Volumetric 3D Research Articles

A Novel 3D Unsupervised Domain Adaptation Framework for Cross-Modality Medical Image Segmentation.

We consider the problem of volumetric (3D) unsupervised domain adaptation (UDA) in cross-modality medical image segmentation, aiming to perform segmentation on the unannotated target domain (e.g. MRI) with the help of labeled source domain (e.g. CT). Previous UDA methods in medical image analysis usually suffer from two challenges: 1) they focus on processing and analyzing data at 2D level only, thus missing semantic information from the depth level; 2) one-to-one mapping is adopted during the style-transfer process, leading to insufficient alignment in the target domain. Different from the existing methods, in our work, we conduct a first of its kind investigation on multi-style image translation for complete image alignment to alleviate the domain shift problem, and also introduce 3D segmentation in domain adaptation tasks to maintain semantic consistency at the depth level. In particular, we develop an unsupervised domain adaptation framework incorporating a novel quartet self-attention module to efficiently enhance relationships between widely separated features in spatial regions on a higher dimension, leading to a substantial improvement in segmentation accuracy in the unlabeled target domain. In two challenging cross-modality tasks, specifically brain structures and multi-organ abdominal segmentation, our model is shown to outperform current state-of-the-art methods by a significant margin, demonstrating its potential as a benchmark resource for the biomedical and health informatics research community.

Continual Adaptation of Semantic Segmentation Using Complementary 2D-3D Data Representations

Semantic segmentation networks are usually pre-trained once and not updated during deployment. As a consequence, misclassifications commonly occur if the distribution of the training data deviates from the one encountered during the robot's operation. We propose to mitigate this problem by adapting the neural network to the robot's environment during deployment, without any need for external supervision. Leveraging complementary data representations, we generate a supervision signal, by probabilistically accumulating consecutive 2D semantic predictions in a volumetric 3D map. We then train the network on renderings of the accumulated semantic map, effectively resolving ambiguities and enforcing multi-view consistency through the 3D representation. In contrast to scene adaptation methods, we aim to retain the previously-learned knowledge, and therefore employ a continual learning experience replay strategy to adapt the network. Through extensive experimental evaluation, we show successful adaptation to real-world indoor scenes both on the ScanNet dataset and on in-house data recorded with an RGB-D sensor. Our method increases the segmentation accuracy on average by 9.9% compared to the fixed pre-trained neural network, while retaining knowledge from the pre-training dataset.

Static Negative-Permeability Metasurface to Transfer Volumetric Static Magnetic Field

Inspired by transformation optics, negative permeability materials enable the transfer of static magnetic fields to a distant location far away from the current source. This is useful for situations in which it is difficult to place a current source near the region where magnetic fields are required. However, existing artificial negative permeability materials are three dimensional (3D) and bulky. In this study, we theoretically design and experimentally demonstrate a metasurface with static negative permeability that displaces volumetric 3D magnetic fields to a distant region. The design overcomes the existing limitation because the dimensions of the structure are reduced to two, and the control of the magnetic field has an increased degree of freedom. The proposed method can be further extended to tools and strategies to precisely displace and/or manipulate dc or quasistatic magnetic fields in regions of interest for various applications such as medical care and measurement precision.

The Knosp Criteria Revisited: 3-Dimensional Volumetric Analysis as a Predictive Tool for Extent of Resection in Complex Endoscopic Pituitary Surgery.

The Knosp criteria have been the historical standard for predicting cavernous sinus invasion, and therefore extent of surgical resection, of pituitary macroadenomas. Few studies have sought to reappraise the utility of this tool after recent advances in visualization and modeling of tumors in complex endoscopic surgery. To evaluate our proposed alternative method, using 3-dimensional (3D) volumetric imaging, and whether it can better predict extent of resection in nonfunctional pituitary adenomas. Patients who underwent endoscopic transsphenoidal resection of pituitary macroadenomas at our institution were reviewed. Information was collected on neurological, endocrine, and visual function. Volumetric segmentation was performed using 3D Slicer software. Relationship of tumor volume, clinical features, and Knosp grade on extent of resection was examined. One hundred forty patients were identified who had transsphenoidal resection of nonfunctional pituitary adenomas. Macroadenomas had a median volume of 6 cm 3 (IQR 3.4-8.7), and 17% had a unilateral Knosp grade of at least 3B. On multiple logistic regression, only smaller log-transformed preoperative tumor volume was independently associated with increased odds of gross total resection (GTR; odds ratio: 0.27, 95% CI: 0.07-0.89, P < .05) when controlling for tumor proliferative status, age, and sex (area under the curve 0.67). The Knosp criteria did not independently predict GTR in this cohort ( P > .05, area under the curve 0.46). Increasing use of volumetric 3D imaging may better anticipate extent of resection compared with the Knosp grade metric and may have a greater positive predictive value for GTR. More research is needed to validate these findings and implement them using automated methods.

