ES) under normal and diaphragmatic breathing. An inertial sensor (LORD MicroStrain®, 3DM-GX3®-45, 2 cm above the umbilicus, 100 Hz, MicroStrain, Williston, VT, USA) recorded the 3D abdomen wall angular displacement (AD) (bandpass filter (0.1–0.5 Hz)). ANOVAs (p ≤ 0.05, SPSS 28.0) were applied to the extracted variables (AD path: magnitude, individual variability-%CVind, and diaphragmatic to normal ratio). Reliability measures (ICC and %SEM) and the minimal detectable change (%MDC90) were estimated. Diaphragmatic breathing increased the AD path (p ≤ 0.05) with the diaphragmatic to normal ratio being lower in HS (p ≤ 0.05). The similar AD time series (cross-correlations at p ≤ 0.05) and the ICCs (>0.80) indicated excellent reliability with the similar across conditions %CVind (p ≤ 0.05), further enhancing reliability. The %MDC90 was consistently higher than the %SEM upper boundary, indicating the differences as “real” ones. The results contribute to the limited data concerning a widely practiced atypical deviation from daily activity, as HS in concurrence with diaphragmatic breathing.

Pendampingan Peningkatan Human Capital Melalui Eksplorasi Dimensi Visual di Kampung Tridi, Malang

Tridi Village is a village located in Malang City, Indonesia, which is famous for the uniqueness and beauty of the 3D wall paintings that decorate the entire village. These paintings create an interesting visual atmosphere, reflecting local art, culture and traditions. Tridi Village has become a popular tourism destination that attracts tourists with its unique charm. Apart from the wall art, this village also has cultural heritage and local crafts which are an additional attraction. Increasing tourism attractiveness through innovative digital marketing strategies is expected to have a positive impact on economic growth and welfare of the people of Tridi Village. This research explores the application of creative thinking methods in developing digital marketing strategies to increase the tourism attractiveness of Kampung Tridi. Through brainstorming and mind mapping sessions, the people of Kampung Tridi are actively involved in generating innovative ideas related to the potential of tourism, arts and local culture. Brainstorming sessions create a collaborative space without critical boundaries, while mind mapping graphically visualizes the relationships between ideas. The result is an integrated digital marketing strategy, designed to increase tourist visits and empower the local economy. Implementation of this strategy requires active community involvement and full support from the local government.

In-Situ Dehydration Test of Shield Spoil in Mudstone and Pebble Soil Composite Stratum

When earth pressure balance (EPB) shield machine is driving in mudstone sand pebble composite stratum, it will produce a large amount of spoil with high water content. The high moisture content of spoil not only increases the difficulty and cost of transportation, but also easily leads to environmental pollution problems. In this paper, based on the shield tunnel project of Chengdu Metro Line 30, the hydraulic characteristic of shield spoil was tested, and on this basis, laboratory tests of shield spoil dehydration were carried out according to the designed precipitation scheme. The results show that: 1) The moisture content of the EPB shield spoil in the mudstone sand pebble composite stratum is as high as 55.2%, and its permeability coefficient is basically the same as that of silt, and the shield residue has the condition of in-situ dehydration. 2) The dehydration amount and residue moisture content of spoil in slope-type spoil pit showed a linear relationship with time, and the dehydration rate is slow and the total precipitation is less. In other schemes, the dehydration amount and water content of spoil increase rapidly in the first 24 hours and slowly in the later period. 3) Considering the total amount and speed of dehydration within 24 hours, the dehydration effect of spoil pit is ranked from high to low: 3D gravel cage wall spoil pit > 3D spoil pit with vacuum pumping > 3D permeable stone spoil pit > 3D spoil pit > Slope-type spoil pit. 4) 3D gravel cage wall spoil pit has high dewatering efficiency, and vacuum pumping can assist the discharge of water. It is recommended to use 3D gravel cage wall spoil pit and vacuum pumping scheme for on-site EPB tunnel spoil dewatering.

Deep scene synthesis of Atlanta-world interiors from a single omnidirectional image.

We present a new data-driven approach for extracting geometric and structural information from a single spherical panorama of an interior scene, and for using this information to render the scene from novel points of view, enhancing 3D immersion in VR applications. The approach copes with the inherent ambiguities of single-image geometry estimation and novel view synthesis by focusing on the very common case of Atlanta-world interiors, bounded by horizontal floors and ceilings and vertical walls. Based on this prior, we introduce a novel end-to-end deep learning approach to jointly estimate the depth and the underlying room structure of the scene. The prior guides the design of the network and of novel domain-specific loss functions, shifting the major computational load on a training phase that exploits available large-scale synthetic panoramic imagery. An extremely lightweight network uses geometric and structural information to infer novel panoramic views from translated positions at interactive rates, from which perspective views matching head rotations are produced and upsampled to the display size. As a result, our method automatically produces new poses around the original camera at interactive rates, within a working area suitable for producing depth cues for VR applications, especially when using head-mounted displays connected to graphics servers. The extracted floor plan and 3D wall structure can also be used to support room exploration. The experimental results demonstrate that our method provides low-latency performance and improves over current state-of-the-art solutions in prediction accuracy on available commonly used indoor panoramic benchmarks.

