3D Matching Research Articles

3D flow field estimation and assessment for live cell fluorescence microscopy.

The revolution in light sheet microscopy enables the concurrent observation of thousands of dynamic processes, from single molecules to cellular organelles, with high spatiotemporal resolution. However, challenges in the interpretation of multidimensional data requires the fully automatic measurement of those motions to link local processes to cellular functions. This includes the design and the implementation of image processing pipelines able to deal with diverse motion types, and 3D visualization tools adapted to the human visual system. Here, we describe a new method for 3D motion estimation that addresses the aforementioned issues. We integrate 3D matching and variational approach to handle a diverse range of motion without any prior on the shape of moving objects. We compare different similarity measures to cope with intensity ambiguities and demonstrate the effectiveness of the Census signature for both stages. Additionally, we present two intuitive visualization approaches to adapt complex 3D measures into an interpretable 2D view, and a novel way to assess the quality of flow estimates in absence of ground truth. https://team.inria.fr/serpico/data/3d-optical-flow-data/. Supplementary data are available at Bioinformatics online.

Objective Identification of Bullets Based on 3D Pattern Matching and Line Counting Scores

In firearm identification, a firearm examiner looks at a pair of fired bullets or cartridge cases using a comparison microscope and determines from this visual analysis if they were both fired from the same firearm. In the particular case of fired bullets, the individual firearm signature takes the form of a striated pattern. Over the time, the firearm examiner’s community developed two distinct approaches for bullet identification: pattern matching and line counting. More recently, the emergence of technology enabling the capture of surface topographies down to a submicron depth resolution has been a catalyst for the field of computerized objective ballistic identification. Objectiveness is achieved through the statistical analysis of various scores of known matches and known nonmatches exhibit pair comparison, which in turn implies the capture of large quantities of bullets and cartridge cases topographies. The main goal of this study was to develop an objective identification method for bullets fired from conventionally rifled barrels, and to test this method on public and proprietary bullet 3D image datasets captured at different lateral resolutions. Two newly developed bullet identification scores, the Line Counting Score (LCS) and the Pattern Matching Score, computed on 3D topographies yielded perfect match versus nonmatch separation for three different sets used in the standard Hamby–Brundage Test. A similar analysis performed using a larger, more-realistic set, enabled us to define a discriminative line at a false match rate of 1/10[Formula: see text]000 on a 2D plot that shows both identification scores for matches and nonmatches. The LCS is shown to produce a better sensitivity than the standard consecutive matching striae criteria for the more-realistic dataset. A likelihood function was also computed from a linear combination of both scores, and a conservative approach based on extreme value theory is proposed to extrapolate this function in the score domain where nonmatch data are not available. This study also provides a better understanding of the limitations of studies that involve very few firearms.

BM3D-based total variation algorithm for speckle removal with structure-preserving in OCT images.

In this paper, we propose a total variation based on block matching 3D (BM3D-TV method), which includes the total variation regular term, the data fidelity term, and the block matching term. In addition, we also propose a fast numerical algorithm based on the split Bregman iteration for the proposed method. By assigning suitable weights to the data fidelity term and block matching term, the image noise reduction and the image structural characteristics can be matched optimally. We test the proposed method on six human retinal and one mouse skin optical coherence tomography (OCT) images respectively, and also compare it with total variation (TV) and BM3D, which were proved to be effective in denoising. The performances of these methods are quantitatively evaluated in terms of the signal-to-noise ratio, the contrast-to-noise ratio, and the averaged equivalent number of homogeneous areas at the aspects of speckle reduction and structure protection. Vast experiments show that the BM3D-TV method can effectively reduce speckle noise in OCT images, protect important structural information and improve image quality, compared with the BM3D and TV methods.

Study of a Full-View 3D Finger Vein Verification Technique

Finger vein modality has unique advantages, allowing it to play an important role in biometrics. However, the approach to vein imaging and information acquisition typically adopted in current vein verification systems employs a monocular camera to acquire a single-view 2D vein image from only one side of the finger, which causes two problems: it acquires limited vein pattern information for verification, and it causes clear differences among samples of the same subject captured from different finger positions in contact-free mode. Both of these problems have adverse effects on system performance. In general, existing systems are more sensitive to positional variations of the finger, particularly those caused by pitch and roll movements. This concern remains a challenge despite considerable efforts to address it in recent years. To provide a fundamental solution to the above issues, we propose an entirely new system, which includes a software and hardware platform that collects a full-view of the vein pattern information from whole fingers with three cameras, a novel 3D reconstruction method to build the full-view 3D finger vein image, and a corresponding 3D finger vein feature extraction and matching strategy based on a lightweight convolutional neural network (CNN) with depthwise separable convolution. Experimental results demonstrate the potential of our proposed system and show that compared to the traditional single-view 2D mode of finger vein recognition, the new system both efficiently improves the recognition performance and simultaneously takes full advantage of additional valid information provided by the finger vein biometrics.