Triplet Fusion Upconversion Nanocapsule Synthesis.

Triplet fusion upconversion (UC) allows for the generation of one high energy photon from two low energy input photons. This well-studied process has significant implications for producing high energy light beyond a material's surface. However, the deployment of UC materials has been stymied due to poor material solubility, high concentration requirements, and oxygen sensitivity, ultimately resulting in reduced light output. Toward this end, nanoencapsulation has been a popular motif to circumvent these challenges, but durability has remained elusive in organic solvents. Recently, a nanoencapsulation technique was engineered to tackle each of these challenges, whereupon an oleic acid nanodroplet containing upconversion materials was encapsulated with a silica shell. Ultimately, these nanocapsules (NCs) were durable enough to enable triplet fusion upconversion-facilitated volumetric three-dimensional (3D) printing. By encapsulating upconversion materials with silica and dispersing them in a 3D printing resin, photopatterning beyond the surface of the printing vat was made possible. Here, video protocols for the synthesis of upconversion NCs are presented for both small-scale and large-scale batches. The outlined protocols serve as a starting point for adapting this encapsulation scheme to multiple upconversion schemes for use in volumetric 3D printing applications.

Low‐Cost Volumetric 3D Printing of High‐Precision Miniature Lenses in Seconds (Advanced Optical Materials 17/2022)

Targeting the fast prototyping and massive production of complicated lenses, Zhiwei Zhu and co-workers report a low-cost volumetric 3D printing method for the ultra-fast and high-precision fabrication of miniature lenses with sub-nanometric roughness (see article number 2200488). The complex-shaped lenses are generated by the volumetric projection stereolithography and corrected by introducing an iterative learning scheme. Super-smooth surfaces are guaranteed by the meniscus equilibrium effect.

Multilevel segmentation of 2D and volumetric medical images using hybrid Coronavirus Optimization Algorithm

Medical image segmentation is a crucial step in Computer-Aided Diagnosis systems, where accurate segmentation is vital for perfect disease diagnoses. This paper proposes a multilevel thresholding technique for 2D and 3D medical image segmentation using Otsu and Kapur's entropy methods as fitness functions to determine the optimum threshold values. The proposed algorithm applies the hybridization concept between the recent Coronavirus Optimization Algorithm (COVIDOA) and Harris Hawks Optimization Algorithm (HHOA) to benefit from both algorithms' strengths and overcome their limitations. The improved performance of the proposed algorithm over COVIDOA and HHOA algorithms is demonstrated by solving 5 test problems from IEEE CEC 2019 benchmark problems. Medical image segmentation is tested using two groups of images, including 2D medical images and volumetric (3D) medical images, to demonstrate its superior performance. The utilized test images are from different modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and X-ray images. The proposed algorithm is compared with seven well-known metaheuristic algorithms, where the performance is evaluated using four different metrics, including the best fitness values, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Correlation Coefficient (NCC). The experimental results demonstrate the superior performance of the proposed algorithm in terms of convergence to the global optimum and making a good balance between exploration and exploitation properties. Moreover, the quality of the segmented images using the proposed algorithm at different threshold levels is better than the other methods according to PSNR, SSIM, and NCC values. Additionally, the Wilcoxon rank-sum test is conducted to prove the statistical significance of the proposed algorithm.

