3D Imaging System Research Articles

A Novel Three-Dimensional Imaging System Based on Polysaccharide Staining for Accurate Histopathological Diagnosis of Inflammatory Bowel Diseases.

Background & AimsTissue-clearing and three-dimensional (3D) imaging techniques aid clinical histopathological evaluation; however, further methodological developments are required before use in clinical practice.MethodsWe sought to develop a novel fluorescence staining method based on the classical periodic acid-Schiff stain. We further attempted to develop a 3D imaging system based on this staining method and evaluated whether the system can be used for quantitative 3D pathological evaluation and deep learning–based automatic diagnosis of inflammatory bowel diseases.ResultsWe successfully developed a novel periodic acid–FAM hydrazide (PAFhy) staining method for 3D imaging when combined with a tissue-clearing technique (PAFhy-3D). This strategy enabled clear and detailed imaging of the 3D architectures of crypts in human colorectal mucosa. PAFhy-3D imaging also revealed abnormal architectural changes in crypts in ulcerative colitis tissues and identified the distributions of neutrophils in cryptitis and crypt abscesses. PAFhy-3D revealed novel pathological findings including spiral staircase-like crypts specific to inflammatory bowel diseases. Quantitative analysis of crypts based on 3D morphologic changes enabled differential diagnosis of ulcerative colitis, Crohn’s disease, and non-inflammatory bowel disease; such discrimination could not be achieved by pathologists. Furthermore, a deep learning–based system using PAFhy-3D images was used to distinguish these diseases The accuracies were excellent (macro-average area under the curve = 0.94; F1 scores = 0.875 for ulcerative colitis, 0.717 for Crohn’s disease, and 0.819 for non-inflammatory bowel disease).ConclusionsPAFhy staining and PAFhy-3D imaging are promising approaches for next-generation experimental and clinical histopathology.

Human Motion Tracking Using 3D Image Features with a Long Short-Term Memory Mechanism Model-An Example of Forward Reaching.

Human motion tracking is widely applied to rehabilitation tasks, and inertial measurement unit (IMU) sensors are a well-known approach for recording motion behavior. IMU sensors can provide accurate information regarding three-dimensional (3D) human motion. However, IMU sensors must be attached to the body, which can be inconvenient or uncomfortable for users. To alleviate this issue, a visual-based tracking system from two-dimensional (2D) RGB images has been studied extensively in recent years and proven to have a suitable performance for human motion tracking. However, the 2D image system has its limitations. Specifically, human motion consists of spatial changes, and the 3D motion features predicted from the 2D images have limitations. In this study, we propose a deep learning (DL) human motion tracking technology using 3D image features with a deep bidirectional long short-term memory (DBLSTM) mechanism model. The experimental results show that, compared with the traditional 2D image system, the proposed system provides improved human motion tracking ability with RMSE in acceleration less than 0.5 (m/s2) X, Y, and Z directions. These findings suggest that the proposed model is a viable approach for future human motion tracking applications.

Comparison of surgical outcomes between 3-dimensional and 2-dimensional laparoscopy of ovarian cyst (LOOC): a randomised controlled trial

The purpose of this study was to compare the surgical outcomes and efficacy of 3-dimensional (3D) versus 2-dimensional (2D) imaging systems for the treatment of ovarian cyst. A total of 46 patients undergoing a laparoscopic ovarian cystectomy were randomly assigned to either the 3D or 2D laparoscopy group. The primary outcome measure was the operative blood loss. The secondary outcome measure was visually induced motion sickness (VIMS), task efficacy during laparoscopy, and postoperative complication. There were no differences in baseline demographics between the two groups. The operative blood loss was significantly smaller in the 3D groups (28.7 ± 11.6 mL) than in the 2D groups (46.5 ± 24.4 mL) (p = .012). VIMS score was significantly higher in the 3D groups than the 2D groups (p < .001). 3D laparoscopy was superior to 2D in terms of the task efficacy of ovarian cyst enucleation (p < .001), adhesiolysis or dissection (p < .001), and ovarian suturing (p = .008). None of the patients in both groups developed operative complications. In conclusion, a 3D imaging system showed a more favourable surgical outcome and improved task efficacy than 2D in laparoscopic ovarian cystectomy. However, 3D laparoscopy tends to cause more frequent VIMS in surgeons. Impact statement What is already known on this subject? Several studies examining the possible benefits and drawbacks of a 3D imaging system versus 2D in laparoscopic surgery have brought about conflicting results. However, there have been few studies comparing the surgical outcomes of 3D and 2D laparoscopic ovarian cystectomy. What do the results of this study add? 3D laparoscopy showed favourable surgical outcomes and improved task efficacy than 2D laparoscopy in ovarian cystectomy. What are the implications of these findings for clinical practice and/or further research? More complex procedures, such as suturing and adhesiolysis, might be easier to perform with 3D laparoscopy than with 2D laparoscopy. Therefore, further large studies of 3D gynaecologic laparoscopy with different complexities and for surgeons with different surgical skills are needed.

