3D Modalities Research Articles

3D versus 2D Electrolyte–Semiconductor Interfaces in Rylenediimide‐Based Electron‐Transporting Water‐Gated Organic Field‐Effect Transistors

AbstractWater‐gated organic field‐effect transistors (WGOFETs) are relevant devices for use in the fields of biosensors and biosystems. However, real applications require very stringent performance in terms of electrochemical stability and charge mobility to the organic semiconductor in contact with an aqueous environment. Here, a comparative study of two small‐molecule electron‐transporting perylenediimide semiconductors, which differ only in the N‐substituents named PDIF‐CN2 and PDI8‐CN2 is reported. The two materials present similar solid‐state arrangements but, while the PDI8‐CN2 shows a more 3D growth modality and electron mobility independent of the semiconductor layer thickness (≈10−4 cm2 V−1 s−1), the PDIF‐CN2 has an almost‐2D growth modality and the mobility increases with the semiconductor film thickness, reaching a maximum value of ≈5 × 10−3 cm2 V−1 s−1 at 30 nm. Above this thickness, the PDIF‐CN2 switches to a more 3D growth modality, and the mobility drops by one order of magnitude. XRR analysis indicates that a PDIF‐CN2 film can be modeled as a dense layered structure in which each layer is decoupled from the others due to the presence of fluorocarbon‐chains. The availability of additional pathways for charge transport from buried layers and the 2D versus 3D growth can explain the mobility dependence on the film thickness.

VP63.18: Magnetic resonance imaging versus transvaginal ultrasound with or without 3D and HDlive modalities for assessing myometrial and cervical invasion in endometrial cancer

VP63.18: Magnetic resonance imaging versus transvaginal ultrasound with or without 3D and HDlive modalities for assessing myometrial and cervical invasion in endometrial cancer

Accuracy and Reliability of Soft Tissue Landmarks Using Three-Dimensional Imaging in Comparison With Two-Dimensional Cephalometrics: A Systematic Review

Background: Concerns about the accuracy and reliability of soft tissue landmarks using two-dimensional (2D) and three-dimensional (3D) imaging. Objective: The aim of the systematic review is to estimate accuracy and reliability of soft tissue landmarks with 2D imaging and 3D imaging for orthodontic diagnosis planning and treatment planning purposes. Data Sources: Electronic database search was performed in MEDLINE via PubMed, Embase via embase.com, and the Cochrane library website. Selection Criteria: The data were extracted according to two protocols based on Centre for Evidence-Based Medicine (CEBM) critical appraisal tools. Next, levels of evidence were categorized into three groups: low, medium, and high. Data Synthesis: Fifty-five publications were found through database search strategies. A total of nine publications were included in this review. Conclusion According to the available literature, 3D imaging modalities were more accurate and reliable as compared to 2D modalities. Cone beam computed tomography (CBCT) was considered the most reliable imaging tool for soft tissues.

Joubert Syndrome Diagnosed at 16+6 Weeks Gestation and Molar Tooth Sign by 3D Modality

Joubert’s syndrome is a rare genetic disorder. It is an autosomal recessive neuro-developmental disorder involving mid and hind brain. This report describes a fetus at gestational age 16weeks+ 6 days, who presented with characteristic Molar tooth sign on the antenatal scan. This sign is a salient feature of Joubert syndrome (JS). Mostly the diagnosis of JS is made after birth. Few cases are diagnosed prenatally by ultrasound.