End-to-end learning of 3D phase-only holograms for holographic display

Computer-generated holography (CGH) provides volumetric control of coherent wavefront and is fundamental to applications such as volumetric 3D displays, lithography, neural photostimulation, and optical/acoustic trapping. Recently, deep learning-based methods emerged as promising computational paradigms for CGH synthesis that overcome the quality-runtime tradeoff in conventional simulation/optimization-based methods. Yet, the quality of the predicted hologram is intrinsically bounded by the dataset’s quality. Here we introduce a new hologram dataset, MIT-CGH-4K-V2, that uses a layered depth image as a data-efficient volumetric 3D input and a two-stage supervised+unsupervised training protocol for direct synthesis of high-quality 3D phase-only holograms. The proposed system also corrects vision aberration, allowing customization for end-users. We experimentally show photorealistic 3D holographic projections and discuss relevant spatial light modulator calibration procedures. Our method runs in real-time on a consumer GPU and 5 FPS on an iPhone 13 Pro, promising drastically enhanced performance for the applications above.

Using the Axial Oblique View of Computed Tomography (CT) in Evaluating Femoral Anteversion: A Comparative Cadaveric Study.

Twenty-five cadaveric adult femora’s anteversion angles were measured to develop a highly efficient and reproducible femoral anteversion measurement method using computed tomography (CT). Digital photography captured the proximal femur’s two reference lines, head-to-neck (H-N) and head-to-greater trochanter (H-G). Six reference lines (A/B in transverse section; C, axial oblique section; D/E, conventional 3D reconstruction; and M, volumetric 3D reconstruction) from CT scans were used. The posterior condylar line was used as a distal femoral reference. As measured with the H-N and H-G lines, the anteversion means were 10.43° and 19.50°, respectively. Gross anteversion measured with the H-G line had less interobserver bias (ICC; H-N = 0.956, H-G = 0.982). The 2D transverse and volumetric 3D CT sections’ B/M lines were consistent with the H-N line (p: B = 0.925, M = 0.122) and the 2D axial oblique section’s C line was consistent with the H-G line (p < 0.1). The D/E lines differed significantly from the actual gross images (p < 0.05). Among several CT scan femoral anteversion measurement methods, the novel anteversion angle measurement method using CT scans’ axial oblique section was approximated with actual gross femoral anteversion angle from the femoral head to the greater trochanter.

FINGER COUNTING AND VIRTUAL MOUSE USING CVLEARN

The finger tracking system is focused on user- data interaction, where the user interacts with virtual data, by handling through the fingers the volumetric of a 3D object that we want to represent. The finger tracking system focuses on user-data interaction, where the user interacts with virtual data, by handling through the fingers the volumetric 3D object that we want to represent. The human interaction problem gave rise to the system.The main goal is to establish a communication between them and for them to be more intuitive, Finger tracking was developed. The system is capable of tracking the real-time positions in 2D and 3D orientations of the fingers and these intuitive hand movements are used for interactions. Our project introduces an approach where with mouse cursor movements can be controlled using the real- time camera. It is basically an alternative for the all types of mouses that we use. It uses a camera and computer vision technology to controls various mouse actions and is capable of performing every task that the physical computer mouse can.

Low‐Cost Volumetric 3D Printing of High‐Precision Miniature Lenses in Seconds

Abstract3D printing is a promising method for the generation of complex‐shaped optical components. However, the printing efficiency, form accuracy, and surface smoothness are still challenging, especially for the printing of optical components. In this study, by synergizing the volumetric projection stereolithography, meniscus equilibrium effect, and iterative learning scheme, a low‐cost volumetric 3D printing method is developed for the ultra‐fast and high‐precision fabrication of miniature lenses with sub‐nanometric roughness. By including the covered liquid film as a part of the printed lens in the iterative learning, a low form error at the micrometer scale is achieved for the printed lens without any prior knowledge of the 3D printing process. As a demonstration, a sphere lens at the millimeter scale is directly printed in 2 s, achieving a peak‐to‐valley profile error of less than 5 µm, a sub‐nanometric roughness of rms = 0.614 nm, and an imaging resolution of 203.2 lp mm−1. It suggests that besides fast prototyping, the developed 3D printing strategy is suitable for the massive production of precise lenses.

Three-dimensional (3D) anatomic location, extension, and timing of severe osteoradionecrosis of the mandible.

