3D Color Research Articles

A Color- and Geometric-Feature-Based Approach for Denoising Three-Dimensional Cultural Relic Point Clouds.

In the acquisition process of 3D cultural relics, it is common to encounter noise. To facilitate the generation of high-quality 3D models, we propose an approach based on graph signal processing that combines color and geometric features to denoise the point cloud. We divide the 3D point cloud into patches based on self-similarity theory and create an appropriate underlying graph with a Markov property. The features of the vertices in the graph are represented using 3D coordinates, normal vectors, and color. We formulate the point cloud denoising problem as a maximum a posteriori (MAP) estimation problem and use a graph Laplacian regularization (GLR) prior to identifying the most probable noise-free point cloud. In the denoising process, we moderately simplify the 3D point to reduce the running time of the denoising algorithm. The experimental results demonstrate that our proposed approach outperforms five competing methods in both subjective and objective assessments. It requires fewer iterations and exhibits strong robustness, effectively removing noise from the surface of cultural relic point clouds while preserving fine-scale 3D features such as texture and ornamentation. This results in more realistic 3D representations of cultural relics.

The virtual staining method by quantitative phase imaging for label free lymphocytes based on self-supervised iteration cycle-consistent adversarial networks.

Quantitative phase imaging (QPI) provides 3D structural and morphological information for label free living cells. Unfortunately, this quantitative phase information cannot meet doctors' diagnostic requirements of the clinical "gold standard," which displays stained cells' pathological states based on 2D color features. To make QPI results satisfy the clinical "gold standard," the virtual staining method by QPI for label free lymphocytes based on self-supervised iteration Cycle-Consistent Adversarial Networks (CycleGANs) is proposed herein. The 3D phase information of QPI is, therefore, trained and transferred to a kind of 2D "virtual staining" image that is well in agreement with "gold standard" results. To solve the problem that unstained QPI and stained "gold standard" results cannot be obtained for the same label free living cell, the self-supervised iteration for the CycleGAN deep learning algorithm is designed to obtain a trained stained result as the ground truth for error evaluation. The structural similarity index of our virtual staining experimental results for 8756 lymphocytes is 0.86. Lymphocytes' area errors after converting to 2D virtual stained results from 3D phase information are less than 3.59%. The mean error of the nuclear to cytoplasmic ratio is 2.69%, and the color deviation from the "gold standard" is less than 6.67%.

A simple approach to start Mamyshev oscillator at 1030 nm utilizing a saturable absorber mirror

We demonstrate a simple method to start Yb fiber Mamyshev oscillator by adding a saturable absorber mirror (SAM) in an optical path at a bandpass filter reflection. At first, to achieve the starting of Mamyshev oscillator using SAM, by injecting a seed pulse from outside the cavity, an output coupling, a transmitted central wavelength between offset bandpass filters, and a pump LD power are explored to start the Mamyshev oscillator. Then, preserving the above-mentioned three parameters in the cavity, we exchange a fiber-cabled mounted SAM for the seed pulse output FC/APC connector. After that, the Mamyshev oscillator immediately started by turning on the pump LD. To understand the starting dynamics of this approach, we capture the pulse resolved spectrum in an initial stage of the pulse formation of Mamyshev oscillator by time-stretch spectroscopy. Before starting Mamyshev oscillator, a signature of the Q-switch pulse is observed in the 2D color plot imaging of the pulse-resolved single-shot spectrum. When a strong amplified spontaneous emission is input to SAM, a Q-switch pulse is created, and then this Q-switch pulse circulates in the cavity. This Q-switching pulse plays a role in the seed pulse to start the Mamyshev oscillating. We believe this simple approach is one of the efficient techniques for starting the Mamyshev oscillator.

