Search Results (27)

Lantana camara L. is sold worldwide for ornamental purposes, although it is also characterized by high invasiveness potential. Genetic and molecular data available for L. camara are still poor, and breeding is performed through conventional methods. This study focused on a molecular genotyping analysis through the ddRADseq method on an experimental collection of lantana clonal lines to evaluate the potential of molecular techniques in performing marker-assisted breeding, in favour of variety registration and in guaranteeing plant variety protection for the species. Although high genetic uniformity was observed in the population, a unique molecular profile was assigned to every line, indicating the effectiveness of the approach used. Interestingly, low degrees of heterozygosity were observed. In addition, the possibility of inferring ploidy levels through SNP profiles was assessed since it would avoid the necessity of previous biological knowledge and the use of fresh materials. Ploidy analysis is of high interest for lantana breeding to obtain less invasive triploids. Flow cytometry and chromosome counting were used for inference assessment. An nQuack framework provided correct results for the majority of the clonal lines, confirming its effectiveness. These findings encourage the adoption of molecular systems to help breed minor species such as L. camara. Full article

Accurate preoperative image processing in markerless image-guided surgeries is an important task. However, preoperative planning highly depends on the quality of medical imaging data. In this study, a novel algorithm for outer skin layer extraction from head computed tomography (CT) scans is presented and evaluated. Axial, sagittal, and coronal slices are processed separately to generate spatial data. Each slice is binarized using manually defined Hounsfield unit (HU) range thresholding to create binary images from which valid contours are extracted. The individual points of each contour are then projected into three-dimensional (3D) space using slice spacing and origin information, resulting in uniplanar point clouds. These point clouds are then fused through geometric addition into a single enriched triplanar point cloud. A two-step downsampling process is applied, first at the uniplanar level and then after merging, using a voxel size of 1 mm. Across two independent datasets with a total of 83 individuals, the merged cloud approach yielded an average of 11.61% more unique points compared to the axial cloud. The validity of the triplanar point cloud reconstruction was confirmed by a root mean square (RMS) registration error of 0.848 ± 0.035 mm relative to the ground truth models. These results establish the proposed algorithm as robust and accurate across different CT scanners and acquisition parameters, supporting its potential integration into patient registration for markerless image-guided surgeries. Full article

Accurate femoral tunnel positioning is crucial for successful anterior cruciate ligament reconstruction (ACLR), yet traditional arthroscopic techniques face significant challenges in spatial orientation and precise anatomical localization. This study presents a novel marker-less computer-assisted navigation system that integrates three-dimensional femoral modeling with real-time arthroscopic guidance. The system employs advanced image processing techniques for accurate condyle segmentation and implements the Bernard and Hertel (BH) grid system for standardized positioning. A curvature-based feature extraction approach precisely identifies the capsular line reference (CLR) on the lateral condyle surface, forming the foundation for establishing the BH reference grid. The system’s two-stage registration framework, combining SIFT-ICP algorithms, achieves accurate alignment between preoperative models and arthroscopic views. Validation results from expert surgeons demonstrated high precision, with 71.5% of test groups achieving acceptable or excellent performance standards (mean deviation distances: 1.12–1.86 mm). Unlike existing navigation solutions, our system maintains standard surgical workflow without requiring additional surgical instruments or markers, offering an efficient and minimally invasive approach to enhance ACLR precision. This innovation bridges the gap between preoperative planning and intraoperative execution, potentially improving surgical outcomes through standardized tunnel positioning. Full article

In recent years, a global increase in allergy incidence following chemical exposure has been observed. While the process of skin sensitization is well characterized through the adverse outcome pathway (AOP) framework, the immunological mechanisms underlying respiratory sensitization remain less well understood. Respiratory sensitizers are classified as substances of very high concern (SVHC) under the European Union (EU) regulation for the registration, evaluation, authorization and restriction of chemicals (REACH), emphasizing the importance of evaluating respiratory tract sensitization as a critical hazard. However, the existing new approach methodologies (NAMs) for the identification of skin sensitizers lack the capacity to differentiate between skin and respiratory sensitizers. Thus, it is imperative to develop physiologically relevant test systems specifically tailored to assess respiratory sensitizers. This study aimed to evaluate the efficacy of ALIsens^®, a three-dimensional (3D) in vitro alveolar model designed for the identification of respiratory sensitizers and to determine its ability to correctly identify sensitizers. In this study, we used a range of skin sensitizers and non-sensitizers to define the optimal exposure dose, identify biomarkers, and establish tentative thresholds for correct sensitizer classification. The results demonstrate that ALIsens^® is a promising in vitro complex model that could successfully discriminate respiratory sensitizers from skin sensitizers and non-sensitizers. Furthermore, the thymic stromal lymphopoietin receptor (TSLPr) cell surface marker was confirmed as a reliable biomarker for predicting respiratory sensitization hazards. Full article