Abstract 42: The importance of intact tumor immune microenvironment in unpropagated 3D fresh patient tumoroids in immuno-oncology drug testing for immunogenic tumor cell death and T-cell activation

Abstract Background: The tumor stroma contains important components of the tumor microenvironment including fibroblasts, immune cells, and the extracellular matrix. While none of these cells are malignant, the dynamic interplay of these cells drive alterations in cellular functions. While informative, conventional 2D dissociated tumor models do not maintain the stromal-stoichiometry of the tumor microenvironment to accurately assess ex-vivo tumor cell viability and T-cell activation after drug treatment. In this study we performed a comparative assessment of tumor immune microenvironment, and therapy mediated changes in tumor cell viability and T-cell activation in live 3D tumoroids versus matched 2D dissociated cells of the same patients’ fresh tumors side-by-side. Methods: All human tumor samples were obtained with patients’ consent and relevant IRB approval. Un-propagated live 3D tumoroids measuring 100-150 micron in size were prepared from fresh patient tumor samples. In parallel, the same patient tumor sample was enzymatically digested into 2D tumor dissociations to obtain single cell populations for direct comparison to live 3D tumoroids. Cytokine analysis was performed to determine immunomodulatory cytokine profile. To better understand the role of tumor extracellular matrix on immuno-oncology drug response, tumor models were treated with pembrolizumab (Keytruda) and atezolizumab (Tecentriq) (10ug/ml) for 48 hours and multiplex cytokine release assay, flow cytometry and high content confocal image analysis were performed. Results: Comparative studies revealed that removal of extracellular matrix by digestive enzymes significantly affects tumor immune microenvironment as assessed by multiplex cytokine release assays. Flow cytometry analysis demonstrated differential T-cell and NK cell activation upon immuno-oncology drug treatment between the unpropagated 3D-tumoroid and dissociated cell suspension models. High-content imaging studies combined with flow death analysis indicated that tumor extracellular matrix plays an important role in tumor cell killing by immuno-oncology drugs. Summary: Our data shows the importance of maintaining the stoichiometry and cell-to-cell interactions of the tumor microenvironment. Using a powerful combinatorial approach including high-content image analysis, flow cytometry, and cytokine analysis we are able to accurately assess therapy-mediated tumor cell death in a quantitative manner. Furthermore, these data demonstrate that intact tumor extracellular matrix within unpropagated 3D tumoroids is critical for a more accurate assessment of therapy-mediated changes in tumor immune microenvironment. Citation Format: Vijayendra Agrawal, Melanie Mediavilla-Varela, Melba Marie Page, Jenny Kreahling, Soner Altiok. The importance of intact tumor immune microenvironment in unpropagated 3D fresh patient tumoroids in immuno-oncology drug testing for immunogenic tumor cell death and T-cell activation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 42.