BackgroundThe purpose of this study was to describe the topography, extension (volume), and timing of severe osteoradionecrosis (ORN) that required mandible resection in patients previously treated for head and neck cancer at a high-volume Veterans Affairs Medical Center.Materials and methodsThe records from a reference hyperbaric oxygen clinic were retrospectively analyzed (n = 50, 2018–2021). Inclusion criteria were: I) severe ORN defined as progressive ORN that required resection; II) pathologic confirmation of ORN; and III) availability of pre-operative CT-imaging. Using a radiotherapy (RT) imaging software, we performed a detailed volumetric (3D) analysis of the bone involvement by ORN. Time intervals from RT to surgery for ORN and from surgery to the last follow-up were calculated.ResultsAll patients that met inclusion criteria (n = 10) were male with significant smoking history (median 47.5 pack-years) and a median age of 57 years old at the time of RT. The primary tumors were: oropharynx (n = 6), oral cavity (n = 3) and nasopharynx (n = 1). The median time from RT to ORN surgery was 8 years. The most common ORN location was the posterior lateral body (molar) and six patients had associated fractures. The mean ORN volume was 3.6 cc (range: 0.6–8.3), corresponding to a mean 6.3% (range: 0.7–14) of the total mandibular volume. After a median follow-up of 13.5 months, no recurrence of ORN occurred. Three patients died of non-cancer and non-ORN-recurrence related causes (1 y OS 77.1%).ConclusionSevere ORN occurred after a median of 8 years from the previous RT and usually affected the posterior lateral body. Surgical resection achieved excellent ORN control.

Evaluation of visible region in volumetric 3D display using a rotating helical screen

We have proposed a volumetric 3D display in which cross-sectional images are projected on a rotating helical screen. One of challenges of this method is an existence of invisible regions generated depending on observation angle. Invisible region is determined as the sum of dark region as a result of oblique incidence of the projected light on the screen and blind region as a result of blocking light paths to the viewpoint by the screen body. The larger invisible region was shown against the higher viewpoint to the helical screen. It was also shown that invisible region mainly located in the distant side from the viewpoint and in the neighboring region to the rotation axis of the screen. Our evaluation results show that the cylindrical display volume provided by a helical screen offers enough visible region at the viewpoint side and the periphery: indispensable regions for 3D displays.

Volumetric 3D reconstruction of plant leaf cells using SEM, ion milling, TEM, and serial sectioning.

Focused ion beam scanning electron microscopy is well suited for volumetric extractions and 3D reconstructions of plant cells and its organelles. The three-dimensional (3D) reconstruction of individual plant cells is an important tool to extract volumetric data of organelles and is necessary to fully understand ultrastructural changes and adaptations of plants to their environment. Methods such as the 3D reconstruction of cells based on light microscopical images often lack the resolution necessary to clearly reconstruct all cell compartments within a cell. The 3D reconstruction of cells through serial sectioning transmission electron microscopy (ssTEM) and focused ion beam scanning electron microscopy (FIB-SEM) are powerful alternatives but not widely used in plant sciences. Here, we present a method for the 3D reconstruction and volumetric extraction of plant cells based on FIB milling and compare the results with 3D reconstructions obtained with ssTEM. When compared to 3D reconstruction based on ssTEM, FIB-SEM delivered similar results. The data extracted in this study demonstrated that tobacco cells were larger (31410 µm3) than pumpkin cells (20697 µm3) and contained more chloroplasts (175 vs. 124), mitochondria (1317 vs. 291) and peroxisomes (745 vs. 79). While individual chloroplasts, mitochondria, peroxisomes were larger in pumpkin plants (25, 53, and 50%, respectively) they covered more total volume in tobacco plants (5390, 395, 374 µm3, respectively) due to their higher number per cell when compared to pumpkin plants (4762, 134, 59 µm3, respectively). While image acquisition with FIB-SEM was automated, software controlled, and less difficult than ssTEM, FIB milling was slower and sections couldnot be revised or re-imaged as they were destroyed by the ion beam. Nevertheless, the results in this study demonstrated that both, FIB-SEM and ssTEM, are powerful tools for the 3D reconstruction of and volumetric extraction from plant cells and that there were large differences in size, number, and organelle composition between pumpkin and tobacco cells.