NILUT: Conditional Neural Implicit 3D Lookup Tables for Image Enhancement

3D lookup tables (3D LUTs) are a key component for image enhancement. Modern image signal processors (ISPs) have dedicated support for these as part of the camera rendering pipeline. Cameras typically provide multiple options for picture styles, where each style is usually obtained by applying a unique handcrafted 3D LUT. Current approaches for learning and applying 3D LUTs are notably fast, yet not so memory-efficient, as storing multiple 3D LUTs is required. For this reason and other implementation limitations, their use on mobile devices is less popular. In this work, we propose a Neural Implicit LUT (NILUT), an implicitly defined continuous 3D color transformation parameterized by a neural network. We show that NILUTs are capable of accurately emulating real 3D LUTs. Moreover, a NILUT can be extended to incorporate multiple styles into a single network with the ability to blend styles implicitly. Our novel approach is memory-efficient, controllable and can complement previous methods, including learned ISPs. Code at https://github.com/mv-lab/nilut

Colorizing Monochromatic Radiance Fields

Though Neural Radiance Fields (NeRF) can produce colorful 3D representations of the world by using a set of 2D images, such ability becomes non-existent when only monochromatic images are provided. Since color is necessary in representing the world, reproducing color from monochromatic radiance fields becomes crucial. To achieve this goal, instead of manipulating the monochromatic radiance fields directly, we consider it as a representation-prediction task in the Lab color space. By first constructing the luminance and density representation using monochromatic images, our prediction stage can recreate color representation on the basis of an image colorization module. We then reproduce a colorful implicit model through the representation of luminance, density, and color. Extensive experiments have been conducted to validate the effectiveness of our approaches. Our project page: https://liquidammonia.github.io/color-nerf.

Gender Tapestry: gender classification as color assignation

AbstractGender Tapestry is a multi-stage interactive AI art project, challenging traditional gender classification systems. This project diverges from binary approaches by recognizing the individuality of the gender experience and expression. This paper draws parallels to the ways color perception differs amongst people and how gender is also experienced in different ways due to lived experiences. Gender Tapestry uses a multi-label classification system, with predictions extending across six gender categories, with a custom RGB color generated based on the outcomes. Participants receive binary images of their face in their personalized colors and styles, while their uploaded photos contribute to a live Generative Adversarial Network training process. This work was created in response to the very binary representations of gender in AI and the lack of representation for genders outside of the binary. The culmination is an evolving mosaic artwork, incorporating all users' custom colors, illustrating gender as a fluid construct. The mosaic gains in complexity as more images are added and more colors enter the mix, creating a community artwork on gender as a 3D color spectrum. This work contributes to the discourse on diversity and inclusion in AI, emphasizing the fluidity of gender and fostering unconventional artistic representations.

MEFF – A model ensemble feature fusion approach for tackling adversarial attacks in medical imaging

Adversarial attacks pose a significant threat to deep learning models, specifically medical images, as they can mislead models into making inaccurate predictions by introducing subtle distortions to the input data that are often imperceptible to humans. Although adversarial training is a common technique used to mitigate these attacks on medical images, it lacks the flexibility to address new attack methods and effectively improve feature representation. This paper introduces a novel Model Ensemble Feature Fusion (MEFF) designed to combat adversarial attacks in medical image applications. The proposed model employs feature fusion by combining features extracted from different DL models and then trains Machine Learning classifiers using the fused features. It uses a concatenation method to merge the extracted features, forming a more comprehensive representation and enhancing the model's ability to classify classes accurately. Our experimental study has performed a comprehensive evaluation of MEFF, considering several challenging scenarios, including 2D and 3D images, greyscale and colour images, binary classification, and multi-label classification. The reported results demonstrate the robustness of using MEFF against different types of adversarial attacks across six distinct medical image applications. A key advantage of MEFF is its capability to incorporate a wide range of adversarial attacks without the need to train from scratch. Therefore, it contributes to developing a more diverse and robust defence strategy. More importantly, by leveraging feature fusion and ensemble modelling, MEFF enhances the resilience of DL models in the face of adversarial attacks, paving the way for improved robustness and reliability in medical image analysis.