A 2D imaging system for mapping luminescence-depth profiles for rock surface dating

Spatially resolved optically stimulated luminescence (OSL) offers a means for rapid assessment of dose distributions in retrospective dosimetry and geochronology. Until recently, OSL imaging systems have largely been restricted to measurements of millimetre scale samples; this approach is not well suited for applications where the physical process of interest operates on centimetre scale (e.g., depth dependent trap eviction in exposed rocks, sediment mixing in soils, attenuation of gamma radiation, etc.). Here we describe and demonstrate the Risø Luminescence Imager - an electron multiplying charge-coupled device (EMCCD) based imaging system for measuring infrared photoluminescence (IRPL) and infrared stimulated luminescence (IRSL) from centimetre scale samples. While these signals specifically arise from feldspar, the stimulation and detection configuration may be modified to suit other target materials/dosimeters. We characterise the stability and reproducibility of the system through IRPL and IRSL measurements from a large (∼4 × 5 cm) heterogeneous rock sample, and a slice of K-feldspar mineral. Finally, we present examples of suitable applications, including the reconstruction of luminescence-depth profiles from IRPL and IRSL images, and reconstruction of IRSL decay curves. Measurement of luminescence-depth profiles with high resolution using 2D imaging using the Risø Luminescence Imager is expected to improve our understanding of the trap emptying mechanisms (kinetics) in rocks. This system also opens new avenues for the development of field imaging instrumentation and provides opportunity to study feldspar luminescence in relation to its geochemistry.

Accurate stereo vision system calibration with chromatic concentric fringe patterns.

Camera calibration is used to determine the intrinsic and extrinsic parameters of a 3D imaging system based on structured light. Traditional methods like chessboard and circular dots usually employ an intensity-based feature point detection procedure, and are susceptible to noise, image contrast, and image blur. To address these issues, we proposed an active calibration method to accurately detect the centers of chromatic concentric fringe patterns (CCFP). Specifically, we first acquired the circular phase using a phase analysis algorithm, then extracted nine phase contours from the circular phase for the corresponding subpixel center coordinates using an ellipse fitting algorithm, and precisely calculated the final center with their weighted sum. We ran a simulation and evaluated the impacts of different degrees of Gaussian blur and noise on the calibrated parameters. The simulation demonstrates that our approach is more robust to noise and blur than previous ones, and our approach yields a higher calibration accuracy. Moreover, we carried out a comparison experiment to evaluate the performance of our method. It showed that the reprojection error can be reduced by at least 10% in the out-of-focus condition (i.e., the target is beyond the working distance of the camera) and the 3D reconstruction accuracy can be improved by nearly 10%.

Optical to Planar X-ray Mouse Image Mapping in Preclinical Nuclear Medicine Using Conditional Adversarial Networks.

In the current work, a pix2pix conditional generative adversarial network has been evaluated as a potential solution for generating adequately accurate synthesized morphological X-ray images by translating standard photographic images of mice. Such an approach will benefit 2D functional molecular imaging techniques, such as planar radioisotope and/or fluorescence/bioluminescence imaging, by providing high-resolution information for anatomical mapping, but not for diagnosis, using conventional photographic sensors. Planar functional imaging offers an efficient alternative to biodistribution ex vivo studies and/or 3D high-end molecular imaging systems since it can be effectively used to track new tracers and study the accumulation from zero point in time post-injection. The superimposition of functional information with an artificially produced X-ray image may enhance overall image information in such systems without added complexity and cost. The network has been trained in 700 input (photography)/ground truth (X-ray) paired mouse images and evaluated using a test dataset composed of 80 photographic images and 80 ground truth X-ray images. Performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and Fréchet inception distance (FID) were used to quantitatively evaluate the proposed approach in the acquired dataset.