Paranasal sinus surgery, a common treatment for chronic rhinosinusitis, requires exceptional precision due to the proximity of critical anatomical structures. To ensure accurate instrument control and clear visualization of the surgical site, surgeons utilize computer-aided surgical navigation (CSN). A key component of CSN is the registration process, which is traditionally reliant on manual or marker-based techniques. However, there is a growing shift toward marker-less registration methods. In previous work, we investigated a mesh-based registration approach using a Mixed Reality Head-Mounted Display (MR-HMD), specifically the Microsoft HoloLens 2. However, this method faced limitations, including depth holes and invalid values. These issues stemmed from the device’s low-resolution camera specifications and the 3D projection steps required to upscale RGB camera spaces. In this study, we propose a novel automated marker-less registration method leveraging Neural Radiance Field (NeRF) technology with an MR-HMD. To address insufficient depth information in the previous approach, we utilize rendered-depth images generated by the trained NeRF model. We evaluated our method against two other techniques, including prior mesh-based registration, using a facial phantom and three participants. The results demonstrate our proposed method achieves at least a 0.873 mm (12%) improvement in registration accuracy compared to others. Full article

Background: Caregiver–infant reciprocity is related to infant/toddler development and health. However, there is a dearth of research on reciprocity variables like co-occupation and developmental variables such as infant/toddler sensory processing/preferences, and it is important to understand the biopsychosocial mediators of these relations. These include novel genetic markers like maternal oxytocin receptor single-nucleotide polymorphisms (OXTR SNPs). Therefore, this study examined whether mothers carrying risk alleles for three OXTR SNPs displayed different co-occupational behaviors with their infants and whether their infants/toddlers showed different sensory processing/preferences. Methods: Data from the Infant Development and Healthy Outcomes in Mothers Study included prenatal saliva samples assayed for OXTR SNPs, 6-month postnatal behavioral observations coded for maternal–infant co-occupations (reciprocal emotionality, physicality, and intentionality), and 10-, 14-, and 18-month postnatal, maternal-reported Infant/Toddler Sensory Profiles (classified as within or outside the majority range for low registration, sensory seeking, sensory sensitivity, and sensory avoiding). Results: Mothers with rs53576 risk allele A engaged in more frequent reciprocal emotionality, while those with rs2254298 risk allele A engaged in less frequent reciprocal emotionality but more frequent reciprocal intentionality. Mothers with rs53576 risk allele A had infants with 11 times greater odds of being outside of the majority range for sensation avoiding at 10 months old. Conclusions: The results converge with the literature supporting links between OXTR SNPs, caregiver reciprocity, and infant/toddler development but extend the findings to relatively novel constructs (caregiver–infant co-occupations and infant/toddler sensory processing/preferences). Full article

Marker-less hand–eye calibration permits the acquisition of an accurate transformation between an optical sensor and a robot in unstructured environments. Single monocular cameras, despite their low cost and modest computation requirements, present difficulties for this purpose due to their incomplete correspondence of projected coordinates. In this work, we introduce a hand–eye calibration procedure based on the rotation representations inferred by an augmented autoencoder neural network. Learning-based models that attempt to directly regress the spatial transform of objects such as the links of robotic manipulators perform poorly in the orientation domain, but this can be overcome through the analysis of the latent space vectors constructed in the autoencoding process. This technique is computationally inexpensive and can be run in real time in markedly varied lighting and occlusion conditions. To evaluate the procedure, we use a color-depth camera and perform a registration step between the predicted and the captured point clouds to measure translation and orientation errors and compare the results to a baseline based on traditional checkerboard markers. Full article