Multi-wavelength structured light based on metasurfaces for 3D imaging

Abstract Structured light projection provides a promising approach to achieving fast and non-contact three-dimensional (3D) imaging. The resolution is a crucial index that represents security and accuracy in applications such as face recognition and robot vision. It depends on the density of dots in the projection. However, further improving the density of dots in the current system must be at the cost of speed or volume. Here, an all-dielectric ultra-thin metasurface is designed and fabricated to project a multi-wavelength dot array. The density of dots is improved because projected dots with different wavelengths fill the gaps with each other. The experimental results demonstrate that the multi-wavelength projection improves the resolution of 3D imaging. Furthermore, the multi-wavelength system is beneficial to measuring a surface with varying colors. The approach has the potential to achieve a new generation of high-resolution systems for tiny fluctuations and colorful 3D imaging in dark environments.

Colorful 3D Reconstruction and an Extended Depth of Field for a Monocular Biological Microscope Using an Electrically Tunable Lens.

This paper presents a monocular biological microscope with colorful 3D reconstruction and an extended depth of field using an electrically tunable lens. It is based on a 4f optical system with an electrically tunable lens at the confocal plane. Rapid and extensive depth scanning while maintaining consistent magnification without mechanical movement is achieved. We propose an improved Laplacian operator that considers pixels in diagonal directions to provide enhanced fusion effects and obtain more details of the object. Accurate 3D reconstruction is achieved using the shape-from-focus method by tuning the focal power of the electrically tunable lens. We validate the proposed method by performing experiments on biological samples. The 3D reconstructed images obtained from the biological samples match the actual shrimp larvae and bee antenna samples. Two standard gauge blocks are used to evaluate the 3D reconstruction performance of the proposed method. The experimental results show that the extended depth of fields are 120 µm, 240 µm, and 1440 µm for shrimp larvae, bee tentacle samples, and gauge blocks, respectively. The maximum absolute errors are -39.9 μm and -30.6 μm for the first and second gauge blocks, which indicates 3D reconstruction deviations are 0.78% and 1.52%, respectively. Since the procedure does not require any custom hardware, it can be used to transform a biological microscope into one that effectively extends the depth of field and achieves highly accurate 3D reconstruction results, as long as the requirements are met. Such a microscope presents a broad range of applications, such as biological detection and microbiological diagnosis, where colorful 3D reconstruction and an extended depth of field are critical.

Application of virtual reality technology in second language classroom teaching in colleges and universities

The design and implementation of teachers’ classroom teaching strategies is the key to the success of second language classroom teaching. In order to improve the quality of second-language classroom teaching in universities and enhance the interactivity in the teaching process, the application of virtual reality technology in second-language classroom teaching in universities is studied. Firstly, an integrated ware platform is designed for second language classroom teaching in universities, which consists of an integrated ware library and a database. Then virtual reality technology is used to design an integrated ware library within the platform and collect information such as various teaching media resources designed in the classroom teaching content into the integrated ware library; Utilize 3DS Max software in virtual reality technology to construct three-dimensional models of teaching scenes and entities; Choose to use linear difference method to render 3D model colors; From a visual perspective, enhance the realism of the rendered model through image enhancement technology and color contrast enhancement technology. According to the functions of the physical object, various interactive events are added to the created teaching scene and the three-dimensional model of the entity and stored in the integrable ware library to achieve panoramic roaming of the second language classroom teaching scene in universities. The experimental results show that the teaching platform designed by this method can accurately construct three-dimensional models of teaching scenes and objects with good visual effects, providing users with a more realistic sensory experience and effectively improving students’ mastery of teaching content.

A Comparison of Colour Doppler Ultrasound and 2D Ultrasound as Promising Prediction Methods for the Treatment effect of Patients with Advanced Cervical Cancer.