Gesture Recognition Based on 3D Human Pose Estimation and Body Part Segmentation for RGB Data Input

This paper presents a novel approach for dynamic gesture recognition using multi-features extracted from RGB data input. Most of the challenges in gesture recognition revolve around the axis of the presence of multiple actors in the scene, occlusions, and viewpoint variations. In this paper, we develop a gesture recognition approach by hybrid deep learning where RGB frames, 3D skeleton joint information, and body part segmentation are used to overcome such problems. Extracted from the RGB images are the multimodal input observations, which are combined by multi-modal stream networks suited to different input modalities: residual 3D convolutional neural networks based on ResNet architecture (3DCNN_ResNet) for RGB images and color body part segmentation modalities; long short-term memory network (LSTM) for 3D skeleton joint modality. We evaluated the proposed model on four public datasets: UTD multimodal human action dataset, gaming 3D dataset, NTU RGB+D dataset, and MSRDailyActivity3D dataset and the experimental results on these datasets proves the effectiveness of our approach.

Comparison of Three-Dimensional and Conventional Orthodontic Imaging Modalities for Localization of Impacted Maxillary Canines in Patients With Alveolar Cleft.

The purpose of this study was to identify which diagnostic parameters related to impacted maxillary canines can be reliably detected by the conventional orthodontic radiographic modalities and which factors need to be assessed by cone-beam computed tomography (CBCT). In this cross-sectional study, 8 orthodontists evaluated 7 parameters related to the position and anatomy of the impacted canines by means of 2-dimensional (2D) records. After 1 month, the same process was repeated by means of CBCT by the same clinicians. Qazvin University of Medical Sciences. Thirty-two patients with alveolar cleft and impacted maxillary canines who had CBCT scans, lateral cephalograms, and orthopantomographs as pretreatment records. The diagnostic accuracy of 2D and 3-dimensional (3D) radiographic modalities was compared with each other and also with the gold standard by 3 radiologists. The diagnostic accuracy of 2D and 3D imaging modalities was not significantly different regarding the mesiodistal inclination of the impacted tooth (P = .09), apex anatomy (P = .10), and mesiodistal position of the apex (P = .19). Cone-beam computed tomography had significantly higher diagnostic accuracy than conventional radiographic modalities regarding overlapping the adjacent tooth (P = .001), labio-palatal and apico-coronal position of the crown tip, and root resorption of the adjacent tooth (P = .01). The conventional orthodontic radiographic modalities were as accurate as CBCT for determination of impacted canine inclination, apex anatomy, and mesiodistal position of the apex. Cone-beam computed tomography showed higher diagnostic accuracy for other parameters.

Hepatic separation of conjoined twins: Operative technique and review of three-dimensional model utilization

BackgroundThe separation of conjoined twins is a challenging and rare operation. Recent technological advances in imaging and three-dimensional printing (3DP) have allowed for enhancements in preoperative surgical planning and intraoperative anatomical orientation for complex operations. This report aims to consolidate the current clinical evidence utilizing 3DP models as an effective tool for surgical planning of conjoined twin separation and to detail our surgical approach for complex hepatic separation and management. MethodsA literature review was conducted for conjoined twin separations with preoperative use of 3D models including age at attempted separation, operative outcome, 3D modality, and postoperative course between 1998 and 2020. We also conducted a chart review of our electronic medical record for conjoined twin separations between January 2015 and December 2019. ResultsWe report two cases of conjoined twin separation with preoperative use of 3DP models from our institution: one set in the thoracoomphaloischiopagus orientation and the other set in the thoracoomphalopagus orientation with the presence of intrahepatic vascular anomalies. The literature review produced 10 case reports of conjoined twin separation with use preoperative 3D models accounting for 17 individual separation procedures. We summarize our preoperative radiological planning, the evidence of 3DP models as an educational and preoperative tool, ideal timing for separation, and our surgical approach for complex hepatic separation. ConclusionsConjoined twin separation requires a multidisciplinary effort to address the multisystem surgical and medical needs of these patients. These complex patients require extensive preoperative imaging for planning separation, and we strongly recommend utilizing 3D printed models when possible for better surgeon understanding of complex variable anatomy. We have found numerous reports of successful conjoined twin separation using 3DP technology in preoperative planning. The use of three-dimensional printed models for preoperative assessments is an invaluable tool and is rapidly improving in fidelity. Type of studyOperative technique and case series. Level of evidenceLevel IV.