3D Printing the Future of Healthcare

3D Printing the Future of Healthcare

GNSS/INS/LiDAR-SLAM Integrated Navigation System Based on Graph Optimization

A Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS)/Light Detection and Ranging (LiDAR)-Simultaneous Localization and Mapping (SLAM) integrated navigation system based on graph optimization is proposed and implemented in this paper. The navigation results are obtained by the information fusion of the GNSS position, Inertial Measurement Unit (IMU) preintegration result and the relative pose from the 3D probability map matching with graph optimizing. The sliding window method was adopted to ensure that the computational load of the graph optimization does not increase with time. Land vehicle tests were conducted, and the results show that the proposed GNSS/INS/LiDAR-SLAM integrated navigation system can effectively improve the navigation positioning accuracy compared to GNSS/INS and other current GNSS/INS/LiDAR methods. During the simulation of one-minute periods of GNSS outages, compared to the GNSS/INS integrated navigation system, the root mean square (RMS) of the position errors in the North and East directions of the proposed navigation system are reduced by approximately 82.2% and 79.6%, respectively, and the position error in the vertical direction and attitude errors are equivalent. Compared to the benchmark method of GNSS/INS/LiDAR-Google Cartographer, the RMS of the position errors in the North, East and vertical directions decrease by approximately 66.2%, 63.1% and 75.1%, respectively, and the RMS of the roll, pitch and yaw errors are reduced by approximately 89.5%, 92.9% and 88.5%, respectively. Furthermore, the relative position error during the GNSS outage periods is reduced to 0.26% of the travel distance for the proposed method. Therefore, the GNSS/INS/LiDAR-SLAM integrated navigation system proposed in this paper can effectively fuse the information of GNSS, IMU and LiDAR and can significantly mitigate the navigation error, especially for cases of GNSS signal attenuation or interruption.

Analysis of forearm rotational motion using biplane fluoroscopic intensity-based 2D–3D matching

Measuring three-dimensional (3D) forearm rotational motion is difficult. We aimed to develop and validate a new method for analyzing 3D forearm rotational motion. We proposed biplane fluoroscopic intensity-based 2D–3D matching, which employs automatic registration processing using the evolutionary optimization strategy. Biplane fluoroscopy was conducted for forearm rotation at 12.5 frames per second along with computed tomography (CT) at one static position. An arm phantom was embedded with eight stainless steel spheres (diameter, 1.5 mm), and forearm rotational motion measurements using the proposed method were compared with those using radiostereometric analysis, which is considered the ground truth. As for the time resolution analysis, we measured radiohumeral joint motion in a patient with posterolateral rotatory instability and compared the 2D–3D matching method with the simulated multiple CT method, which uses CTs at multiple positions and interpolates between the positions. Rotation errors of the radius and ulna between these two methods were 0.31 ± 0.35° and 0.32 ± 0.33°, respectively, translation errors were 0.43 ± 0.35 mm and 0.29 ± 0.25 mm, respectively. Although the 2D–3D method could detect joint dislocation, the multiple CT method could not detect quick motion during joint dislocation. The proposed method enabled high temporal- and spatial-resolution motion analyses with low radiation exposure. Moreover, it enabled the detection of a sudden motion, such as joint dislocation, and may contribute to 3D motion analysis, including joint dislocation, which currently cannot be analyzed using conventional methods.

Computational evaluations of HYDRUS simulations of drip irrigation in 2D and 3D domains (i-Surface drippers)

HYDRUS is a popular package for simulating water and solutes movement in variably-saturated porous media. It is widely used by designers of drip irrigation systems to simulate the active wetting pattern. However, there are many design parameters of the domain and for the flux calculation; other than the acceptable simulations, some configurations might cause under-estimation or over-estimation of the wetting pattern. Comparative assessments of the surface drip simulation parameters were performed. We evaluated the effect of different domain geometries, element shapes, coordinate systems, emitter discharges, and soil textures on the accuracy and stability of the simulation. The results showed that the 3D simulations are more successful and reliable than the 2D simulations in terms of mass balance error. For the 2D domains, the error increases as the texture goes finer, and for axisymmetric domains than the Cartesian ones. We found a relationship between the flux and the soil hydraulic conductivity that their quotient should not exceed 1.8 and 3.2 for axisymmetric and cartesian coordinates. Our outcomes show that the infiltration stage took more time than the redistribution stage because of the variation in water content that delays the convergence at infiltration.Additionally, we found that the range between the saturated and the residual water content of the soil causes instability of the simulation as it gets higher. The differences between 2D simulations and the equivalent 3D slices were highly dependent on the soil texture, the heavier the larger; and dependent on the simulation phase, where the redistribution phase has fewer differences than the infiltration phase. Finally, we have determined the best matching 2D flux profile to each 3D profile and revealed the source of variation between 2D and 3D profiles where it was mostly-affected by the emitter’s location, the soil texture, and simulation phase. In part 2 of this paper, we expanded the study for subsurface drip simulations and showed the difference between the two systems’ designs.

A Visualization Modeling Method of Road 3D Model

This paper presents a visualization modeling method of road 3D model for traffic simulation and driving simulation. With this method, the semi-automatic design of the road longitudinal curve can be realized, and the linearity test can be completed automatically according to the road design theory. The building block method has been used in this method to store the linear data of the road. Based on the constrained Delaunay triangulation theory, the automatic construction of the road 3D model and matching with the terrain model is realized. This paper introduces the main algorithms and data structure used in this method, and implements a 3D visualization modeling tool by using Qt, OSG and other software.