A number of studies have evaluated the effect of colour Doppler ultrasound in patients with cervical cancer. This study aims to evaluate the efficacy of colour Doppler ultrasound and two-dimensional ultrasound of monitoring patients with cervical cancer. Colour Doppler ultrasound (Experimental group) and two-dimensional ultrasound (Control group) are used to monitor cervical cancer and assess the treatment effects. PFS, CI, HR, DCR, ORR, PR, SD, PD, ROD, sensitivity, and specificity, accuracy between the two groups were collected and analyzed. A total of 50 patients are included in this study, and the results show that PFS (Experimental group (EG) 5.8±2.2 versus Control group (CG) 6.1±2.6), CI (EG 20% versus CG 16%), HR (EG0.31±0.18 versus CG 0.36±0.21), DCR (EG 80% versus CG 84%), ORR(EG 28% versus CG 36%), PR (EG 16% versus CG 20%), SD (EG 48% versus CG 56%), PD (EG 12% versus CG 16%) (EG 12% versus CG 16%), ROD(EG 44% versus CG 52%) between the two groups are >0.05, and the values of sensitivity (EG 75.6% versus CG 40.2%), specificity (EG 78.4% versus CG 43.3%), and accuracy(EG 80.5% versus CG 41.4%) between the two groups are<0.05. Both Colour Doppler ultrasound and two-dimensional ultrasound are effective methods to evaluate the efficacy of concurrent chemo-radiotherapy in patients with cervical cancer.

ACCURACY EVALUATION OF AUTOMATIC SEGMENTATION IN BIOMEDICAL IMAGES: 3D SPATIAL MAPPING OF SEGMENTATION ERRORS

Currently implemented accuracy metrics in open-source libraries for segmentation by supervised machine learning are typically one-dimensional scores [1]. While extremely relevant to evaluate applicability in clinics, anatomical location of segmentation errors is often neglected.This study aims to include the three-dimensional (3D) spatial information in the development of a novel framework for segmentation accuracy evaluation and comparison between different methods.Predicted and ground truth (manually segmented) segmentation masks are meshed into 3D surfaces. A template mesh of the same anatomical structure is then registered to all ground truth 3D surfaces. This ensures all surface points on the ground truth meshes to be in the same anatomically homologous order. Next, point-wise surface deviations between the registered ground truth mesh and the meshed segmentation prediction are calculated and allow for color plotting of point-wise descriptive statistics. Statistical parametric mapping includes point-wise false discovery rate (FDR) adjusted p-values (also referred to as q-values).The framework reads volumetric image data containing the segmentation masks of both ground truth and segmentation prediction. 3D color plots containing descriptive statistics (mean absolute value, maximal value,…) on point-wise segmentation errors are rendered. As an example, we compared segmentation results of nnUNet [2], UNet++ [3] and UNETR [4] by visualizing the mean absolute error (surface deviation from ground truth) as a color plot on the 3D model of bone and cartilage of the mean distal femur.A novel framework to evaluate segmentation accuracy is presented. Output includes anatomical information on the segmentation errors, as well as point-wise comparative statistics on different segmentation algorithms. Clearly, this allows for a better informed decision-making process when selecting the best algorithm for a specific clinical application.

ECMR 4-07 - Direct Assessment of Atrioventricular Valves Using Color Overlay and 2D Magnitude Images: A Comparison with Grayscale Analysis

ECMR 4-07 - Direct Assessment of Atrioventricular Valves Using Color Overlay and 2D Magnitude Images: A Comparison with Grayscale Analysis

The Use of 3D Scanning and 3D Color Printing Technologies for the Study and Documentation of Late Bronze Age Pottery from East-Central Greece

The Use of 3D Scanning and 3D Color Printing Technologies for the Study and Documentation of Late Bronze Age Pottery from East-Central Greece

An acid-chromic luminescent lanthanide metallogel for time-dependent information encryption and anti-counterfeiting.

Luminescent materials with dynamic color transformation demonstrate significant potential in advanced information encryption and anti-counterfeiting. In this study, we designed multi-color luminescent lanthanide metallogels featuring time-dependent color transformation. These materials are based on Förster resonance energy transfer (FRET) platforms, facilitating cascade energy transfer from the ligand 4,4',4''-[1,3,5-benzenetriyltris (carbonylimino)]trisbenzoic acid (H3L) to Tb3+ ions and subsequently to Sulforhodamine 101. The emission color of the gels can be readily adjusted by the introduction of HCl, transitioning from initial green, yellow, light red, and red hues to blue, violet, pink, and deep red, respectively. Importantly, the color change in these gels is time-dependent, controlled by the hydrolysis time of glucono-δ-lactone, which modulates the luminescence intensity of H3L, Tb3+, and Sulforhodamine 101. Exploiting these characteristics, we developed methods for information encryption utilizing 3D color codes and anti-counterfeiting flower patterns. These patterns undergo time-dependent transformations, generating a series of 3D codes and flower patterns that can only be recognized in a predetermined manner. These findings highlight the promising application of lanthanide metallogels in advanced information protection strategies.