Detection of the 3D temperature characteristics of maize under water stress using thermal and RGB-D cameras

Global warming and water resource shortage greatly influence the crop growth and negatively affect the crop yield. Breeding water–stress resistant crop varieties is one of the effective ways to handle this problem. The surface temperatures of the crop are essential for assessing their water stress resistance. Thermal imaging has been widely used to acquire the crop surface temperatures. However, most studies focus on 2D measurement. A 3D thermal imaging system is designed, and a method is developed by using the thermal and RGB-D data to acquire 3D thermal information of maize under water stress conditions. First, thermal and RGB-D cameras were used to collect the thermal and color images, and depth data of maize at the jointing stage and the thermal and color images were processed to extract the edge images of maize. Second, the KAZE feature was selected to register the edge images. Testing results showed that the KAZE feature has better performance than the SURF and BRISK features in the thermal and color image registration of maize. On the basis of the thermal and color image registration, the depth data of maize were assigned with temperature values. Third, the depth data of maize were further processed with denoising, maize extraction, amplification, smoothing, and temperature correction steps to improve the data qualities. Finally, the crop water stress index and canopy–air temperature difference values of each point were calculated. The results demonstrated that the system and the proposed method can effectively detect the water stress characteristics of maize in 3D, which can be combined with the morphological traits of leaves to synthetically analyze the water stress resistance of the crop.

Comparison of 2D 4K vs. 3D HD laparoscopic imaging systems using a pelvitrainer model: a randomized controlled study

Laparoscopic surgery provides well-known benefits, but it has technological limitations. Depth perception is particularly crucial, with three-dimensional (3D) imaging being superior to two-dimensional (2D) HD imaging. However, with the introduction of 4K resolution monitors, 2D rendering is capable of providing higher-quality visuals. Therefore, this study aimed to compare 3D HD and 2D 4K imaging using a pelvitrainer model. Eight experts and 32 medical students were performing the same four standardized tasks using 2D 4K and 3D HD imaging systems. Task completion time and the number of errors made were recorded. The Wilcoxon test and mixed-effects models were used to analyze the results. Students were significantly faster in all four tasks when using the 3D HD perspective. The median difference ranged from 18 s in task 3 (P < 0.003) up to 177.5 s in task 4 (P < 0.001). With the exception of task 4, students demonstrated significantly fewer errors in all tasks involving 3D HD imaging. The experts’ results confirmed these findings, as they were also faster in all four tasks using 3D HD, which was significant for task 1 (P < 0.001) and task 4 (P < 0.006). The expert group also achieved better movement accuracy using the 3D HD system, with fewer mistakes made in all four tasks, which was significant in task 4 (P < 0.001). Participants in both groups achieved better results with the 3D HD imaging system than with the 2D 4K system. The 3D HD image system should be used when available. Trial registration: this trial is registered at research registry under the identifier researchregistry6852.

Influence of Marker Number and Position on Accuracy of Breast Measurement With Three-Dimensional Camera.

The VECTRA H1 three-dimensional (3D) imaging system (Canfield Scientific, Parsippany, NJ) enables easy 3D image construction and measurement. Although the number and positions of markers on the skin for image synthesis might affect accuracy of measurements, few studies have mentioned the possibility. This study investigated the accuracy and reproducibility of distance measurements using VECTRA H1, focusing on the number and positions of markers. A total of 3, 5, or 7 markers were attached to a female breast model including lateral markers 6 cm from the midline and photographed with VECTRA. Five markers were configured in more two ways, with the lateral markers either positioned 3 cm outside the midline (narrow interval) or 9 cm outside the midline (wide interval). 3D models were created three times under each condition, for a total of 15 models. Differences (measurement error) between measured values on 3D models and actual measured values were verified for six distances, such as distance between the nipples. The average difference was 11.1 mm with 3 markers (95% confidence interval (CI), 4.38-17.7 mm, p = 0.0028). In comparison, average difference was -0.395 mm (-0.866 to 0.0763 mm, p = 0.095) with 5 markers, and 0.139 mm (-0186 to 0.465 mm, p = 0.379) with 7 markers, all less than 1 mm. Average difference with narrow interval 5 markers was larger than one with wide interval. In 3D imaging of the breast using VECTRA H1, distance measurements offering clinically satisfactory accuracy can be made by setting appropriate marker conditions. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Video-assisted thoracic surgery sleeve resection and bronchoplasty using 3D imaging system: its safety and efficacy

