Volumetric 3D Research Articles

Added value of volumetric MRI pulse sequence 3D VISTA (Volume ISotopic Turbo spin echo Acquisition) in perianal fistula depiction and characterization

PurposeDiagnosis of perianal fistula represents a challenge for surgeons. It is well known that magnetic resonance imaging (MRI) plays an important role in that. The new 3D MRI sequence VISTA (Volume ISotopic Turbo spin echo Acquisition) can improve detection and characterization of perianal fistula compared with two-dimensional (2D) sequences. The aim of the study was to compare the diagnostic performance of the new 3D MRI sequence VISTA with the widely routinely used T2 FSE pulse sequence in depiction and characterization of perianal fistula by using the contrast-enhanced (CE) 3D T1 sequence THRIVE (T1-weighted high-resolution isotropic volume examination) as a reference standard.Material and methodsForty adult patients were enrolled in this prospective study. They underwent MRI perianal region examination using routine T2 TSE and CE 3D T1 sequence THRIVE with addition of the new 3D MRI sequence VISTA. T2, 3D VISTA and (CE) 3D T1 sequence THRIVE images were evaluated by two radiologists separately for detection and characterization of perianal fistula, then comparison between of T2 and 3D VISTA sequences was done using (CE) 3D T1 sequence THRIVE as a reference. Each sequence sensitivity, specificity and accuracy were calculated by both readers.ResultsFor reader 1, the sensitivity, specificity and accuracy were 92.5%, 90.5% and 93.6% for 3D VISTA and 84.1%, 83.7% and 87.3% for T2 FSE. For reader 2, the sensitivity, specificity and accuracy were 91.5%, 92.8% and 94.8% for 3D VISTA and 82.9%, 84.5% and 86.7% for T2 FSE.ConclusionsUsing CE 3D T1 sequence THRIVE as the reference standard, 3D VISTA pulse sequence on the perianal region has better diagnostic performance in the detection and characterization of perianal fistula as compared to the routinely used T2 FSE sequence.

Radical inhibition in tomographic volumetric 3D printing for thiol-Ene photoresists: From Photorheology to printability

The introduction of tomographic volumetric 3D printing is revolutionizing the manufacturing and bioprinting landscape by enabling the rapid creation of complex three-dimensional (biological) structures with high precision down to 20 μm. Despite the recognized role of radical inhibition in volumetric 3D printing, a study of inhibition has remained elusive. Here, A comprehensive framework is presented to study the role of the widely reported radical inhibitor TEMPO in the volumetric 3D printability of a thiol-ene photocrosslinkable photoresist composed of triallyl isocyanurate (TTT) and pentaerythritol tetrakis(3-mercaptopropionate) (PETMP). Through photorheological measurements, kinetic modeling, FTIR spectroscopy, and validation via volumetric 3D printing, the relationship between inhibitor concentrations, the evolution of the shear moduli as well as the conversion as a function of light dose, and volumetric 3D printing is elucidated. The findings in this study provide a robust methodology for predicting optimal printing conditions of photoresists for tomographic volumetric 3D printing, obviating the need for extensive trial-and-error.

Volumetric 3D printing of ionic conductive elastomers for multifunctional flexible electronics

Flexible electronics based on ionic conductive elastomers (ICE) hold significant potential for applications in smart wearables, self-powered sensing, and human-computer interaction. However, current fabrication techniques constrain ICE-based ionic electronic components to simplified volumetric geometries, limiting their functionality. This work reports a volumetric 3D printing (V3DP) for fabricating flexible electronic components with excessive transparency, high conductivity, excellent thermal stability, and superior adhesion. By controlling the light dose, this printing technique enables precise modulation of the printed structures' mechanical properties. Furthermore, V3DP greatly improves the processing efficiency of high-viscosity ionic conductive liquids and makes it easier to prepare composite structures, combining different conductive mechanisms through unique overprinting. This study provides a promising strategy for preparing multifunctional, liquid-free, ionic flexible electronics, such as strain sensors and ionic-electronic triboelectric nanogenerators (iTENG).

