3D Visualization Method Research Articles

Visual Edge Feature Detection and Guidance under 3D Interference: A Case Study on Deep Groove Edge Features for Manufacturing Robots with 3D Vision Sensors

For manufacturing robots equipped with 3D vision sensors, the presence of environmental interference significantly impedes the precision of edge extraction. Existing edge feature extraction methods often enhance adaptability to interference at the expense of final extraction precision. This paper introduces a novel 3D visual edge detection method that ensures greater precision while maintaining adaptability, capable of addressing various forms of interference in real manufacturing scenarios. To address the challenge, data-driven and traditional visual approaches are integrated. Deep groove edge feature extraction and guidance tasks are used as a case study. R-CNN and improved OTSU algorithm with adaptive threshold are combined to identify groove features. Subsequently, a scale adaptive average slope sliding window algorithm is devised to extract groove edge points, along with a corresponding continuity evaluation algorithm. Real data is used to validate the performance of the proposed method. The experiment results show that the average error in processing interfered data is 0.29mm, with an average maximum error of 0.54mm, exhibiting superior overall performance and precision compared to traditional and data-driven methods.

Research on the 3D Visualization Method of Web-Based Seismic Wave CT Results and the Application in Underground Caverns

Research on the 3D Visualization Method of Web-Based Seismic Wave CT Results and the Application in Underground Caverns

Real-time ultrasound AR 3D visualization toward better topological structure perception for hepatobiliary surgery.

Ultrasound serves as a crucial intraoperative imaging tool for hepatobiliary surgeons, enabling the identification of complex anatomical structures like blood vessels, bile ducts, and lesions. However, the reliance on manual mental reconstruction of 3D topologies from 2D ultrasound images presents significant challenges, leading to a pressing need for tools to assist surgeons with real-time identification of 3D topological anatomy. We propose a real-time ultrasound AR 3D visualization method for intraoperative 2D ultrasound imaging. Our system leverages backward alpha blending to integrate multi-planar ultrasound data effectively. To ensure continuity between 2D ultrasound planes, we employ spatial smoothing techniques to interpolate the widely spaced ultrasound planes. A dynamic 3D transfer function is also developed to enhance spatial representation through color differentiation. Comparative experiments involving our AR visualization of 3D ultrasound, alongside AR visualization of 2D ultrasound and 2D visualization of 3D ultrasound, demonstrated that the proposed method significantly reduced operational time(110.25 ± 27.83s compared to 292 ± 146.63s and 365.25 ± 131.62s), improved depth perception and comprehension of complex topologies, contributing to reduced pressure and increased personal satisfaction among users. Quantitative experimental results and feedback from both novice and experienced physicians highlight our system's exceptional ability to enhance the understanding of complex topological anatomy. This improvement is crucial for accurate ultrasound diagnosis and informed surgical decision-making, underscoring the system's clinical applicability.

Edge-protected IDW-based DEM detail enhancement and 3D terrain visualization

Terrain visualization plays an important role in Digital Twin, geology, environmental science, and exploration. Generating 3D visualization results by the Digital Elevation Model (DEM) is an effective method. However, existing DEM 3D visualization methods generally lack sufficient detail to obtain good visual effects. Therefore, we propose a novel DEM detail enhancement and 3D terrain visualization method. Our method is based on the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm and the edge-protected Inverse Distance Weighted (IDW) algorithm, and achieves 3D visualization of DEM data through a workflow of converting the raw DEM data into an image, followed by enhancement and detail optimization of the image, and finally converting the image into triangular meshes. The edge-protected IDW algorithm performs IDW interpolation optimization based on the Canny edge detector combined with the Otsu threshold optimization method to detect edge areas, achieving smooth transitions in the edge areas. Experiments show that our method generates detail-rich 3D visualization results after enhancing original DEM data. We also conducted an ablation study to provide a side-by-side comparison of each step. Our method can be further applied to many tasks, such as virtual reality, GIS, and geological exploration.