A review of Image Guided Radiation Therapy in head and neck cancer from 2009-201 - Best Practice Recommendations for RTTs in the Clinic.

Radiation therapy (RT) is beneficial in Head and Neck Cancer (HNC) in both the definitive and adjuvant setting. Highly complex and conformal planning techniques are becoming standard practice in delivering increased doses in HNC. A sharp falloff in dose outside the high dose area is characteristic of highly complex techniques and geometric uncertainties must be minimised to prevent under dosage of the target volume and possible over dosage of surrounding critical structures. CTV-PTV margins are employed to account for geometric uncertainties such as set up errors and both interfraction and intrafraction motion. Robust immobilisation and Image Guided Radiation Therapy (IGRT) is also essential in this group of patients to minimise discrepancies in patient position during the treatment course. IGRT has evolved with increased 2-Dimensional (2D) and 3-Dimensional (3D) IGRT modalities available for geometric verification. 2D and 3D IGRT modalities are both beneficial in geometric verification while 3D imaging is a valuable tool in assessing volumetric changes that may have dosimetric consequences for this group of patients. IGRT if executed effectively and efficiently provides clinicians with confidence to reduce CTV-PTV margins thus limiting treatment related toxicities in patients. Accumulated exposure dose from IGRT vary considerably and may be incorporated into the treatment plan to avoid excess dose. However, there are considerable variations in the application of IGRT in RT practice. This paper aims to summarise the advances in IGRT in HNC treatment and provide clinics with recommendations for an IGRT strategy for HNC in the clinic.

Non-invasive dynamic observation of placental vascular anastomoses in monochorionic twins: Assessment using three-dimensional sonography combined with tomographic ultrasound imaging

IntroductionThree-dimensional (3D) sonography combined with tomographic ultrasound imaging (TUI) to observe placental vascular anastomoses in monochorionic diamniotic (MCDA) twin pregnancies was evaluated. MethodsWomen with MCDA twin pregnancies at a gestational age of 16–32 weeks were enrolled in this retrospective study. Placental anastomoses were detected using two-dimensional (2D) and 3D sonography. Two-dimensional data were obtained by color and spectral Doppler and 3D data with high-definition flow within the area between twins’ umbilical cord insertions. Volume post-processing using TUI mode identified anastomoses. Anastomotic findings on ultrasound were compared with fetoscopic surgery or postnatally injected placentas for diagnostic value. Anastomoses detection was compared between the two imaging modalities. ResultsSeventy-six twin pregnancies were analyzed: 11 selective intrauterine growth restrictions (sIUGR), 10 twin-to-twin transfusion syndrome (TTTS), and 55 without complications. Seventy-one twin pregnancies had arterio-arterial (AA) anastomoses and 75 had arterio-venous (AV) anastomoses. Three-dimensional sonography combined with TUI was more sensitive (87.3%) and accurate (88.2%) in detecting AA anastomoses than 2D sonography (74.6%, 76.3%, respectively; P < 0.05), but had comparable sensitivity for AV anastomoses. The specificity of both modalities for anastomoses was 100%. The detection rate of AA anastomoses by 3D modality was (40%) TTTS vs. (87.3%) normal (P < 0.05), but comparable (90.9%) for sIUGR. The detection rates of AV anastomoses (90%, 81.8%) in TTTS and sIUGR were comparable with (87.3%) normal (P > 0.05). DiscussionThree-dimensional sonography combined with TUI highlighted placental anastomoses and may be useful for the clinical diagnosis and therapy of MCDA twin complications.

Sonographic detection of fetal abnormalities before 11 weeks of gestation.

Sonographic detection of fetal abnormalities before 11 weeks of gestation.

Speckle tracking deformation imaging to detect regional fibrosis in hypertrophic cardiomyopathy: a comparison between 2D and 3D echo modalities.