Modern Methods of Fluorescence Nanoscopy in Biology

Optical microscopy has undergone significant changes in recent decades due to the breaking of the diffraction limit of optical resolution and the development of high-resolution imaging techniques, which are collectively known as fluorescence nanoscopy. These techniques allow researchers to observe biological structures and processes at a nanoscale level of detail, revealing previously hidden features and aiding in answering fundamental biological questions. Among the advanced methods of fluorescent nanoscopy are: STED (Stimulated Emission Depletion Microscopy), STORM (STochastic Optical Reconstruction Microscopy), PALM (Photo-activated Localization Microscopy), TIRF (Total Internal Reflection Fluorescence), SIM (Structured Illumination Microscopy), MINFLUX (Minimal Photon Fluxes), PAINT (Points Accumulation for Imaging in Nanoscale Topography) и RESOLFT (REversible Saturable Optical Fluorescence Transitions) and others. In addition, most of these methods make it possible to obtain volumetric (3D) images of the objects under study. In this review, we will look at the principles of these methods, their advantages and disadvantages, and their application in biological researches.

SonoPrint: Acoustically Assisted Volumetric 3D Printing for Composites.

Advances in additive manufacturing in composites have transformed aerospace, medical devices, tissue engineering, and electronics. A key aspect of enhancing properties of 3D-printed objects involves fine-tuning the material by embedding and orienting reinforcement within the structure. Existing methods for orienting these reinforcements are limited by pattern types, alignment, and particle characteristics. Acoustics offers a versatile method to control the particles independent of their size, geometry, and charge, enabling intricate pattern formations. However, integrating acoustics into 3D printing has been challenging due to the scattering of the acoustic field between polymerized layers and unpolymerized resin, resulting in unwanted patterns. To address this challenge, SonoPrint, an innovative acoustically assisted volumetric 3D printer is developed that enables simultaneous reinforcement patterning and printing of the entire structure. SonoPrint generates mechanically tunable composite geometries by embedding reinforcement particles, such as microscopic glass, metal, and polystyrene, within the fabricated structure. This printer employs a standing wave field to create targeted particle motifs-including parallel lines, radial lines, circles, rhombuses, hexagons, and polygons-directly in the photosensitive resin, completing the print in just a few minutes. SonoPrint enhances structural properties and promises to advance volumetric printing, unlocking applications in tissue engineering, biohybrid robots, and composite fabrication.

Digital Protection and Inheritance Path of Intangible Cultural Heritage based on Image Processing Algorithm

This research paper introduces a novel approach in the realm of digital preservation and inheritance of Intangible Cultural Heritage (ICH) through a Customized 3D Convolutional Neural Network (CNN). The core of this study lies in the development of an advanced image processing algorithm tailored to accurately recognize, categorize, and archive diverse forms of ICH, which include traditional performances, ceremonies, oral traditions, and crafts. Utilizing a volumetric 3D CNN, this paper demonstrates how complex ICH elements can be effectively captured and analyzed, overcoming the limitations of traditional 2D image processing methods. The network is trained on a comprehensive dataset of ICH imagery, ensuring sensitivity to the subtle nuances and dynamic nature of these cultural expressions. This paper highlights the algorithm’s capability in not only safeguarding the visual aspects of ICH but also in providing an interactive, digital medium for education and cultural dissemination. The proposed method shows significant promise in aiding the efforts of cultural preservationists and educators, offering a technologically advanced pathway for the protection and inheritance of the world’s rich, yet vulnerable, cultural heritage. This study sets a precedent in the interdisciplinary field of cultural heritage conservation, digital technology, and artificial intelligence, providing a scalable and effective solution for global ICH preservation initiatives.

Long-Term Prognostic Impact of Three-Dimensional Speckle-Tracking Echocardiography-Derived Left Ventricular Global Longitudinal Strain in Healthy Adults-Insights from the MAGYAR-Healthy Study.