A Novel Method for Regional Prospecting Based on Modern 3D Graphics

During comprehensive regional prospecting evaluation and delineation of a prospecting target area, various types of data, including geological, geophysical, geochemical, and remote sensing, are usually integrated and visualized in a unified spatial environment, making it convenient for researchers to identify mineralization. To maximize the precision of spatial boundaries, the maps traditionally used in prospecting are predominantly in vector formats. However, with the rapid development of modern real-time 3D graphics and computer cartography technology, raster maps can now provide richer detail representation compared to traditional vector maps while still meeting the precision requirements. In this paper, we present a new GPU-based 3D visualization method for spatial data, specifically, two types of bitmap-based maps called dynamic geochemical maps (DGMs) and interactive geological maps (IGMs). A novel software system implementing this method was developed and has been applied in the exploration of the Zhunuo ore district, Tibet, showing large advantages over traditional vector maps.

Utilizing augmented reality for reconstruction of fractured, fragmented and damaged craniofacial remains in forensic anthropology

Forensic anthropologists are often confronted with human remains that have been damaged due to trauma, fire, or postmortem taphonomic alteration, frequently resulting in the fracture and fragmentation of skeletal elements. The augmented reality (AR) technology introduced in this paper builds on familiar 3D visualization methods and utilizes them to make three dimensional holographic meshes of skeletal fragments that can be manipulated, tagged, and examined by the user. Here, CT scans, neural radiance fields (NeRF) artificial intelligence software, and Unreal Engine production software are utilized to construct a three-dimensional holographic image that can be manipulated with HoloLens™ technology to analyze the fracture margin and reconstruct craniofacial elements without causing damage to fragile remains via excessive handling. This allows forensic anthropologists a means of assessing aspects of the biological profile and traumatic injuries without risking further damage to the skeleton. It can also be utilized by students and professional anthropologists to practice refitting before reconstructing craniofacial fragments if refitting is necessary. Additionally, the holographic images can be used to explain complicated concepts in a courtroom without the emotional response related to using bony elements as courtroom exhibits.

3D magnetic seed localization for augmented reality in surgery

PurposeFor tumor resection, surgeons need to localize the tumor. For this purpose, a magnetic seed can be inserted into the tumor by a radiologist and, during surgery, a magnetic detection probe informs the distance to the seed for localization. In this case, the surgeon still needs to mentally reconstruct the position of the tumor from the probe’s information. The purpose of this study is to develop and assess a method for 3D localization and visualization of the seed, facilitating the localization of the tumor.MethodsWe propose a method for 3D localization of the magnetic seed by extending the magnetic detection probe with a tracking-based localization. We attach a position sensor (QR-code or optical marker) to the probe in order to track its 3D pose (respectively, using a head-mounted display with a camera or optical tracker). Following an acquisition protocol, the 3D probe tip and seed position are subsequently obtained by solving a system of equations based on the distances and the 3D probe poses.ResultsThe method was evaluated with an optical tracking system. An experimental setup using QR-code tracking (resp. using an optical marker) achieves an average of 1.6 mm (resp. 0.8 mm) 3D distance between the localized seed and the ground truth. Using a breast phantom setup, the average 3D distance is 4.7 mm with a QR-code and 2.1 mm with an optical marker.ConclusionTracking the magnetic detection probe allows 3D localization of a magnetic seed, which opens doors for augmented reality target visualization during surgery. Such an approach should enhance the perception of the localized region of interest during the intervention, especially for breast tumor resection where magnetic seeds can already be used in the protocol.

Feasibility and accuracy of a real-time depth-based markerless navigation method for hologram-guided surgery

BackgroundTwo-dimensional (2D) medical visualization techniques are often insufficient for displaying complex, three-dimensional (3D) anatomical structures. Moreover, the visualization of medical data on a 2D screen during surgery is undesirable, because it requires a surgeon to continuously switch focus. This switching focus problem also results in extensive use of intraoperative radiation to gain additional insights for a 3D configuration. The use of augmented reality (AR) has the potential to overcome these problems, for instance by using markers on target points that are aligned with the AR solution. However, placing markers for a precise virtual overlay are time-costly, always have to be visible within the field of view and disrupt the surgical workflow. In this study, we developed ARCUS, a depth-based, markerless AR navigation system, which overlays 3D virtual elements onto target body parts to overcome the limitations of 2D medical visualization techniques.Methods and resultsIn a phantom study, our markerless ARCUS system was evaluated for accuracy and precision by comparing it to a Quick Response (QR) code-based AR registration method. The evaluation involved measuring the Euclidean distance between target points on a 3D-printed face and their corresponding points on the virtual overlay using a robotic arm for precise measurements. Correlations between the measuring points provided by our markerless system and the actual measuring points on the 3D-print were high, with promising consistent Euclidean distances between the 3D points and the virtual points generated by both our markerless system and the Vuforia QR Code system. We also show two clinical examples of ex vivo case studies on cadaveric human specimens where our markerless ARCUS system could be applicable to.ConclusionThe markerless AR navigation system holds strong potential as a 3D visualization method in clinical settings. While both ARCUS and the Vuforia QR code-based method fell short of meeting the surgical threshold of a 2 mm offset, our markerless system demonstrated promising features such as instant registration, markerless operation, and potential compatibility with non-rigid structures. Its automated virtual overlay onto target body parts offers significant advantages, paving the way for investigations into future clinical use.