BackgroundVideo-assisted thoracic surgery sleeve resection with bronchial anastomosis or bronchoplasty is a technically demanding procedure. Three-dimensional endoscopic surgery has been reported to be helpful in decreasing operation time and improving spatial perception with less surgical errors, but there have been rare reports about relatively difficult thoracoscopic procedures utilizing 3D thoracoscope. We performed this study to evaluate early clinical outcomes of thoracoscopic sleeve resection and bronchoplasty utilizing 3D thoracoscope.MethodsData from a total of 36 patients who underwent thoracoscopic sleeve lobectomy or bronchoplasty at our institution from December 2015 to October 2017 were retrospectively reviewed. Three-port approach with one utility incision was used with a 10 mm, 30° three-dimensional thoracoscope. Twenty-three patients (81%) were male, and mean age was 65.9 ± 9.4 years. Fourteen patients (38.9%) underwent sleeve resection with bronchial anastomosis, 22 (61.1%) underwent wedge or simple bronchoplasty, and one patient received concomitant PA procedure. Bronchial anastomosis sites were not covered with viable tissue flaps.ResultsThere was no (0%) suture needle injury from spatial misperception during bronchoplasty or sleeve anastomosis. There was no (0%) operative mortality. The pathologic report revealed squamous cell carcinoma (63.9%), adenocarcinoma (19.4%), carcinoid (6.9%), adenosquamous carcinoma (3.4%), and sarcomatoid carcinoma (2.8%). One (2.8%) late mortality was due to systemic recurrence of sarcomatoid carcinoma. There was no (0.0%) anastomotic failure. The mean number of dissected lymph nodes were 27.4 ± 13.2, and mean operation time was 216.8 ± 60.0 min. Median postoperative 24-h drain amount was 315 mL. Median chest tube days and hospital days were 4 and 6, respectively. Two patients (5.6%) had complications greater than Clavien-Dindo grade II—one case of ARDS, and the other case of a delayed bronchopleural fistula.ConclusionsThoracoscopic sleeve resection and bronchoplasty utilizing HD 3D thoracoscope is a safe and effective procedure with excellent early clinical outcomes. Further investigation for long-term outcomes will be needed.

Two-channel 3D range geometry compression with primitive depth modification

Modern computing and imaging technologies have allowed for many recent advances to be made in the field of 3D range imaging: range data can now be acquired at speeds much faster than real-time, with sub-millimeter precision. However, these benefits come at the cost of an increased quantity of data being generated by 3D range imaging systems, potentially limiting the number of applications that can take advantage of this technology. One common approach to the compression of 3D range data is to encode it within the three color channels of a traditional 24-bit RGB image. This paper presents a novel method for the modification and compression of 3D range data such that the original depth information can be stored within, and recovered from, only two channels of a traditional 2D RGB image. Storage within a traditional image format allows for further compression to be realized via lossless or lossy image compression techniques. For example, when JPEG 80 is used to store the encoded output image, this method achieves an 18.2% reduction in file size when compared to a similar three-channel, image-base compression method, with only a corresponding 0.17% reduction in global reconstruction accuracy.

Fine detection technology of rock mass structure based on borehole acousto-optic combined measurement

Aiming at the problem of rock mass structure fine detection, a solution idea of synchronous data acquisition based on acoustic scanning technology and borehole panoramic image technology is proposed. Based on the omni-directional acoustic pulse reflection sequence data and panoramic optical borehole image, the problem of difficult calculation of typical borehole structure scale and extended azimuth positioning is solved. A 3D modeling and data visualization optimization scheme of borehole rock mass structure based on full pulse acoustic scanning data and forward-looking borehole optical image is formed. By combining the acoustic scanning characteristics of section and the optical image characteristics of rock wall, the extraction technology of borehole rock mass structural characteristic parameters is formed. The 3D imaging and characteristic parameter extraction technology system of borehole rock mass structure is formed, which is applied to the actual borehole rock mass structure detection. The detection results are consistent with the actual characteristics.