Three-dimensional (3D) speckle-tracking echocardiography (STE) combines the advantages of STE and volumetric 3D echocardiography, which shows the left ventricle (LV) in 3D during the cardiac cycle and is also suitable for accurate strain measurements in addition to volumetric assessments using the same virtual 3D LV cast. The present study aimed to confirm the prognostic impact of 3DSTE-derived LV global longitudinal strain (GLS) in healthy adults during a 12-year follow-up period. The current study comprised 124 healthy individuals with a mean age of 31.0 ± 11.7 years (64 males) at the time of complete two-dimensional Doppler echocardiography (2DE) and 3DSTE. During a mean follow-up of 8.01 ± 4.12 years, 10 healthy individuals suffered cardiovascular events, including 2 cardiac deaths. Using ROC analysis, 3DSTE-derived LV-GLS ≥ 14.77% was found to be a significant predictor for cardiovascular event-free survival (sensitivity 70%, specificity 71%, area under the curve 76%, p = 0.007). Using 2DE, higher LV end-diastolic and end-systolic volumes, a larger LV end-systolic diameter and a lower LV ejection fraction could be detected in subjects with LV-GLS < 14.77% as compared to cases with LV-GLS ≥ 14.77%. Subjects with events had thicker interventricular septa, a larger LV mass and lower 3DSTE-derived LV-GLS and a higher ratio of cases had LV-GLS < 14.77%. From subjects with LV-GLS < 14.77%, seven individuals (18%) had events. Multivariate regression analysis identified age and LV-GLS as independent predictors of event-free survival. 3DSTE-derived LV-GLS is a strong independent predictor of cardiovascular survival in healthy adults.

Free-breathing, fat-corrected T1 mapping of the liver with stack-of-stars MRI, and joint estimation of T1, PDFF, , and .

Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat and inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition. Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T. The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps. The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, and in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.

IMG-13. PREDICTION OF PEDIATRIC MEDULLOBLASTOMA SUBGROUPS USING CLINICO-RADIOMIC ANALYSIS

Abstract BACKGROUND Pediatric medulloblastoma is an aggressive brain tumor and tailored treatment has the potential to lead to better patient outcomes. The WHO 2021 classification of medulloblastoma involves an integrated diagnosis that incorporates genetically defined characteristics, including molecular subgroups (WNT-activated, SHH-activated TP53 wildtype, SHH-activated TP53-mutant, and non-WNT/non-SHH). Clinically acquired radiology (MRI) imaging characteristics could provide a non-invasive, pre-treatment biomarker for such subgroups faster than standard methylation-based turn-around times, and for use in countries where methylation is not available. METHODS Herein, we utilize a multi-institutional dataset of multi-parametric, clinical MRIs of pediatric medulloblastoma patients from the Children’s Brain Tumor Network (median age = 8.9 years) to assess the predictive value of patient-level radiomic and clinical factors. 89 subjects with treatment-naïve T1w/T1w contrast-enhanced/T2w/FLAIR images and molecular subgroups (derived from methylation profiling or RNA sequencing) were included (SHH=18, WNT=10, non-SHH/WNT=61). Radiomic features were extracted from a radiologist-defined volumetric (3D) segmentation for each subject separately (including solid tumor, cystic, and peritumoral edema regions). Clinical variables included sex, age at diagnosis, and metastatic disease. 20 top performing features were selected based on an ANOVA between features/classes and subsequently used to train and evaluate three separate classification models based on radiomic, clinical, or clinico-radiomic features (Linear SVM; leave-one-subject-out cross-validation). RESULTS The combined clinico-radiomic model had the top performance (AUC=0.83) followed by radiomic (0.78) and clinical (0.5) for predicting SHH/WNT vs. non-SHH/WNT groups. Predictive radiomic features included intensity-based statistics (T1w, T2w, T1w-CE), texture (T2w), and morphological shape characteristics. CONCLUSIONS Our findings show potential for early prediction of molecular subgroups using baseline imaging that could lend to faster decision-making in patient treatment planning. Future work aims to evaluate the inclusion of histological characteristics for a full integrated diagnostic approach as well as assessment of prognostic value of the combined multi-omic features.