Tattoo free setup for partial breast irradiation: A feasibility study.

PurposePatients undergoing external beam accelerated partial breast irradiation (APBI) receive permanent tattoos to aid with daily setup alignment and verification. With the advent of three‐dimensional (3D) body surface imaging and two‐dimensional (2D) x‐ray imaging‐based matching to surgical clips, tattoos may not be necessary to ensure setup accuracy. We compared the accuracy of conventional tattoo‐based setups to a patient setup without tattoos.Materials/methodsTwenty consecutive patients receiving APBI at our institution from July 10, 2017 to February 13, 2018 were identified. All patients received tattoos per standard of care. Ten patients underwent setup using tattoos for initial positioning followed by surface imaging and 2D matching of surgical clips. The other ten patients underwent positioning using surface imaging followed by 2D matching without reference to tattoos. Overall setup time and orthogonal x‐ray‐based shifts after surface imaging per fraction were recorded. Shift data were used to calculate systematic and random error.ResultsAmong ten patients in the “no tattoo” group, the average setup time per fraction was 6.83 min vs 8.03 min in the tattoo cohort (P < 0.01). Mean 3D vector shifts for patients in the “no tattoo” group were 4.6 vs 5.9 mm in the “tattoo” cohort (P = NS). Mean systematic errors in the “no tattoo” group were: 1.2 mm (1.5 mm SD) superior/inferior, 0.5 mm (1.6 mm SD) right/left, and 2.3 mm (1.9 mm SD) anterior/posterior directions. Mean systematic errors in the “tattoo” group were: 0.8 mm (2.2 mm SD) superior/inferior, 0.3 mm (2.5 mm SD) right/left, and 1.4 mm (4.4 mm SD) anterior/posterior directions. The random errors in the “no tattoo” group ranged from 0.6 to 0.7 mm vs 1.2 to 1.7 mm in the “tattoo” group.ConclusionsUsing both surface imaging and 2D matching to surgical clips provides excellent accuracy in APBI patient alignment and setup verification with reduced setup time relative to the tattoo cohort. Skin‐based tattoos may no longer be warranted for patients receiving external beam APBI.

Crystal structures, Hirsfeld surface analysis and a computational study of four ethyl 2-oxo-2H-chromene-3-carboxylate derivatives: a survey of organyl 2-oxo-2H-chromene-3-carboxylate structures

Abstract Crystal structures, Hirshfeld surface analysis and a computational study have been carried out on 2-oxo-2H-chromene-3-carboxylates. Crystal structures are reported for ethyl R-2-oxo-2H-chromene-3-carboxylate derivatives, 2a: R=6-Me, 2b: 7-Me, 2c: 7-Me, 2d: R=7-MeO. In contrast to 2-oxo-2H-chromene-3-carboxamides, 1, in which classical intramolecular N–H···O hydrogen bonds stabilize planar structures and hinder rotation of the amido group out of the coumarin plane in 2, without an equivalent hydrogen bond, there is a greater rotational freedom of the carboxylate group. The interplanar angles between the coumarin core and its attached –C(O)–R substituent in crystalline 2a, 2b, 2c and 2d are 10.41(6), 36.65(6), 10.4(2) and 5.64(6)°, respectively, with distances between the carbonyl oxygen atoms of 2.8255(16), 2.9278(16), 4.226(2) and 2.8328(14) Å, respectively. A theoretical study of molecular conformations was carried out at the M06-2X density level with the 6-31+G(d) and aug-cc-pVTZ basis sets, in methanol solution modeled by PCM, indicated that the most stable conformations had the carbonyl group of the ester in the plane of the coumarin core: the s-cis arrangement of the ester carbonyl and the 2-oxo moieties being the slightly more stable than the s-trans form by less than 0.5 kcal/mol. The experimental conformations of 2a and 2d match well the low energy s-cis arrangement, and 2c matches the slightly lesser stable s-trans arrangement found in the theoretical study. A survey of the molecular conformations of more than 50 2H-chromene-3-carboxylates derivatives in the CCDC data base indicated two distinct groupings of conformations, s-cis and s-trans, each with interplanar angles &lt;30°.