Current Developments in Vitrectomy: Hypersonic Vitrectomy and 3-Dimensional (3D) Vitrectomy Surgery

With the advancing technology in vitrectomy surgery, revolutionary changes have occurred. Improvements in the imaging and vitrectomy systems have made the operation process more practical and comfortable, and have led to significant success in the postoperative period. 3D imaging systems, which entered into ophthalmology practice in 2008, and hypersonic vitrectomy systems, which started to practice ophthalmology as a new technology in 2017, have gained new perspectives in vitrectomy surgery.

In Situ Visualization for 3D Ultrasound-Guided Interventions with Augmented Reality Headset.

Augmented Reality (AR) headsets have become the most ergonomic and efficient visualization devices to support complex manual tasks performed under direct vision. Their ability to provide hands-free interaction with the augmented scene makes them perfect for manual procedures such as surgery. This study demonstrates the reliability of an AR head-mounted display (HMD), conceived for surgical guidance, in navigating in-depth high-precision manual tasks guided by a 3D ultrasound imaging system. The integration between the AR visualization system and the ultrasound imaging system provides the surgeon with real-time intra-operative information on unexposed soft tissues that are spatially registered with the surrounding anatomic structures. The efficacy of the AR guiding system was quantitatively assessed with an in vitro study simulating a biopsy intervention aimed at determining the level of accuracy achievable. In the experiments, 10 subjects were asked to perform the biopsy on four spherical lesions of decreasing sizes (10, 7, 5, and 3 mm). The experimental results showed that 80% of the subjects were able to successfully perform the biopsy on the 5 mm lesion, with a 2.5 mm system accuracy. The results confirmed that the proposed integrated system can be used for navigation during in-depth high-precision manual tasks.

Time-Varying Vibration Compensation Based on Segmented Interference for Triangular FMCW LiDAR Signals

Frequency modulation continuous wave (FMCW) light detection and ranging (LiDAR) 3D imaging system may suffer from time-varying vibrations which will affect the accuracy of ranging and imaging of a target. The system uses only a single-period FMCW LiDAR signal to measure the range of each spot; however, traditional methods may not work well to compensate for the time-varying vibrations in a single period because they generally assume the vibration velocity is constant. To solve this problem, we propose a time-varying vibration compensation method based on segmented interference. We first derive the impact of time-varying vibrations on the range measurement of the FMCW LiDAR system, in which we divide the time-varying vibration errors into primary errors caused by the vibrations with a constant velocity and quadratic errors. Second, we estimate the coefficients of quadratic vibration errors by using a segmented interference method and build a quadratic compensation filter to eliminate the quadratic vibration errors from the original signals. Finally, we use the symmetrical relations of signals in a triangular FMCW period to estimate the vibration velocity and establish a primary compensation filter to eliminate the primary vibration errors. Numerical tests verify the applicability of this method in eliminating time-varying vibration errors with only a one-period triangular FMCW signal and its superiority over traditional methods.

Evaluation of 3D Face-Scan images obtained by stereophotogrammetry and smartphone camera

The purpose of this study is to compare and analyze the similarities between three-dimensional images captured by a smartphone camera with depth sensors and a conventional 3dMD Face system. Twenty six individuals (16female, 10male) were involved in this study, agreed to take part and as such had no paralysis, tics, etc., which may prevent taking the image. Anthropometric points were marked, and plasters were placed on the forehead, upper nasal dorsum and zygoma to determine matching areas. 3D images were captured with a DOF (Depth of Field) camera of a smartphone (iPhone X, Apple Inc. CA, USA) and a 3D imaging system (3dMD, Atlanta, GA, USA). Linear and angular measurements were carried. Overlapping area amounts of matched images and X, Y and Z coordinates of landmarks were compared. For comparison of the data, student t-test and Mann-Whitney U test were used at P<0.05. Statistically significant changes were found in distance between inner commissures of right and left eye fissure and nasolabial angle. RMS (Root Mean Square) values were found between 0.58 and 1. Images captured with a DOF camera of a smartphone, can be used to record and evaluate 3D soft tissue changes. However, due to the anatomical features of some regions, the deficiency of clear visualization needs improvements.