RedLionfish - fast Richardson-Lucy Deconvolution package for efficient point spread function suppression in volumetric data.

The experimental limitations with optics observed in many microscopy and astronomy instruments result in detrimental effects for the imaging of objects. This can be generally described mathematically as a convolution of the real object image with the point spread function that characterizes the optical system. The popular Richardson-Lucy (RL) deconvolution algorithm is widely used for the inverse process of restoring the data without these optical aberrations, often a critical step in data processing of experimental data. Here we present the versatile RedLionfish python package, that was written to make the RL deconvolution of volumetric (3D) data easier to run, very fast (by exploiting GPU computing capabilities) and with automatic handling of hardware limitations for large datasets. It can be used programmatically in Python/numpy using conda or PyPi package managers, or with a graphical user interface as a napari plugin.

Tuberculous spondylitis: Macromorphological and radiological studies on a skeleton from the Late Iron Age monument of Nor Armavir, Armenia

The skeleton in question derives from the Late Iron Age monument of Nor Armavir and was unearthed from burial No. 19. The deceased was buried in an unusual position. In this article, we characterize the pathological bony changes indicative of tuberculous spondylitis. The skeleton was subject to a detailed macroscopic investigation. Besides age at death estimation and sex determination, a careful palaeopathological evaluation was performed on the bone remains. In addition, volumetric (3D) computed tomography was carried out on four lumbar vertebrae (L2–5) to complement the macromorphology-based diagnosis.

Impact of spleen volume on post-allogenic hematopoietic transplant outcomes in myelofibrosis: Utility of 3D volumetrics in splenomegaly.

6558 Background: Splenomegaly is a hallmark of myelofibrosis, thought to be correlated with graft failure and worsened overall survival in transplant patients. Past studies have utilized manual spleen measurement, potentially affecting accuracy. Using 3D volume can more precisely measure spleen size. Hence, the true impact of splenomegaly on transplant outcomes remains unclear. In this retrospective study, we examined myelofibrosis patients who underwent HCT and, using 3D volumetrics, analyzed the impact of splenomegaly and volume reduction over time on post HCT outcomes. Methods: This retrospective study included 130 City of Hope myelofibrosis patients with pre HCT imaging (2004–2023). Patients were divided into pre HCT spleen volume of &gt;3000 cc and &lt;3000 cc, with &gt;3000 cc considered massive splenomegaly. Spleen volume was measured using Vitrea 3D volumetric software. For each patient, depending on imaging available, volume was measured 0-3 months pre HCT, 3-6 months, 6-9 months, and 9-12 months post HCT with corresponding volume reduction calculations. Pre HCT spleen volume was also temporally correlated with several post HCT outcomes. Results: Median age at HCT was 60 (17-75), and 95% of patients received the Fludarabine/Melphalan conditioning regimen. Median spleen volume pre HCT was 1150 cc (41-6695 cc). Sixteen patients measured &gt;3000cc, and 114 patients measured &lt;3000cc. Median spleen volume 3-6 months post HCT was 661 cc (80-1731 cc) with a median 48% volume reduction. The data suggests that majority of volume reduction occurred during this time (table). Five-year overall survival (OS) was 72.8%. Relapse was 11.0% at 1 year and 14.7% at 5 years. NRM at 5 years was 17.3%. ANC engraftment peaked at 28 days at 92.3%. Pre HCT spleen volume (&lt;1000 cc, 1000-2000 cc, &gt;2000 cc) did not have a significant impact on OS (P = 0.992), disease free survival (P = 0.783), relapse (P = 0.187), NRM (P = 0.627), or ANC Engraftment (P = 0.526). There was a statistically insignificant downward trend for platelet engraftment (P = 0.162). For patients with or without massive splenomegaly (&gt;3000cc), there was no significant effect with any of the analyzed post HCT outcomes. Conclusions: This retrospective study includes an analysis of spleen volume by 3D volumetrics, a more accurate measurement of spleen size, and whether it significantly impacts post HCT outcomes. Our data analysis demonstrates that splenomegaly, massive or not, does not significantly impact transplant outcomes for patients receiving a reduced intensity conditioning regimen.[Table: see text]