We aimed at directly comparing three-dimensional (3D) and two-dimensional (2D) deformation parameters in hypertrophic hearts and depict which may best reflect underlying fibrosis in hypertrophic cardiomyopathy (HCM), defined by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR). We included 40 HCM [54.1 ± 14.3 years, 82.5% male, maximum wall thickness (MWT) 19.3 ± 4.8 mm] and 15 hypertensive (HTN) patients showing myocardial hypertrophy (58.1 ± 15.6 years, 80% male, MWT 12.8 ± 1.4 mm) who have consecutively undergone 2D-, 3D-speckle tracking echocardiography and LGE CMR. Deformation parameters (2D and 3D) presented overall poor to moderate correlations, with 3D_longitudinal strain (LS) and 3D_circumferential strain (CS) values being constantly higher compared to 2D derivatives. By regression analysis, hypertrophy substrate (HCM vs. hypertension) and hypertrophy magnitude were the parameters to influence 2D-3D LS and CS strain correlations (R2 = 0.66, P < 0.001 and R2 = 0.5, P = 0.001 accordingly). Among segmental deformation indices, 2D_LS showed the best area under the curve [AUC = 0.78, 95% confidence intervals (CI) (0.75-0.81), P < 0.0005] to detect fibrosis, with 3D deformation parameters showing similar AUC (0.65) and 3D_LS presenting the highest specificity [93.1%, 95% CI (90.6-95.1)]. In hypertrophic hearts, 2D and 3D deformation parameters are not interchangeable, showing modest correlations. Thickness, substrate, and tracking algorithm calculating assumptions seem to induce this variability. Nevertheless, among HCM patients 2D_peak segmental longitudinal strain remains the best strain parameter for tissue characterization and fibrosis detection.

CSIOR: Circle-Surface Intersection Ordered Resampling

Triangular mesh is one of the most popular 3D modalities, which usage spans a wide variety of applications in computer vision, computer graphics and multimedia. Raw mesh surfaces generated by 3D scanning devices often suffer from mesh irregularity and also lack the implicit ordered structure that characterizes 2D images. Therefore, they are not suitable to be processed as such, especially for applications requiring fine surface analysis tasks. In this paper, we propose CSIOR, a novel mesh regularization technique exhibiting novel capabilities including (a) quasi-equilateral triangle and ordered tessellation that can accommodate non-convex shaped surfaces, (b) implicit generation of iso-geodesic contours, and (c) preservation of the object geometric properties, such as shape and surface corrugations (relief patterns). We evidence the superiority of our technique over current methods through a series of experiments performed on a variety of surfaces with relief patterns.

ELearning and Embryology: Designing an Application to Improve 3D Comprehension of Embryological Structures.

Embryology and histology are subjects that are viewed as particularly challenging by students in higher education. This negative perception is the result of many factors such as restricted access to lab facilities, lack of allocated time to these labs, and the complexity of the subject itself. One main factor that influences this viewpoint is the difficulty of grasping 3D orientation of sectioned tissues, especially regarding embryology. Attempts have been made previously to create alternative teaching methods to help alleviate these issues, but few have explored 3D visualisation. We aimed to address these issues by creating 3D embryological reconstructions from serial histology sections of a sheep embryo. These were deployed in a mobile application that allowed the user to explore the original sections in sequence, alongside the counterpart 3D model. The application was tested against a currently available eHistology programme on a cohort of life sciences graduates (n=14) through qualitative surveys and quantitative testing through labelling and orientation-based tests. The results suggest that using a 3D modality such as the one described here significantly improves student comprehension of orientation of slides compared to current methods (p=0.042). Furthermore, the developed application was deemed more interesting, useful, and usable than current eHistology tools (p<0.05). Modalities such as that developed here could therefore provide a more effective approach to learning these challenging subjects potentially increasing student engagement with embryology and histology.

Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods

We consider the problem of 3D shape reconstruction from multimodal data, given uncertain calibration parameters. Typically, 3D data modalities can come in diverse forms such as sparse point sets, volumetric slices, and 2D photos. To jointly process these data modalities, we exploit a parametric level set method that utilizes ellipsoidal radial basis functions. This method not only allows us to analytically and compactly represent the object; it also confers on us the ability to overcome calibration-related noise that originates from inaccurate acquisition parameters. This essentially implicit regularization leads to a highly robust and scalable reconstruction, surpassing other traditional methods. In our results we first demonstrate the ability of the method to compactly represent complex objects. We then show that our reconstruction method is robust both to a small number of measurements and to noise in the acquisition parameters. Finally, we demonstrate our reconstruction abilities from diverse modalities such as volume slices obtained from liquid displacement (similar to CT scans and X-rays) and visual measurements obtained from shape silhouettes as well as point clouds.

Effective approaches to three-dimensional digital reconstruction of fragmented human skeletal remains using laser surface scanning

The preservation and reconstruction of anthropological and archaeological remains has been given considerable attention in recent years, particularly within the fields of forensic science and palaeoanthropology. However, few studies have tapped the potential of using 3D technology to reconstruct, remodel and recontour remains and artefacts for the purpose of human identification. The aim of this study was to use 3D technology for the reconstruction and remodelling of fragmented and missing elements of skeletal remains. This project presents the application of three dimensional (3D) modalities to two different simulated forensic case scenarios where an attempt was made to remodel the missing element of the human cranium and reconstruction of fragmented replicated human mandible was performed. The accuracy of the reconstructed model was affirmed based on the anatomical features and digital analysis and methods for use in forensic practice are recommended.

A novel 2D and 3D multimodal approach for in-the-wild facial expression recognition

This study proposes a novel deep learning approach for the fusion of 2D and 3D modalities in in-the-wild facial expression recognition (FER). Different from other studies, we exploit the 3D facial information in in-the-wild FER. In particular, in-the-wild 3D FER dataset is not widely available; therefore, 3D facial data are constructed from available 2D datasets thanks to recent advances in 3D face reconstruction. The 3D facial geometry features are then extracted by deep learning technique to exploit the mid-level details, which provides meaningful expression for the recognition. In addition, to demonstrate the potential of 3D data on FER, the 2D projected images of 3D faces are taken as additional input to FER. These features are then jointly fused with 2D features obtained from the original input. The fused features are then classified by support vector machines (SVMs). The results show that the proposed approach achieves state-of-the-art recognition performances on Real-World Affective Faces (RAF) and Static Facial Expressions in the Wild (SFEW 2.0), and AffectNet dataset. This approach is also applied to a 3D FER dataset, i.e. BU-3DFE, to compare the effectiveness of reconstructed and available 3D face data for FER. This is the first time such a deep learning combination of 3D and 2D facial modalities is presented in the context of in-the-wild FER.

Review of the effect of 3D medical printing and virtual reality on urology training with ‘MedTRain3DModsim’ Erasmus + European Union Project

Background/aimIt is necessary to incorporate novel training modalities in medical education, especially in surgical fields, because of the limitations of cadaveric training. Traditional medical education has many drawbacks, such as residency working hour restrictions, patient safety conflicts with the learning needs, and the lack of hands-on workshops. The MedTRain3DModsim Project aimed to produce 3-dimensional (3D) medical printed models, simulations, and innovative applications for every level of medical training using novel worldwide technologies. It was aimed herein to improve the interdisciplinary and transnational approaches, and accumulate existing experience for medical education, postgraduate studies, and specialty training.Materials and methodsThis project focused on models of solid organs and the urinary system, including the kidney, prostate, ureter, and liver. With 3D medical printing, it is possible to produce a body part from inert materials in just a few hours with the standardization of medical 3D modeling.ResultsThe target groups of this project included medical students and residents, graduate students from engineering departments who needed medical education and surgical training, and medical researchers interested in health technology or clinical and surgical anatomy. ConclusionIt was also intended to develop a novel imaging platform for education and training by reevaluating the existing data using new software and 3D modalities. Therefore, it was believed that our methodology could be implemented in all related medical fields.