Case report: Forensic 3D-match of hair brush and scalp abrasions revealing dynamic brush deformation

Abstract Forensic injury interpretation can be greatly enhanced by the use of 3D-surface documentation, also in conjunction with full body scans. For static juxtapositioning, a rigid shape transfer from weapon or injury causing object to the victim's skin or bone will be assumed for patterned injuries, upon which an object's shape directly explains the shape of an injury. Forensic pathology expertise may be essential in reading the resulting 3D shape match attempts, particularly when in due process of injury causation, deformation of either the object/weapon or victim's tissues occurred, causing a dynamic rather than rigid shape transfer. In this case, a 3D match using manual forensic juxtapositioning of punctate and elongated striate forehead skin abrasions and a hairbrush yielded a partial but not perfect match. Qualitative medicolegal appreciation of the partial match result clearly indicated centrifugal brush bristle deformation after impact, causing a centrifugal abrasion pattern, thus having dynamically extended an initially stationary punctate abrasion and bristle end shape match. This was corroborated by both the elasticity of the bristles and the brush frame fracture. Presence and location of the fracture indicated a relatively high force between the brush handle on one hand and the bristles on the other. This case shows how the application of targeted forensic pathology interpretation can elucidate what technically only is a partial 3D match and add re-constructive meaning. Generally, more research is needed in establishing just how technical sciences and specific medicolegal expertise are best integrated.

Assisting Pottery Restoration Procedures with Digital Technologies

The fragmentary nature of pottery is considered a common place. Conservators are requested to apply a proper restoration solution by taking under consideration a wide range of morphological features and physicochemical properties that derive from the artefact itself. In this work, the authors discuss on a low-cost pottery-oriented restoration pipeline that is based on the exploitation of technologies such as 3D digitisation, data analysis, processing and printing. The pipeline uses low-cost commercial and open source software tools and on the authors' previously published 3D pose normalisation algorithm that was initially designed for 3D vessel shape matching. The authors objectively evaluate the pipeline by applying it on two ancient Greek vessels of the Hellenistic period. The authors describe in detail the involved procedures such as the photogrammetric 3D digitisation, the 3D data analysis and processing, the 3D printing procedures and the synthetic shreds post processing. They quantify the pipeline's applicability and efficiency in terms of cost, knowledge overhead and other aspects related to restoration tasks.

A Hierarchical Attention Fused Descriptor for 3D Point Matching

Motivated by recent successes on learning 3D feature representations, we present a Siamese network to generate representative 3D descriptors for 3D point matching in point cloud registration. Our system, dubbed HAF-Net, consists of feature extraction module, hierarchical feature reweighting and recalibration module (HRR), as well as feature aggregation and compression module. The HRR module is proposed to adaptively integrate multi-level features through learning, acting as a hierarchical attention fusion mechanism. The learnable feature pooling technique VLAD is extended into our aggregation module, which is further utilized to extract principal components of features and compress them into a low dimensional feature vector. To train our model, we amass a large dataset for 3D point matching. The dataset is composed of matched and unmatched point block pairs, which are automatically searched from existing reconstruction datasets with known poses. The experiments demonstrate that the proposed HAF-Net not only outperforms other state-of-the-art approaches in 3D feature representation but also has a good generalization ability in various tasks and datasets.

Registration Algorithm for Point Cloud Based on Normalized Cross-Correlation

We propose a registration algorithm based on neighborhood similarity for 3D point clouds collected by optical measurement and without prior information. The algorithm first applies the improved minimum spanning tree (Prim algorithm) to classify the point cloud in order to obtain the topology information of the data. Specifically, vectors among root nodes and child nodes are processed, and the points on nodes are classified into different levels according to their scanning angle to simplify data and preserve the most representative points. Then, through the perspective conversion between 2D and 3D and according to the corresponding point set obtained by previous classification, the fast normalized cross-correlation (a 2D matching criterion) is applied to determine the relationship between initial characteristic points. Finally, distance constraints remove the errors between point pairs and allow calculating the registration parameters. Experimental results show that the algorithm has high registration accuracy and is suitable for point cloud data obtained by laser and structured light acquisition.