Self-consistent coupling of JOREK and CARIDDI: On the electromagnetic interaction of 3D tokamak plasmas with 3D volumetric conductors

The self-consistent electromagnetic integration of tokamak plasma magnetohydrodynamic (MHD) models with external conductors is considered in this manuscript. We integrate the extended MHD code JOREK and the eddy current code CARIDDI, via a scheme based on the virtual casing principle enabling two-way coupled fully implicit simulations. The robustness of this new integrated tool is validated against JOREK-STARWALL and CarMa0NL simulations for vertical displacement events in a simplified ASDEX Upgrade-like geometry and for n = 1 tearing modes in a circular high-aspect-ratio tokamak. The impact of 3D wall structures on the plasma evolution is highlighted introducing ports at different locations of a simplified axisymmetric wall and characterizing its effect on the plasma evolution. In addition to realistically capturing the 3D interactions between plasma and wall structures, the coupled codes will allow in the future 1:1 comparisons to experiments using virtual magnetic diagnostics that capture screening effects accurately.

Differences in distribution and features of carotid and middle cerebral artery plaque in patients with pial infarction and perforating artery infarction: A 3D vessel wall imaging study

PurposeAtherosclerotic plaques of carotid artery (CA) and middle cerebral artery (MCA) are important causes of acute ischemic stroke (AIS). This study was designed to jointly assess the plaque distribution and features of CA and MCA in AIS patients with pial infarction (PI) and perforating artery infarction (PAI), and to investigate the associations between plaque characteristics and ischemic infarction patterns. MethodsImaging data of sixty-five patients from a cross-sectional study were reviewed. All the patients had acute infarction in the MCA territory on diffusion weighted imaging (DWI) and underwent CA and MCA vessel wall imaging (VWI). The CA and MCA plaque presence and high-risk features on the ipsilateral side of infarction were analyzed. The brain infarction lesions were divided into PI group vs. non-PI group, and PAI group vs. non-PAI group. Different plaque distribution types and plaque features were compared in each two groups, and their associations were investigated using binary logistic regression. ResultsSixty-five patients (mean age, 54.6 ± 10.1 years; 61 men) were included. The CA high-risk plaque (OR: 5.683 [1.409–22.929], P = 0.015) and MCA plaque presence (OR: 3.949 [1.397–11.162], P = 0.010) were significantly associated with PI. MCA plaques that involved the orifice of the perforating arteries were significantly associated with PAI (OR: 15.167 [1.851–124.257], P = 0.011). ConclusionCA and MCA plaques show distinct distribution and high-risk features in patients with PI and PAI. Combined intracranial and extracranial arteries imaging should be considered for the evaluation of the symptomatic ischemic patients.

3D aneurysm wall enhancement is associated with symptomatic presentation

BackgroundAneurysm wall enhancement (AWE) is a potential surrogate biomarker for aneurysm instability. Previous studies have assessed AWE using 2D multiplanar methods, most of which were conducted qualitatively.ObjectiveTo use a new...

Application of power algorithm optimization for optimal placement of BRB in 3D shear wall frame building structure

This paper examines the optimal placement, optimal numbers, and the optimal shape of Buckling Restrained Braces (BRB) for a 3D shear-wall frame building structure based on linear static analysis utilizing ETABS software. The total amount of BRBs referred to as the number of BRBs are considered as design variables and the objective function to be minimized is the maximum story displacement and inter-story drift. The diagonal shape (D), X-shape (X), V-shape (V), and Inverted V-shape (Inv-V) of BRBs are installed between shear walls simultaneously with initial stiffnesses of 1K0, 2K0, 4K0, and 8K0, respectively. Then, the performance efficiency analysis is carried out to identify the effectiveness of initial stiffness, BRB shapes, and optimal stories. Based on the results of the optimization procedure and efficiency analysis, it is found that the performance of the structure can be improved by optimizing BRB placement within the optimal stories rather than using the maximum amount of BRBs in all stories. The most optimal location to install BRBs is the middle stories and the BRB placement at the upper and lower stories is shown to have minor or no effects on reducing story responses of the structure. Furthermore, the model with Inv-V, V, and X shapes of BRB have almost the same maximum efficiency performance, while the model with diagonal shapes has the lowest performance efficiency. Additionally, the maximum performance of the structure can be achieved by using larger initial stiffness. The proposed method is further validated by comparing the results of ETABS with MATLAB programming. It concludes that the method proposed in this study saves 40% of the total amount of BRBs used in the structure by optimal placement of BRBs within the height of the structure. This method of optimization allows the structural designer to decide the optimal placement, optimal shape, and optimal stiffness of BRBs either by the predetermined performance level of the structure or based on experiences in RC shear wall-frame building structures.