Bragg edge tomography characterization of additively manufactured 316L steel

In this work we perform a neutron Bragg edge tomography of stainless steel 316L additive manufacturing samples, one as built via standard laser powder bed fusion, and one using the novel three-dimensional (3D) laser shock peening technique. First, we consider conventional attenuation tomography of the two samples by integrating the signal for neutron wavelengths beyond the last Bragg edge, to analyze the bulk density properties of the material. This is used to map defects, such as porosities or cracks, which yield a lower density. Second, we obtain strain maps for each of the tomography projections by tracking the wavelength of the strongest Bragg edge corresponding to the {111} lattice plane family. Algebraic reconstruction techniques are used to obtain volumetric 3D maps of the strain in the bulk of the samples. It is found that not only the volume of the sample where the shock peening treatment was carried out yields a higher bulk density, but also a deep and remarkable compressive strain region. Finally, the analysis of the Bragg edge heights as a function of the projection angle is used to describe qualitatively crystallographic texture properties of the samples.

3D volumetric analysis at implant sites after soft tissue augmentation

Background. The role of soft tissues in the survival of dental implants remains one of the most discussed problem of the modern dentistry. Two main parameters such as the width of the keratinized gingiva and thickness of the peri-implant tissues are known to play an important role in the stability of the dental implants. Soft tissues thickness is necessary to achieve an aesthetic long-term stable result. Different methods for increasing soft tissue thickness are described in the literature.Materials and methods. Study included 30 patients with insufficient peri-implant soft tissue thickness. All patients underwent buccal soft tissue thickness augmentation by two different methods: collagen matrix (1 group) and free connective tissue graft (2 group). In the study we evaluated the amount of soft tissue thickness gain by using volumetric 3D- analysis.Results. The amount of soft tissue thickness before surgery was 1,63±0,7 mm in the 1 group, 1,61±0,7 mm in the 2 group. Three months after surgery the amount of soft tissue gain was 1,18±0,11 mm in the 1 group, 1,55 ±0,11 mm in the 2 group.Conclusion. The use of a free connective tissue graft as well as a collagen matrix is an effective method for increasing the thickness of soft tissues in the peri-implant area.

Inverse-Directed Propagation-Based Hexagonal Hogel Sampling for Holographic Stereogram Printing System

Holographic stereogram (HS) printing is a promising holographic technique for three-dimensional (3D) visualization of an object with accurate depth cues. In this paper, unlike the conventional rectangular hogel based HS, efficient hexagonal hogels sampling for HS printing that enhances the volumetric visualization of reconstruction while providing rapidly generated data using inverse-directed propagation (IDP) is proposed. Specifically, an array of hexagonal hogels is sampled by a computer-generated integral imaging technique using an IDP, which acquires the full information of the 3D object prior to higher volumetric 3D reconstruction. To demonstrate the proposed approach, IDP-based hexagonal hogel sampling for HS printing is implemented, and the enhanced image quality of printed holograms is verified both by numerical simulation and in an optical experiment.

Microtomographic Analysis of a Palaeolithic Wooden Point from the Ljubljanica River.

A rare and valuable Palaeolithic wooden point, presumably belonging to a hunting weapon, was found in the Ljubljanica River in Slovenia in 2008. In order to prevent complete decay, the waterlogged wooden artefact had to undergo conservation treatment, which usually involves some expected deformations of structure and shape. To investigate these changes, a series of surface-based 3D models of the artefact were created before, during and after the conservation process. Unfortunately, the surface-based 3D models were not sufficient to understand the internal processes inside the wooden artefact (cracks, cavities, fractures). Since some of the surface-based 3D models were taken with a microtomographic scanner, we decided to create a volumetric 3D model from the available 2D tomographic images. In order to have complete control and greater flexibility in creating the volumetric 3D model than is the case with commercial software, we decided to implement our own algorithm. In fact, two algorithms were implemented for the construction of surface-based 3D models and for the construction of volumetric 3D models, using (1) unsegmented 2D images CT and (2) segmented 2D images CT. The results were positive in comparison with commercial software and new information was obtained about the actual state and causes of the deformation of the artefact. Such models could be a valuable aid in the selection of appropriate conservation and restoration methods and techniques in cultural heritage research.