3D visualization and printing: An "Anatomical Engineering" trend revealing underlying morphology via innovation and reconstruction towards future of veterinary anatomy.

The amalgamation of veterinary anatomy, technology and innovation has led to development of latest technological advancement in the field of veterinary medicine, i.e., three-dimensional (3D) imaging and reconstruction. 3D visualization technique followed by 3D reconstruction has been proven to enhance non-destructive 3D visualization grossly or microscopically, e.g., skeletal muscle, smooth muscle, ligaments, cartilage, connective tissue, blood vessels, nerves, lymph nodes, and glands. The core aim of this manuscript is to document non-invasive 3D visualization methods being adopted currently in veterinary anatomy to reveal underlying morphology and to reconstruct them by 3D softwares followed by printing, its applications, current challenges, trends and future opportunities. 3D visualization methods such as MRI, CT scans and micro-CT scans are utilised in revealing volumetric data and underlying morphology at microscopic levels as well. This will pave a way to transform and re-invent the future of teaching in veterinary medicine, in clinical cases as well as in exploring wildlife anatomy. This review provides novel insights into 3D visualization and printing as it is the future of veterinary anatomy, thus making it spread to become the plethora of opportunities for whole veterinary science.

Efficient 3D imaging and pathological analysis of the human lymphoma tumor microenvironment using light-sheet immunofluorescence microscopy.

Rationale: The composition and spatial structure of the lymphoma tumor microenvironment (TME) provide key pathological insights for tumor survival and growth, invasion and metastasis, and resistance to immunotherapy. However, the 3D lymphoma TME has not been well studied owing to the limitations of current imaging techniques. In this work, we take full advantage of a series of new techniques to enable the first 3D TME study in intact lymphoma tissue. Methods: Diverse cell subtypes in lymphoma tissues were tagged using a multiplex immunofluorescence labeling technique. To optically clarify the entire tissue, immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO+), clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) and stabilization to harsh conditions via intramolecular epoxide linkages to prevent degradation (SHIELD) were comprehensively compared with the ultimate dimensional imaging of solvent-cleared organs (uDISCO) approach selected for clearing lymphoma tissues. A Bessel-beam light-sheet fluorescence microscope (B-LSFM) was developed to three-dimensionally image the clarified tissues at high speed and high resolution. A customized MATLAB program was used to quantify the number and colocalization of the cell subtypes based on the acquired multichannel 3D images. By combining these cutting-edge methods, we successfully carried out high-efficiency 3D visualization and high-content cellular analyses of the lymphoma TME. Results: Several antibodies, including CD3, CD8, CD20, CD68, CD163, CD14, CD15, FOXP3 and Ki67, were screened for labeling the TME in lymphoma tumors. The 3D imaging results of the TME from three types of lymphoma, reactive lymphocytic hyperplasia (RLN), diffuse large B-cell lymphoma (DLBCL), and angioimmunoblastic T-cell lymphoma (AITL), were quantitatively analyzed, and their cell number, localization, and spatial correlation were comprehensively revealed. Conclusion: We present an advanced imaging-based method for efficient 3D visualization and high-content cellular analysis of the lymphoma TME, rendering it a valuable tool for tumor pathological diagnosis and other clinical research.