Enhancing prediction of cancer therapy-related cardiomyopathy from surveillance echocardiograms: A Children’s Oncology Group (COG) report.

10012 Background: Many childhood cancer patients receive cardiotoxic therapies and need surveillance for therapy-related cardiomyopathy (CM). (Echo)cardiography is used to screen for cardiac dysfunction but has relatively poor discriminatory ability to predict who will develop CM. We sought to identify combinations of echo parameters that can better predict which patients subsequently develop CM. Methods: Longitudinal echos (obtained per routine care) of patients diagnosed with cancer < 21y who subsequently met CM criteria (left ventricular [LV] ejection fraction ≤50% / fractional shortening ≤28%, ≥2 times, with ≥1 time after completion of cancer therapy) plus clinical data were collated from COG sites. Echos and data from patients without CM were also collated. All echos were centrally remeasured for 42 routinely reported parameters in blinded fashion. We applied least absolute shrinkage and selection operator (LASSO) to fit logistic models to identify the most influential predictors for CM development within 2 and 5y of echo, plus age and sex. Data were randomly split into training (85%) and test (15%) sets with 10-fold cross validation. Prediction accuracy was calculated using area under the ROC curve (AUC), based on the model that provided the minimum mean cross-validated error. Results: Echos from 88 CM cases (248 echos predating CM) and 126 non-cases (518 echos) were available. Patients (n = 214) were diagnosed at mean age 7.7±5.2y with mean 9.5±4.0y follow-up. Mean doxorubicin equivalent doses for cases and non-cases were 350±188 and 272±199 mg/m2, respectively. For 2y CM prediction, models achieved training AUC 0.85 (95%CI 0.78-0.92; 261 echos) and test AUC 0.74 (95% CI 0.74-0.90; 46 echos). Factors selected included age, 2-dimensional (2D) measurements of LV geometry (LV systolic and end-systolic dimensions, and posterior wall thickness), systolic function (M-mode fractional shortening), diastolic function (mitral inflow E wave, septal E’, septal A’), and a measurement of combined systolic and diastolic function (myocardial performance index). For 5y CM prediction, models achieved training AUC 0.90 (95%CI 0.85-0.95; 175 echos) and test AUC 0.89 (95%CI 0.78-0.99; 30 echos). Age, LV end-systolic dimension (2D and M-mode), M-mode LV posterior wall thickness, 2D wall thickness-dimension ratio, mitral inflow E, septal E’, septal A’, and the myocardial performance index were selected. At both times 2D end-systolic dimension was the most influential parameter. Inclusion of anthracycline and chest radiotherapy dose did not meaningfully improve the AUCs. Conclusions: Prediction models that incorporate conventional echo data may be able to accurately identify childhood cancer patients at high risk of developing CM 2-5y prior to CM diagnosis. This may provide a window of opportunity to introduce interventions that may arrest or slow CM progression.

Imaging Methods to Quantify the Chest and Trunk Deformation in Adolescent Idiopathic Scoliosis: A Literature Review.

Background context: Scoliosis is a three-dimensional deformity of the spine with the most prevalent type being adolescent idiopathic scoliosis (AIS). The rotational spinal deformation leads to displacement and deformation of the ribs, resulting in a deformity of the entire chest. Routine diagnostic imaging is performed in order to define its etiology, measure curve severity and progression during growth, and for treatment planning. To date, all treatment recommendations are based on spinal parameters, while the esthetic concerns and cardiopulmonary symptoms of patients are mostly related to the trunk deformation. For this reason, there is a need for diagnostic imaging of the patho-anatomical changes of the chest and trunk in AIS. Aim: The aim of this review is to provide an overview, as complete as possible, of imaging modalities, methods and image processing techniques for assessment of chest and trunk deformation in AIS. Methods: Here, we present a narrative literature review of (1) image acquisition techniques used in clinical practice, (2) a description of various relevant methods to measure the deformity of the thorax in patients with AIS, and (3) different image processing techniques useful for quantifying 3D chest wall deformity. Results: Various ionizing and non-ionizing imaging modalities are available, but radiography is most widely used for AIS follow-up. A disadvantage is that these images are only acquired in 2D and are not effective for acquiring detailed information on complex 3D chest deformities. While CT is the gold standard 3D imaging technique for assessment of in vivo morphology of osseous structures, it is rarely obtained for surgical planning because of concerns about radiation exposure and increased risk of cancer during later life. Therefore, different modalities with less or without radiation, such as biplanar radiography and MRI are usually preferred. Recently, there have been advances in the field of image processing for measurements of the chest: Anatomical segmentations have become fully automatic and deep learning has been shown to be able to automatically perform measurements and even outperform experts in terms of accuracy. Conclusions: Recent advancements in imaging modalities and image processing techniques make complex 3D evaluation of chest deformation possible. Before introduction into daily clinical practice, however, there is a need for studies correlating image-based chest deformation parameters to patient-reported outcomes, and for technological advancements to make the workflow cost-effective.