Interstitial Flow Recapitulates Gemcitabine Chemoresistance in A 3D Microfluidic Pancreatic Ductal Adenocarcinoma Model by Induction of Multidrug Resistance Proteins.

Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most lethal cancers due to a high chemoresistance and poor vascularization, which results in an ineffective systemic therapy. PDAC is characterized by a high intratumoral pressure, which is not captured by current 2D and 3D in vitro models. Here, we demonstrated a 3D microfluidic interstitial flow model to mimic the intratumoral pressure in PDAC. We found that subjecting the S2-028 PDAC cell line to interstitial flow inhibits the proliferation, while maintaining a high viability. We observed increased gemcitabine chemoresistance, with an almost nine-fold higher EC50 as compared to a monolayer culture (31 nM versus 277 nM), and an alleviated expression and function of the multidrug resistance protein (MRP) family. In conclusion, we developed a 3D cell culture modality for studying intratissue pressure and flow that exhibits more predictive capabilities than conventional 2D cell culture and is less time-consuming, and more scalable and accessible than animal models. This increase in microphysiological relevance might support improved efficiency in the drug development pipeline.

PVRNet: Point-View Relation Neural Network for 3D Shape Recognition

Three-dimensional (3D) shape recognition has drawn much research attention in the field of computer vision. The advances of deep learning encourage various deep models for 3D feature representation. For point cloud and multi-view data, two popular 3D data modalities, different models are proposed with remarkable performance. However the relation between point cloud and views has been rarely investigated. In this paper, we introduce Point-View Relation Network (PVRNet), an effective network designed to well fuse the view features and the point cloud feature with a proposed relation score module. More specifically, based on the relation score module, the point-single-view fusion feature is first extracted by fusing the point cloud feature and each single view feature with point-singe-view relation, then the pointmulti- view fusion feature is extracted by fusing the point cloud feature and the features of different number of views with point-multi-view relation. Finally, the point-single-view fusion feature and point-multi-view fusion feature are further combined together to achieve a unified representation for a 3D shape. Our proposed PVRNet has been evaluated on ModelNet40 dataset for 3D shape classification and retrieval. Experimental results indicate our model can achieve significant performance improvement compared with the state-of-the-art models.

Adding Depth to Cephalometric Analysis: Comparing Two- and Three-Dimensional Angular Cephalometric Measurements.

Lateral cephalometric radiographs (LCR) have been the standard tool used for cephalometric analysis in craniofacial surgery. Over the past decade, a three-dimensional (3D) revolution in cephalometric analysis and surgical planning has been underway. To date, research has not validated whether cephalometric measurements taken from two-dimensional (2D) and 3D data sources are equivalent and interchangeable. The authors sought to compare angular cephalometric measurements taken with 2D and 3D modalities. Sixty-two head CT scans (36 females, 26 males) with an average age of 63 ± 20 years were studied. Twelve cephalometric angular measurements were taken from 3D reconstructed skulls using the software package Mimics 19.0 (Materialize; Leuven, Belgium). These same facial angles were measured from 2D lateral cephalograms reconstructed from the original CT scans using Dolphin 11.9. Measurements taken with both techniques were compared for agreement using a paired t test. Intra-class correlation coefficient assessment was used to determine inter-rater reliability. Statistical significance was set at P < 0.05. Five of the 12 angular measurements (SNA, SNB, MP-FH, U1-SN, and U1-L1) demonstrated statistically significant differences (P < 0.05) between the 2D and 3D analyses. All of these differences were less than the standard deviations for the respective measure. The differences between angular cephalometric values obtained from 2D LCRs and 3D CT reconstructions are small. This supports the practices of using 2D and 3D cephalometric data interchangeably in most applications. Clinicians must be selective in which measures they employ to maximize accuracy and care must be taken when measuring dental inclination with lateral cephalograms.