Evaluation of 3D geovisualization of volumetric geospatial data in the form of horizontal planes using selected software

The main motivation of the paper is to provide an overview of 3D geovisualization capabilities of selected software and present selected methods of visualization of 3D geospa-tial data using horizontal planes. The paper is focused on the evaluation of software and meth-ods for the visualization of thematic geospatial data with an emphasis on visual analysis in 3D. Meteorological data of the ALADIN forecast model were used to create visualizations. The first part focuses on the evaluation of selected software in terms of 3D visualization capa-bilities. The evaluation encompasses software tools such as geographic information systems, web-based solutions, and 3D computer graphics software. The result is a comparison of these software in terms of suitability for visual analysis in 3D, for example in terms of spatial data support, 3D visualizations, or analytical functions. The second part is focused on the presen-tation of four methods of 3D data visualization using horizontal planes for visualizing thematic data, including single plane, multiple planes without transparency, multiple planes with trans-parency, and multiple planes overlay. These methods were evaluated based on graphical var-iables, both the original ones defined by Jacques Bertin and those added later by other car-tographers, to achieve the most optimal visual analysis in 3D. The article concludes by high-lighting the advantages and disadvantages of the different visualization methods, and their specifics in terms of graphical variables. The importance of interactive visualization environ-ments for fully utilizing the potential of these methods is emphasized.

The Application of Image Graphic Visual Communication Techniques in Artistic Creation from the Perspective of Digital Media

Abstract This paper first studies the connection between computer image graphics and visual communication and analyses the use of image graphics and visual communication technology in artistic creation. It denoises the image and proposes a method for enhancing blurred light images based on visual communication technology. It also outlines the process of applying computer graphic image processing technology to the field of visual communication design. Then VR technology is combined with visual communication and art design, a 3D image virtual reconstruction system based on visual communication effects is designed, and a 3D image graphical visual art creation method is constructed. Finally, we analyzed the impact of virtual reality art creation in terms of aesthetic evaluation, experience impact, and satisfaction. The results showed that the simple main effect of expression was significant when intensity was perceived for three different types of emotions, as shown by the simple effect analysis of expression on the type of emotion, which were FA(2, 160)=43.05, p<0.001, FB(2, 160)=10.45, p<0.001, and FA*B(2, 160)=12.36, p <0.001. This study complements the research on virtual aesthetics and, at the same time, provides a new research direction for the diversified and integrated development of art.

INHIBISI EKSTRAK DAUN SIRIH MERAH TERHADAP LIPASE PANKREAS SEBAGAI ANTIOBESITAS SECARA IN SILICO

A Obesity triggers the emergence of various degenerative diseases, such as stroke, heart disease, type 2 diabetes, and insulin resistance. Pancreatic lipase inhibitors are anti-obesity drug agents that work by inhibiting pancreatic lipase enzymes. This study aims to search and predict the inhibitory activity of pancreatic lipase from the active compound of red betel leaf. The research began with virtual screening of 60 test ligands, prediction of ligand stability and toxicity, validation method of molecular docking, molecular docking, 2D and 3D visualization. The results showed that benzethonium octyloxyacetate, salicylic acid beta-D-glucopyranosyl ester, and anthocyanins had the best potential in inhibiting pancreatic lipase enzymes based on virtual screening, ligand stability, ligand toxicity, energy affinity, number of hydrogen bonds with active site, bond distance, and constants inhibition (Ki). Benzethonium octyloxyacetate has an affinity value of -8 kcal/mol, has a hydrogen bond interaction on the His349 residue on the active site of the pancreatic lipase receptor (6KSM) with a bond distance of 2,94 Å and Ki value of 1,347 μM

Three-dimensional Visualization of Overhead Transmission Lines with UAV-LiDAR Point Cloud Data

Three-dimensional reconstruction and visualization of overhead transmission lines is an important foundation for grid operation and maintenance management. This paper introduces a 3D visualization method of transmission lines based on the unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) technology, which includes four steps: (I) Using UAV-LiDAR technology to obtain 3D point cloud data of power lines; (II) Using the least-squares method with loss minimization constraints to fit the point cloud data of the power lines, to obtain the accurate fitting function of the power lines; (III) Using the spline interpolation algorithm to draw the 3D scene in the 3D vectors, and combine with building information modeling (BIM) model to construct the transmission line visualization scene. The method of this paper can improve the authenticity and reliability of transmission line simulation and provide technical support for the digital platform of power grid management.