Using Computer Vision and Artificial Intelligence to Track the Healing of Severe Burns.

Burn care management includes assessing the severity of burns accurately, especially distinguishing superficial partial-thickness burns from deep partial-thickness burns, in the context of providing definitive, downstream treatment. Moreover, the healing of the wound in the subacute care setting requires continuous tracking to avoid complications. Artificial intelligence (AI) and computer vision (CV) provide a unique opportunity to build low-cost and accessible tools to classify burn severity and track changes in wound parameters, both in the clinic by physicians and nurses and asynchronously in the remote setting by the patient themselves. Wound assessments can be achieved by AI-CV using the principles of image-guided therapy using high-quality 2D color images. Wound parameters can include wound 2D spatial dimension and the characterization of wound color changes, which demonstrates physiological changes such as the presentation of eschar/necrotic tissue, pustulence, granulation tissue, and scabbing. Here we present the development of AI-CV-based Skin Abnormality Tracking Algorithm pipeline. Additionally, we provide the results on a single localized burn tracked for a 6-week period in the clinic and an additional 2-week period of home monitoring.

Achieving Multicolor Emitting of Antimony-Doped Indium-Based Halide Perovskite via Monovalent Metal Induced Phase Engineering.

Lead-free metal halide perovskites have attracted attention because of their excellent optical properties and nontoxicity. Here, we report the synthesis of Sb3+-doped indium halide perovskite Cs2InCl5·H2O:Sb3+ by an improved solution coprecipitation method. The treatment of the Sb3+-doped indium halide perovskite with selected monovalent cation halides led to Cs2MInCl6 (Ag+, K+, Na+) in different crystal structures or phases. Sb3+ has an isolated ns2 electron, and Sb3+-doped metal halide acts as the luminescence center and exhibits bright broadband emission that originated from self-trapped excitons. Under UV light excitation, these phosphors with different crystal structures emitted multicolored luminescence ranging from blue, green, yellow, and red depending on whether or not or which monovalent metal ion was used. The phosphor samples were used to print high-resolution 2D color barcodes for security and anticounterfeiting applications. The study presented here provides a new approach for the design and synthesis of lead-free metal halide perovskites with different crystal structures and unique optical properties.

Three-dimensional quantification of mandibular asymmetries in Caucasian adult patients with different sagittal and vertical skeletal patterns. A cone beam study using 3D segmentation and mirroring procedures

IntroductionAn accurate identification of mandibular asymmetries is required by modern orthodontics and orthognathic surgery to improve diagnosis and treatment planning of such deformities. Although craniofacial deformities are very frequent pathologies, some types of asymmetries can be very difficult to assess without the proper diagnostic tools. The purpose of this study was to implement the usage of three-dimensional (3D) segmentation procedures to identify asymmetries at the mandibular level in adult patients with different vertical and sagittal patterns where the asymmetries could go unnoticed at the observational level.MethodsThe study sample comprised 60 adult patients (33 women and 27 men, aged between 18 and 60 years). Subjects were divided into 3 sagittal and vertical skeletal groups. CBCT images were segmented, mirrored and voxel-based registered with reference landmarks using ITK-SNAP® and 3DSlicer® software’s. 3D surface models were constructed to evaluate the degree of asymmetry at different anatomical levels.ResultsThere was a degree of asymmetry, with the left hemimandible tending to contain the right one (0.123 ± 0.270 mm (CI95% 0.036–0.222; p < 0.001). Although the subjects under study did not present significant differences between mandibular asymmetries and their sagittal or vertical skeletal pattern (p = 0.809 and p = 0.453, respectively), a statistically significant difference has been found depending on the anatomical region (p < 0.001; CI95%=1.020–1.021), being higher in the condyle, followed by the ramus and the corpus.ConclusionsAlthough mandibular asymmetries cannot be correlated with vertical and sagittal skeletal patterns in symmetric patients, knowledge about 3D segmentation procedures and color maps can provide valuable information to identify mandibular asymmetries.