Using Unmanned Aerial Vehicles and Multispectral Sensors to Model Forage Yield for Grasses of Semiarid Landscapes

Forage yield estimates provide relevant information to manage and quantify ecosystem services in grasslands. We fitted and validated prediction models of forage yield for several prominent grasses used in restoration projects in semiarid areas. We used field forage harvests from three different sites in Northern Utah and Southern California, USA, in conjunction with multispectral, high-resolution UAV imagery. Different model structures were tested with simple models using a unique predictor, the forage volumetric 3D space, and more complex models, where RGB, red edge, and near-infrared spectral bands and associated vegetation indices were used as predictors. We found that for most dense canopy grasses, using a simple linear model structure could explain most (R2 0.7) of the variability of the response variable. This was not the case for sparse canopy grasses, where a full multispectral dataset and a non-parametric model approach (random forest) were required to obtain a maximum R2 of 0.53. We developed transparent protocols to model forage yield where, in most circumstances, acceptable results could be obtained with affordable RGB sensors and UAV platforms. This is important as users can obtain rapid estimates with inexpensive sensors for most of the grasses included in this study.

An easy-to-build, accessible volumetric 3D printer based on a liquid crystal display for rapid resin development

Additive manufacturing has revolutionized the way prototypes and one-off parts are produced, but standard additive manufacturing techniques such as material extrusion or vat photopolymerization still present various issues like high print times and defects due to the layer-by-layer nature of the print process. Computed axial lithography (CAL), a novel volumetric additive manufacturing technique, solves many of the issues associated with traditional 3D printing, like staircasing defects and long printing times. However, state of the art CAL requires complex optical setups, limiting access to a working machine, greatly reducing the pace of new material and technologies being adapted to CAL. The Liquid Crystal Display-based computed axial lithography (LCD-CAL) setup here presented keeps many of the advantages of CAL, but utilizes a single lens and an LCD for its optical setup. By moving to LCDs, the machine cost is greatly reduced, and the extremely simplified optical setup of LCD-CAL makes CAL widely accessible. To highlight the versatility of the developed LCD-CAL, we design and characterize two high-viscosity resins for CAL printing based on highly crosslinked and bio-based acrylates, respectively. This work paves the way for widespread adoption of volumetric 3D printing by making a low cost, high speed CAL printer available.

Light-field flow cytometry for high-resolution, volumetric and multiparametric 3D single-cell analysis

Imaging flow cytometry (IFC) combines flow cytometry and fluorescence microscopy to enable high-throughput, multiparametric single-cell analysis with rich spatial details. However, current IFC techniques remain limited in their ability to reveal subcellular information with a high 3D resolution, throughput, sensitivity, and instrumental simplicity. In this study, we introduce a light-field flow cytometer (LFC), an IFC system capable of high-content, single-shot, and multi-color acquisition of up to 5,750 cells per second with a near-diffraction-limited resolution of 400-600 nm in all three dimensions. The LFC system integrates optical, microfluidic, and computational strategies to facilitate the volumetric visualization of various 3D subcellular characteristics through convenient access to commonly used epi-fluorescence platforms. We demonstrate the effectiveness of LFC in assaying, analyzing, and enumerating intricate subcellular morphology, function, and heterogeneity using various phantoms and biological specimens. The advancement offered by the LFC system presents a promising methodological pathway for broad cell biological and translational discoveries, with the potential for widespread adoption in biomedical research.

Ultrafast Response Organic Photoswitch Materials and Their Application in Volumetric 3D Display.