Scapular Y: the forgotten radiograph in glenohumeral arthritis—novel measurement of posterior humeral head subluxation on scapular Y radiographs

BackgroundAxillary radiographs, 2-dimensional (2D) axial computed tomography (CT) scans, and 3-dimensional (3D) software are described to quantify posterior humeral head subluxation (PHHS) in patients with glenohumeral arthritis (GHOA). This study’s purpose was to compare a novel method of PHHS calculated from upright scapular Y radiographs and compare it to legacy measures of PHHS on axillary radiographs, 2D CT, and 3D CT in patients with Walch type B glenoid morphology. MethodsPatients undergoing anatomic total shoulder arthroplasty for primary GHOA with Walch B glenoids and a full series of preoperative radiographs and 2D and 3D CT scans were retrospectively identified. Three fellowship-trained shoulder surgeons independently measured the percentages of PHHS on axillary and scapular Y radiographs and axial 2D CT. PHHS on 3D CT was measured volumetrically using surgical templating software. ResultsThirty patients were identified with GHOA undergoing anatomic total shoulder arthroplasty. There were 26 type-B2 (86.7%) glenoids, 3 type-B1 (10%) glenoids, and 1 type-B3 (3.3%) glenoid. The mean PHHS value for the entire group on the scapular Y radiographs was 77.0% ± 13.8%, axillary radiographs was 77.3% ± 8.6%, 2D CT was 74% ± 5.6%, and 3D CT was 83.3% ± 6.0%. PHHS on 3D CT was 6% greater than that on scapular Y (P = .04) and axillary (P < .01) radiographs and 9% greater than that on 2D CT (P < .0001). Correlation between scapular Y PHHS and all other imaging modalities was weak (axillary radiograph, r = 0.369; 2D CT, r = 0.097; 3D CT, r = 0.134). Correlation between axillary radiograph PHHS was moderate for 2D CT (r = 0.518) and weak for 3D CT (r = 0.398). Correlation of 2D CT PHHS to volumetric 3D CT was strong (r = 0.754). Excellent inter-rater reliability for a single measure between raters was observed on scapular Y radiographs (intraclass correlation coefficient; ICC = 0.922), and moderate inter-rater reliability was observed on axillary radiographs (ICC = 0.680) and 2D CT (ICC = 0.692). ConclusionScapular Y radiographs provide a novel, reliable method to measure PHHS. The weak-to-moderate correlation between scapular Y and other imaging modalities (axillary radiographs and 2D and 3D CTs) may be related to the dynamic position of the humeral head in the supine vs. upright position. Taken along with the axillary radiograph, the scapular Y radiograph provides a more comprehensive understanding of subluxation. With an increasing focus on reducing cost, utilizing the scapular Y method provides another objective measure of PHHS. Surgeons should be aware that PHHS on volumetric 3D CT was 9% greater than that on 2D CT and 6% greater than that on axillary or scapular Y radiographs.

Property enhancement approaches of fused filament fabrication technology: A review

AbstractThe shift from rapid prototyping to rapid manufacturing using 3D printing is prominent after the development of volumetric 3D printing, multi‐material printing, and functional materials development. Fused filament fabrication (FFF) is a fast‐growing additive manufacturing technology with widespread end‐user applications. The key constraints to its growth are the lower surface and mechanical properties compared to conventional manufacturing paradigms. The goal of this review is to look at the numerous pre‐processing and post‐processing parameters for the property enhancement of FFF. Pre‐processing methods included optimization of process parameters (infill percentage, pattern, layer height, nozzle and platform temperature, raster angle and width, build orientation, and air gap) and adaptive slicing techniques. Mechanical (hot air jetting, barrel finishing, sand blasting, laser polishing, etc.), chemical (vapor smoothing, dipping, plating, and painting), and thermal (thermal annealing and normalizing) post‐processing techniques were successful in improving the mechanical strength and surface finish of fused filament fabricated parts. This paper outlines the various methodologies a FFF user could incorporate for enhancing the final finished product's properties. The potential future prospects for the development of the 3D printing sector are also examined.