Scaling laws for two- and three-dimensional wall jet scour based on the phenomenological theory of turbulence

The scour induced by wall jets may cause serious bed erosion and thus damage to hydraulic structures. Previous studies are largely empirical, providing only correlations of experimental data. At present, it is not clear what difference exists in the physical mechanisms of two-dimensional (2D) and three-dimensional (3D) wall jet scour. This study first summarizes previous efforts for predicting wall jet scour depths. Then, a scaling analysis is presented for investigating scour depths by applying the phenomenological theory of turbulence. It is shown that for wall jet cases, the dimensionless equilibrium scour depth can generally be expressed as a power function of the densimetric Froude number and relative roughness height, with the power index depending on jet configurations. The predictions of scour depth using the resulting formulas agree well with published data. The present analysis provides new insights into the understanding of the underlying physical mechanisms of wall jet scour as well as the difference between 2D and 3D configurations.

New understanding from intestinal absorption model: How physiological features influence mass transfer and absorption

AbstractMathematical modeling of mass transfer and absorption in the small intestine has been a challenging task. Systematic review and analysis of existing efforts indicate the need to pursue a reliable predictive model that is physically sound and computationally efficient. With the consideration of 3D intestinal inner wall structure, this work rigorously derives an absorption model that can be used as a source term in a 1D distributed model, conventionally called the diffusion–convection–reaction model. Moreover, computational fluid dynamics simulations are carried out to generate in silico experimental data for quantification of the mass‐transfer coefficient in the absorption model. This model facilitates a better understanding of the intricate influence of intestinal morphology and motility on mass transfer and absorption in the intestine. Rat duodenum featuring a villous structure and pendular movement is selected as an example to demonstrate the capability of this approach.

Use of the double-stage LSTM network in electrical tomography for 3D wall moisture imaging

This paper deals with a new two-step algorithmic method to improve the accuracy of imaging moisture in building walls using electrical impedance tomography (EIT). The problem of assessing dampness in buildings is important both from the point of view of the national cultural heritage, economics, safety, and aesthetics of real estate and the health of people inside buildings. The main impediment to EIT development is solving the ill-posed and inverse problem that makes obtaining reliable images of high-resolution moisture distribution difficult. To resolve this problem, we propose the new double-stage neural network approach. First, the method's originality is determined by using the second neural network, which improves the images obtained thanks to the first network. Using the first network, training images are generated, constituting inputs for the second network, while both neural networks are trained on a similar set of pattern output images. The approach to input measurements and images is also original, which, thanks to the conversion into vectors (sequences), made it possible to use the LSTM (long short-term memory) network. The research proved the effectiveness of the new method.

EDIT Software: A tool for the semi-automatic 3D reconstruction of bladder cancer and urinary bladder of animal models

Background and objectiveThis study presents the EDIT software, a tool for the visualization of the urinary bladder anatomy in the 3D space and for its semi-automatic 3D reconstruction. Methods: The inner bladder wall was computed by applying a Region of Interest (ROI) feedback-based active contour algorithm on the ultrasound images while the outer bladder wall was calculated by expanding the inner borders to approach the vascularization area on the photoacoustic images. The validation strategy of the proposed software was divided into two processes. Initially, the 3D automated reconstruction was performed on 6 phantom objects of different volume in order to compare the software computed volumes of the models with the true volumes of phantoms. Secondly, the in-vivo 3D reconstruction of the urinary bladder for 10 animals with orthotopic bladder cancer, which range in different stages of tumor progression was performed. Results: The results showed that the minimum volume similarity of the proposed 3D reconstruction method applied on phantoms is 95.59%. It is noteworthy to mention that the EDIT software enables the user to reconstruct the 3D bladder wall with high precision, even if the bladder silhouette has been significantly deformed by the tumor. Indeed, by taking into account the dataset of the 2251 in-vivo ultrasound and photoacoustic images, the presented software performs segmentation with dice similarity 96.96% and 90.91% for the inner and the outer borders of the bladder wall, respectively. Conclusions: This study delivers the EDIT software, a novel software tool that uses ultrasound and photoacoustic images to extract different 3D components of the bladder.