Volumetric three-dimensional (3D) display technology based on static screens is a crucial branch of 3D displays. The essential component in volumetric 3D displays is selectively excitable display media that can generate voxels at any position. Here, we synthesized a series of organic photoswitch materials to meet the specific requirements of 3D display mediums. In these photoswitch solutions, voxels are activated ultrafast within tens of picoseconds at the intersection of two control lasers and faded rapidly within tens of milliseconds when switching light is turned off. An experimental volumetric 3D display system utilizing an organic photoswitch solution as a screen is demonstrated. The system not only achieves a dynamic 3D display but also enables 360° viewing. The volumetric 3D display system can display true 3D images without auxiliary glasses and is expected to be applicable in fields as diverse as virtual reality, medical imaging, architectural design, and military visualization.

Validation and comparison of 2D grading scales and 3D volumetric measurements for outcome assessment of bone-grafted alveolar clefts in children.

Several methods have been proposed to assess outcome of bone-grafted alveolar clefts on cone beam computed tomography (CBCT), but so far these methods have not been compared and clinically validated. To validate and compare methods for outcome assessment of bone-grafted clefts with CBCT and provide recommendations for follow-up. In this observational follow-up study, two grading scales (Suomalainen; Liu) and the volumetric bone fill (BF) were used to assess the outcome of 23 autogenous bone-grafted unilateral alveolar clefts. The mean age at bone grafting was 9 years. The volumetric BF was assessed in five vertical sections. The bone-grafted cleft outcome was based on a binary coding (success or regraft) on a clinical multidisciplinary expert consensus meeting. Grading scales and volumetric assessment were compared in relation to the bone-grafted cleft outcome (success or regraft). Reliability for the different outcome variables was analyzed with intra-class correlation and by calculating kappa values. The study had a limited sample size. Clinical CBCT acquisitions had a varying tube current and exposure time. Volumetric 3D measurements allowed for outcome assessment of bone-grafted alveolar clefts with high reliability and validity. The two grading scales showed highly reliable outcomes, yet the validity was high for the Suomalainen grading scale but low for the Liu grading scale. Volumetric 3D measurement as well as the Suomalainen grading can be recommended for outcome assessment of the bone-grafted cleft. Yet, one must always make a patient-specific assessment if there is a need to regraft.

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration.

Volumetric 3D object analyses are being applied in research fields such as structural bioinformatics, biophysics, and structural biology, with potential integration of artificial intelligence/machine learning (AI/ML) techniques. One such method, 3D Zernike moments, has proven valuable in analyzing protein structures (e.g., protein fold classification, protein-protein interaction analysis, and molecular dynamics simulations). Their compactness and efficiency make them amenable to large-scale analyses. Established methods for deriving 3D Zernike moments, however, can be inefficient, particularly when higher order terms are required, hindering broader applications. As the volume of experimental and computationally-predicted protein structure information continues to increase, structural biology has become a "big data" science requiring more efficient analysis tools. This application note presents a Python-based software package, ZMPY3D, to accelerate computation of 3D Zernike moments by vectorizing the mathematical formulae and using graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow together with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithm development. The ZMPY3D package can be installed via PyPI, and the source code is available from GitHub. Volumetric-based protein 3D structural similarity scores and transform matrix of superposition functionalities have both been implemented, creating a powerful computational tool that will allow the research community to amalgamate 3D Zernike moments with existing AI/ML tools, to advance research and education in protein structure bioinformatics. ZMPY3D, implemented in Python, is available on GitHub (https://github.com/tawssie/ZMPY3D) and PyPI, released under the GPL License.

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging.

Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisitions, and numerous studies have recently attempted to harness deep learning (DL) technology in enabling scan time reduction and image quality improvement. Various DL-based image reconstruction products allow for additional scan time reduction on top of existing accelerated acquisition methods without compromising the image quality.

Volumetric 3D analysis of cosmetic defects after clipping via mini-pterional and conventional pterional craniotomies

Volumetric 3D analysis of cosmetic defects after clipping via mini-pterional and conventional pterional craniotomies