Background: Current fiducial markers (FMs) in external-beam radiotherapy (EBRT) for prostate cancer (PCa) cannot be positively visualized on magnetic resonance imaging (MRI) and create dose perturbation and significant imaging artifacts on computed tomography (CT) and MRI. We report our initial experience with clinical imaging of a novel multimodality FM, NOVA. Methods: We tested Gold Anchor [G-FM], BiomarC [carbon, C-FM], and NOVA FMs in phantoms imaged with kilovoltage (kV) X-rays, transrectal ultrasound (TRUS), CT, and MRI. Artifacts of the FMs on CT were quantified by the relative streak artifacts level (rSAL) metric. Proton dose perturbations (PDPs) were measured with Gafchromic EBT3 film, with FMs oriented either perpendicular to or parallel with the beam axis. We also tested the performance of NOVA-FMs in a patient. Results: NOVA-FMs were positively visualized on all 4 imaging modalities tested. The rSAL on CT was 0.750 ± 0.335 for 2-mm reconstructed slices. In F-tests, PDP was associated with marker type and depth of measurement (p < 10⁻⁶); at 5-mm depth, PDP was significantly greater for the G-FM (12.9%, p = 10⁻⁶) and C-FM (6.0%, p = 0.011) than NOVA (4.5%). EBRT planning with MRI/CT image co-registration and daily alignments using NOVA-FMs in a patient was feasible and reproducible. Conclusions: NOVA-FMs were positively visible and produced less PDP than G-FMs or C-FMs. NOVA-FMs facilitated MRI/CT fusion and identification of regions of interest. Full article

Augmented Reality (AR) technology visualizes virtual objects in the real environment, offering users an immersive experience that enhances their spatial perception of virtual objects. This makes AR an important tool for visualization in engineering, education, and gaming. The Unmanned Aerial Vehicles’ (UAVs’) low-altitude public air route (Skyroad) is a forward-looking virtual transportation infrastructure flying over complex terrain, presenting challenges for user perception due to its invisibility. In order to achieve a 3D and intuitive visualization of Skyroad, this paper proposes an AR visualization framework based on a physical sandbox. The framework consists of four processes: reconstructing and 3D-printing a sandbox model, producing virtual scenes for UAVs Skyroad, implementing a markerless registration and tracking method, and displaying Skyroad scenes on the sandbox with GPU-based occlusion handling. With the support of the framework, a mobile application called SkyroadAR was developed. System performance tests and user questionnaires were conducted on SkyroadAR; the results showed that our approachs to tracking and occlusion provided an efficient and stable AR effect for Skyroad. This intuitive visualization is recognized by both professional and non-professional users. Full article

Image-to-patient registration is a coordinate system matching process between real patients and medical images to actively utilize medical images such as computed tomography (CT) during surgery. This paper mainly deals with a markerless method utilizing scan data of patients and 3D data from CT images. The 3D surface data of the patient are registered to CT data using computer-based optimization methods such as iterative closest point (ICP) algorithms. However, if a proper initial location is not set up, the conventional ICP algorithm has the disadvantages that it takes a long converging time and also suffers from the local minimum problem during the process. We propose an automatic and robust 3D data registration method that can accurately find a proper initial location for the ICP algorithm using curvature matching. The proposed method finds and extracts the matching area for 3D registration by converting 3D CT data and 3D scan data to 2D curvature images and by performing curvature matching between them. Curvature features have characteristics that are robust to translation, rotation, and even some deformation. The proposed image-to-patient registration is implemented with the precise 3D registration of the extracted partial 3D CT data and the patient’s scan data using the ICP algorithm. Full article