Spatio-temporal continuous gesture recognition under degraded environments: performance comparison between 3D integral imaging (InIm) and RGB-D sensors

In this paper, we introduce a deep learning-based spatio-temporal continuous human gesture recognition algorithm under degraded conditions using three-dimensional (3D) integral imaging. The proposed system is shown as an efficient continuous human gesture recognition system for degraded environments such as partial occlusion. In addition, we compare the performance between the 3D integral imaging-based sensing and RGB-D sensing for continuous gesture recognition under degraded environments. Captured 3D data serves as the input to a You Look Only Once (YOLOv2) neural network for hand detection. Then, a temporal segmentation algorithm is employed to segment the individual gestures from a continuous video sequence. Following segmentation, the output is fed to a convolutional neural network-based bidirectional long short-term memory network (CNN-BiLSTM) for gesture classification. Our experimental results suggest that the proposed deep learning-based spatio-temporal continuous human gesture recognition provides substantial improvement over both RGB-D sensing and conventional 2D imaging system. To the best of our knowledge, this is the first report of 3D integral imaging-based continuous human gesture recognition with deep learning and the first comparison between 3D integral imaging and RGB-D sensors for this task.

How I do it? Uniportal full endoscopic pseudoarthrosis release of left L5/S1 Bertolotti's syndrome under intraoperative computer tomographic guidance in an ambulatory setting.

There is limited literature on technique full endoscopic pseudoarthrosis release of Bertolotti syndrome. Uniportal full endoscopic pseudoarthrosis release technique applies for patients presenting with symptomatic Bertolotti's syndrome. Full-thickness endoscopic drilling is carried out from most ventrolateral margin of pseudoarthrosis articulating with the highest part of sacral ala (PH) point to dorsal medioinferior margin of pseudoarthrosis adjacent to superior articular process (MS) point. Complete pseudoarthrosis release was confirmed with an intraoperative 3D imaging system. The uniportal full endoscopic pseudoarthrosis release is a good alternative to open surgery to release pseudoarthrosis in L5/S1 Bertolotti's syndrome in an ambulatory setting.

Time-magnified photon counting with 550-fs resolution

Time-correlated single-photon counting (TCSPC) is an enabling technology for applications such as low-light fluorescence lifetime microscopy and photon counting time-of-flight (ToF) 3D imaging. However, state-of-the-art TCSPC single-photon timing resolution (SPTR) is limited to 3–100 ps by single-photon detectors. Here, we experimentally demonstrate a time-magnified TCSPC (TM-TCSPC) that achieves an ultrashort SPTR of 550 fs with an off-the-shelf single-photon detector. The TM-TCSPC can resolve ultrashort pulses with a 130-fs pulse width difference at a 22-fs accuracy. When applied to photon counting ToF 3D imaging, the TM-TCSPC greatly suppresses the range walk error that limits all photon counting ToF 3D imaging systems by 99.2% and thus provides high depth accuracy and precision of 26 µm and 3 µm, respectively.

The Application of Cameras in Precision Pig Farming: An Overview for Swine-Keeping Professionals.

Simple SummaryThe preeminent purpose of precision livestock farming (PLF) is to provide affordable and straightforward solutions to severe problems with certainty. Some data collection techniques in PLF such as RFID are accurate but not affordable for small- and medium-sized farms. On the other hand, camera sensors are cheap, commonly available, and easily used to collect information compared to other sensor systems in precision pig farming. Cameras have ample chance to monitor pigs with high precision at an affordable cost. However, the lack of targeted information about the application of cameras in the pig industry is a shortcoming for swine farmers and researchers. This review describes the state of the art in 3D imaging systems (i.e., depth sensors and time-of-flight cameras), along with 2D cameras, for effectively identifying pig behaviors, and presents automated approaches for monitoring and investigating pigs’ feeding, drinking, lying, locomotion, aggressive, and reproductive behaviors. In addition, the review summarizes the related literature and points out limitations to open up new dimensions for future researchers to explore.Pork is the meat with the second-largest overall consumption, and chicken, pork, and beef together account for 92% of global meat production. Therefore, it is necessary to adopt more progressive methodologies such as precision livestock farming (PLF) rather than conventional methods to improve production. In recent years, image-based studies have become an efficient solution in various fields such as navigation for unmanned vehicles, human–machine-based systems, agricultural surveying, livestock, etc. So far, several studies have been conducted to identify, track, and classify the behaviors of pigs and achieve early detection of disease, using 2D/3D cameras. This review describes the state of the art in 3D imaging systems (i.e., depth sensors and time-of-flight cameras), along with 2D cameras, for effectively identifying pig behaviors and presents automated approaches for the monitoring and investigation of pigs’ feeding, drinking, lying, locomotion, aggressive, and reproductive behaviors.