A Direct Material Reconstruction Method for DECT Based on Total Variation and BM3D Frame

Dual-energy computed tomography (DECT) has attracted the attention of clinical researchers because of its outstanding capabilities to identify and decompose materials. Considering that material decomposition is unstable, reconstructed material images experience severe noise magnification resulting from the measurement data. To alleviate this problem, we propose a direct material reconstruction method by establishing a novel constrained reconstruction model based on total variation (TV) and block matching 3D (BM3D) frame regularization. TV regularization preserves the sparsity in the gradient domain of material maps and helps to preserve the image edges. BM3D frame is applied to depict the similarities among various patches in reconstructed images by grouping similar 2D image blocks into 3D data arrays combined with sparse transforms. To solve the program efficiently, a practical algorithm based on alternating direction method is developed. A modified strategy of block matching denoising is designed by incorporating the polychromatic reconstructed image into the problem solution. Digital and real data phantom studies are performed to validate the performance of the proposed method. The proposed method reduces the standard deviation on the selected region of interests by an average of 95.02% and 89.03% for the digital phantom and 95.21% and 84.19% for the real data compared with the extended simultaneous algebraic reconstruction technique and TV-based method, respectively. The reconstruction results demonstrate that the proposed method has promising capabilities in direct material reconstruction and superiority over its counterparts.

Quantitative comparison of freeware software for bone mesh from DICOM files

Musculo-skeletal modelling, 3D printing of bone models and also custom design of relevant prostheses starts from accurate STL files. These are obtained from medical imaging after careful segmentation and 3D reconstruction using specialized software, but most of these are very expensive. The aim of the present study is to assess and compare alternative software available for free. Three freeware software were selected from the most popular, and one standard platform was made available at the institute of the authors. Using each of these four software and starting from available DICOM files obtained previously by a CT scanner, three different bone models were reconstructed from each of five different human anatomical areas for a total of 60 bone model reconstructions. A young radiographer performed the bone reconstruction without specific technical training. 3D spatial matching of corresponding anatomical models was also performed to determine distance-maps for the assessment of final surface quality. In all four software many valuable features were available, with minimum differences, and bone models of good quality were obtained. Large differences in file sizes (mean range over the five anatomical models 66-338) and in the number of triangles (870-1350 thousands) were found, with triangles for MByte ratio ranging from about 4 to 20 thousands. The distance-map analysis revealed that root mean square deviation averaged over the five anatomical models ranged from 0.13 to 2.21 mm for the six spatial matches between the four software. These software are suitable for 3D bone model reconstruction, and do not require special training, and as such these can open up opportunities for biomechanical modelling and medical education.

Video denoising algorithm based on improved dual‐domain filtering and 3D block matching

This study introduces an algorithm for video denoising based on improved dual-domain filtering and 3D block matching. The wavelet thresholding based on 3D block matching is introduced to make full use of the correlation of video sequence in order to apply dual-domain filtering to the video. A layered approach is used that attempts denoising in both a base layer and a detail layer. The result of wavelet thresholding based on 3D block matching is used as a guide image to make the base layer smoother. Shrinkage of short-time Fourier transform coefficients further decreases the noise in the detail layer. Experimental results show that the authors' algorithm generates a better base layer and detail layer than the traditional dual-domain filtering algorithms. The subjective and objective comparisons of different algorithms also prove that the proposed algorithm performs better for video denoising.

Ligand-Based Pharmacophore Modeling Using Novel 3D Pharmacophore Signatures.

Pharmacophore modeling is a widely used strategy for finding new hit molecules. Since not all protein targets have available 3D structures, ligand-based approaches are still useful. Currently, there are just a few free ligand-based pharmacophore modeling tools, and these have a lot of restrictions, e.g., using a template molecule for alignment. We developed a new approach to 3D pharmacophore representation and matching which does not require pharmacophore alignment. This representation can be used to quickly find identical pharmacophores in a given set. Based on this representation, a 3D pharmacophore ligand-based modeling approach to search for pharmacophores which preferably match active compounds and do not match inactive ones was developed. The approach searches for 3D pharmacophore models starting from 2D structures of available active and inactive compounds. The implemented approach was successfully applied for several retrospective studies. The results were compared to a 2D similarity search, demonstrating some of the advantages of the developed 3D pharmacophore models. Also, the generated 3D pharmacophore models were able to match the 3D poses of known ligands from their protein-ligand complexes, confirming the validity of the models. The developed approach is available as an open-source software tool: http://www.qsar4u.com/pages/pmapper.php and https://github.com/meddwl/psearch.