The intrinsic mode activation and evolution in fiber splicing based on 3D refractive index profile characterization

Fiber fusion splicing tremendously affects the modal stability, insertion loss and transmission quality of the optical fiber communication systems. Especially, in the few-mode fibers, a tiny dissatisfactory fiber splicing operation may lead to a big modal perturbation or unexpected mode coupling. In this paper, we propose a 3D refractive index profile visualization method to demonstrate the mode activation and evolution in fiber fusion splicing. A refractive index profile measuring instrument is established and applied to detect the 3D refractive index profile deformation caused by the fiber splicing. Then, based on the measured values of 3D refractive index profile, the mode activation is analyzed for fiber splicing between a single-mode fiber and a two-mode fiber with different core-offset distance. Results show that the mode begins to tremble with a core-offset of 4 μm and the high-order modes are effectively activated at the core-offset of 7 μm. The basic theoretical model and experiment results provide a profound support in almost all kinds of fiber splicing operation, mode interference construction and mode coupling modulation. Additionally, the method can be expanded to the research on fiber cleaving and bending.

3D DC inversion, visualization, and processing of dense time-lapse data in fine domains applied to remediation monitoring

Using electrical direct-current (DC) data to monitor the subsurface is an efficient solution for observing changes in the shallow subsurface. Recent advances in instrumentation enable the acquisition of large data sets over 3D domains in a reasonable time. We have developed an inversion approach capable of handling very large amounts of data on a finely discretized domain, which enables the delivery of time-lapse results of dense data acquisitions in a feasible time and with high resolution. To spatially represent 3D DC data, a visualization method is introduced that formally generalizes the focusing point of a common pseudosection in three dimensions. The method physically describes subsurface properties for simple geologic scenarios. In addition, the focusing points are used to design our 3D measuring protocol. We develop a DC data processing scheme using the full time-domain induced polarization (IP) waveform data by applying two novel physics-based criteria that enforce charge buildup and steady state. These criteria are tested on DCIP field data and find that 98% of the filtered DC data have less than 1% relative error. The 3D visualization method and inversion algorithm are evaluated on synthetic scenarios of 3D DC dense borehole data. Then, we indicate time-lapse results of DC field data acquired at an uncontaminated site where a remediation agent was injected at depth. The data are acquired with a new DCIP instrument capable of measuring dense data sets at fast acquisition times. Accounting for DCIP data acquisition, signal processing, and 3D inversion of 60,000 DC measurements, our results locate in 14 h the 3D spread of the remediation agent in a [Formula: see text] volume.

Online temperature-monitoring technology for grain storage: a three-dimensional visualization method based on an adaptive neighborhood clustering algorithm.

Post-harvest quality assurance is a crucial link between grain production and end users. It is essential to ensure that grain does not deteriorate due to heating during storage. To visualize the temperature distribution of a grain pile, the present study proposed a three-dimensional (3D) temperature field visualization method based on an adaptive neighborhood clustering algorithm (ANCA). The ANCA-based visualization method contains four calculation modules. First, discrete grain temperature data, obtained by sensors, are collected and interpolated using back propagation (BP) neural networks to model the temperature field. Then a new adaptive neighborhood clustering algorithm is applied to divide interpolation data into different categories by combining spatial characteristics and spatiotemporal information. Next, the Quickhull algorithm is used to compute the boundary points of each cluster. Finally, the polyhedrons determined by boundary points are rendered into different colors and are constructed in a 3D temperature model of the grain pile. The experimental results show that ANCA is much better than the DBSCAN and MeanShift algorithms on compactness (around 95.7% of tested cases) and separation (approximately 91.3% of tested cases). Moreover, the ANCA-based visualization method for grain pile temperatures has a shorter rendering time and better visual effects. This research provides an efficient 3D visualization method that allows managers of grain depots to obtain temperature field information for bulk grain visually in real time to help them protect grain quality during storage. © 2023 Society of Chemical Industry.

Three-Dimensional Visualization of Long-Range Atmospheric Transport of Crop Pathogens and Insect Pests