Caries Detection in Primary Teeth Using Intraoral Scanners Featuring Fluorescence: Protocol for a Diagnostic Agreement Study.

Digital methods that enable early caries identification can streamline data collection in research and optimize dental examinations for young children. Intraoral scanners are devices used for creating 3D models of teeth in dentistry and are being rapidly adopted into clinical workflows. Integrating fluorescence technology into scanner hardware can support early caries detection. However, the performance of caries detection methods using 3D models featuring color and fluorescence in primary teeth is unknown. This study aims to assess the diagnostic agreement between visual examination (VE), on-screen assessment of 3D models in approximate natural colors with and without fluorescence, and application of an automated caries scoring system to the 3D models with fluorescence for caries detection in primary teeth. The study sample will be drawn from eligible participants in a randomized controlled trial at the Royal Children's Hospital, Melbourne, Australia, where a dental assessment was conducted, including VE using the International Caries Detection and Assessment System (ICDAS) and intraoral scan using the TRIOS 4 (3Shape TRIOS A/S). Participant clinical records will be collected, and all records meeting eligibility criteria will be subject to an on-screen assessment of 3D models by 4 dental practitioners. First, all primary tooth surfaces will be examined for caries based on 3D geometry and color, using a merged ICDAS index. Second, the on-screen assessment of 3D models will include fluorescence, where caries will be classified using a merged ICDAS index that has been modified to incorporate fluorescence criteria. After 4 weeks, all examiners will repeat the on-screen assessment for all 3D models. Finally, an automated caries scoring system will be used to classify caries on primary occlusal surfaces. The agreement in the total number of caries detected per person between methods will be assessed using a Bland-Altman analysis and intraclass correlation coefficients. At a tooth surface level, agreement between methods will be estimated using multilevel models to account for the clustering of dental data. Automated caries scoring of 3D models was completed as of October 2023, with the publication of results expected by July 2024. On-screen assessment has commenced, with the expected completion of scoring and data analysis by March 2024. Results will be disseminated by the end of 2024. The study outcomes may inform new practices that use digital models to facilitate dental assessments. Novel approaches that enable remote dental examination without compromising the accuracy of VE have wide applications in the research environment, clinical practice, and the provision of teledentistry. Australian New Zealand Clinical Trials Registry ACTRN12622001237774; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384632. DERR1-10.2196/51578.

Three-dimensional representation of the Vita Toothguide 3D-Master: An in vivo clinical study.

The Vita Toothguide 3D-Master (Vita Zahnfabrik) is considered the dental shade guide in which the three dimensions of color - lightness, hue, and chroma - are most well-ordered in the CIELAB color space. No research has yet explored how well the Vita Toothguide 3D-Master is ordered in the 3D color space by recording color coordinates in vivo. To evaluate the spatial color distribution of the Vita Toothguide 3D-Master's lightness, chroma, and hue groups and its 26 physical shade tabs. The dental color (L*, C*, h°, a*, and b* color coordinates) of a healthy maxillary central incisor was recorded for 1361 participants (aged between 18 and 89 years) using a Vita Easyshade Compact spectrophotometer (Vita Zahnfabrik). The R 2.7.2. statistics program was used to create the visual representations. The five lightness levels are those that are best distributed in the color space, in relation to the L* coordinates, followed by the chroma group and, finally, the hue group. The 5M1, 5M2, and 5M3 physical shade tabs are situated at a greater distance apart from the other tabs in the color space. The Vita Toothguide 3D-Master's 26 physical shade tabs are satisfactorily distributed in three-dimensional space, although strict mathematical criteria are not followed. The natural dental shades that fall lower on the lightness scale are the most poorly represented by the physical shade tabs. Darker teeth are poorly represented by the Vita Toothguide 3D-Master's physical shade tabs. The spatial distribution of dental shade guides needs to be improved to ensure they provide homogeneous coverage of the entire chromatic spectrum corresponding to natural teeth. This would help reduce the errors inherent to the subjective visual color selection process.