Some of the most devastating crop diseases and insect pests can be transmitted by wind over extremely long distances. These low-probability but high-impact events can have severe consequences for crop production and food security by causing epidemic outbreaks or devastating insect infestations in previously uninfected geographic areas. Two prominent examples that have recently caused substantial damage to agricultural production are novel strains of wheat rusts and desert locust swarm infestations. Whilst quantitative estimates of long-range atmospheric transport events can be obtained using meteorological transport simulations, the exact characteristics of three-dimensional spatiotemporal dynamics of crop pathogen transport and insect flight on extremely large spatial scales, over entire regions and continents, remain largely unknown. Here, we investigate the feasibility and usefulness of new advanced geospatial data visualization methods for studying extremely long-distance airborne transmission of crop pathogens and insect pests. We combine field surveillance data and a Lagrangian Particle Dispersion Model with novel techniques from computer graphics to obtain, for the first time, detailed three-dimensional visual insights into airborne crop pathogen and insect pest transport on regional and continental scales. Visual insights into long-distance dispersal of pests and pathogens are presented as a series of short 3D movies. We use interactive three-dimensional visual data analysis for explorative examination of long-range atmospheric transport events from a selection of outbreak and infestation sites in East Africa and South East Asia. The practical usefulness of advanced 3D visualization methods for improving risk estimates and early warning is discussed in the context of two operational crop disease and insect pest management systems (for wheat rusts and desert locusts). The tools and methods introduced here can be applied to other pathogens, pests, and geographical areas and can improve understanding of risks posed to agricultural production by crop disease and insect pest transmission caused by meteorological extreme events.

Research on the three-dimensional visual management and control for marine intelligent mould bed based on digital twin

ABSTRACT Mould bed is crucial for supporting the ship subsection and controlling its deformation during shipbuilding. However, its visualisation and control process intelligence are often inadequate, leading to reduced accuracy and efficiency in ship subsection construction. Aiming at the problem, a three-dimensional (3D) visual monitoring method for the marine intelligent mould bed is proposed based on digital twin, and the overall framework of the management and control system is designed. Meanwhile, a fuzzy PID control principle optimised by the genetic algorithm is proposed to better control the deformation of the ship subsection. On this basis, the verification of the developed system is carried out based on the physical intelligent mould bed, and the 3D visual management and control of the marine intelligent mould bed are realised. It provides a foundation for improving the accuracy and efficiency of ship subsection construction.

Abstract P4-02-29: A 3D Visualization Method for Breast Cancer Surgeons and Patients

Abstract Background: Surgical oncologists currently rely on 2D image slices, such as those from mammograms, to assess the locations and extents of their patients’ breast cancer tumors. In order to accurately evaluate the potential success of various surgical options, a surgeon must mentally translate these 2D images into more realistic, 3D image to visualize breast and tumor morphologies. For a patient without the same experience, it is even more difficult to imagine the true, 3D shape, size and location of their tumor and to participate fully in decision-making and surgical planning. Since the type of surgery chosen (nipple-sparing versus skin-sparing, mastectomy versus lumpectomy), and its ultimate clinical and cosmetic consequences, depends on not only a surgeon’s accurate pre-operative assessment, but also on the patient’s understanding; a method of clear, precise, 3D visualization in the clinic would represent a significant advancement. Methods: Using DCE-MRI as input, we developed TumorSight (TSi) to provide surgical oncologists with an accurate, 3D representation of a patient’s breast tissue and tumor, and to allow computation of useful metrics, such as the tumor-to-breast volume ratio and distance to surgically useful anatomical landmarks such as the nipple. TSi was used to create 3D models of breast cancer patient tumor using MRIs from the SimBioSys Virtual TumorBank which currently houses thousands of patients. Results: After creating the models, labels for tumor, as well as skin, chest wall, nipple, adipose tissue, glandular tissue, and vasculature were created. After tumor segmentation validation studies (of 49 patients) were completed, the median absolute volumetric error was 0.32 and the median maximum Hausdorff distance was 17.72mm. From these representations, we determine whether the tumor is monocentric, multifocal or diffuse, compute the tumor volume-to-breast volume ratio, and measure the distance of closest approach between the tumor and the nipple. In addition, by adding a margin to the tumor and computing the volume within a convex boundary containing the tumor+margin, TSi provides a pre-operative estimate of the extirpative volume and its fraction of the total breast volume. Conclusion: The ability to visualize, in 3D, a tumor’s location and distribution in the breast, and to accurately measure important metrics such as tumor-to-nipple distance, multifocality, and tumor-to-breast volume, are critical to surgical planning in breast cancer. To assist in this planning, TSi provides a surgeon and their patient with a three-dimensional breast and tumor representation and reports measurements of key features of interest. Citation Format: Amanda Parker, Tyler M. Earnest, Arda Pekis, Vignesh Kannan, Joseph Peterson, John A. Cole, Anuja K. Antony, Daniel Cook. A 3D Visualization Method for Breast Cancer Surgeons and Patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-02-29.