The application of surgical navigation in oral and maxillo-facial surgery has been increasing over time. In fact, computer-assisted surgery provides real-time, precise, and accurate position and guidance during surgery. The purpose of our work is to introduce the evolution of surgical navigation in recent decades, describe some technical aspects of this technology, explore new possibilities of application of surgical navigation in oral surgery, and validate the accuracy of computer-assisted surgery. We included four patients in our sample who underwent virtual planning on the cone beam CT data set and surgical navigation using non-invasive fiducial markers. The first patient presented a dislocated orthodontic arch in the soft tissues of the cheek, while the other patients presented supernumerary and impacted dental elements. Among them, two patients were affected by craniofacial synostosis. We evaluated the accuracy of computer-assisted surgery, calculating the discrepancy between the real and virtual target. In all cases, the target registration error was less than or equal to 1 mm. We can affirm that surgical navigation is a valid tool to enhance oral surgery, guaranteeing an undoubted advantage in terms of the reliability and predictability of the results, especially in complex cases. Full article

Honglian type cytoplasmic male sterility (CMS) is one of the three known major CMS types of rice (Oryza sativa L.) commercially used in hybrid rice seed production. Hybrid rice generated by the Honglian type CMS is a special group of hybrid rice, having distinct agricultural characteristics. The main objective of the study was to screen out the Honglian hybrid rice adapted for growing in Pakistan based on desirable traits. Different Honglian-type hybrid rice varietieswere tested locally in different locations in Pakistan based on various desirabletraits. Three Honglian types of hybrids (HP1, HP2, HP3) performed well, had better agricultural traits and showed high yield potential over the check variety. Different qualitative and quantitative traits were studied to conclude the advantages of these varieties for Pakistani local adaptation evaluations. Forty-eight SSR markers were used to study the genetic diversities of the hybrids. Nine selected polymorphic SSR markers (RM-219, RM-236, RM-274, RM-253, RM-424, RM-567, RM-258, RM-481, RM-493) showed genetic variations among Honglian hybrid rice varieties through PCR analysis. In 2019 and 2020, the increment of the yield potential of HP1, HP2 and HP3 was better (+43.90%, +35.44%, +37.13% and +30.91%, +33.37%, +33.62%, respectively, in both years)than the check variety KSK-133. All the desirable traits were analyzed through Principal Component Analysis (PCA). The principal components with more than one eigenvalue showed more variability. The average variability of 74.78% was observed among genotypes and their desirable traits in both years. National Uniform Yield Trial (NUYT) and Distinctness, Uniformity, Stability (DUS) trials are being conducted under the supervision of National Coordinated Rice (NCR) and Federal Seed Certification and Registration Department (FSCRD), Government of Pakistan. In the 2020 trial, the average yield of 104 rice varieties/hybrids was 8608 kg/ha; HP1, HP2 and HP3 (8709 kg/ha, 8833 kg/ha, and 9338 kg/ha, respectively) were all higher than the average yield, and HP3 yield was higher than over check varieties (D-121, Guard-53). In the 2021 trial, the average yield of 137 varieties was 7616 kg/ha; the HP1 yield (7863 kg/ha) was higher than the average overcheck varieties/hybrids. Various qualitative and quantitative traits showed desirable genetic diversity among the rice hybrids. It was also observed that, under higher temperatures, the seeds setting rate of Honglian-type hybrid rice was stable, which is the guarantee for stable yield and rice production in Pakistan. Moreover, it was considerably better, suggesting that Honglian-type hybrid rice varieties can be grown in Pakistan because they are less risky under climate change, especially the global warming challenges. Full article

This study proposes a markerless Augmented Reality (AR) surgical framework for breast lesion removal using a depth sensor and 3D breast Computed Tomography (CT) images. A patient mesh in the real coordinate system is acquired through a patient 3D scan using a depth sensor for registration. The patient mesh on the virtual coordinate system is obtained by contrast-based skin segmentation in 3D mesh generated from breast CT scans. Then, the nipple area is detected based on the gradient in the segmented skin area. The region of interest (ROI) is set based on the detection result to select the vertices in the virtual coordinate system. The mesh on the real and virtual coordinate systems is first aligned by matching the center of mass, and the Iterative Closest Point (ICP) method is applied to perform more precise registration. Experimental results of 20 patients’ data showed 98.35 ± 0.71% skin segmentation accuracy in terms of Dice Similarity Coefficient (DSC) value, 2.79 ± 1.54 mm nipple detection error, and 4.69 ± 1.95 mm registration error. Experiments using phantom and patient data also confirmed high accuracy in AR visualization. The proposed method in this study showed that the 3D AR visualization of medical data on the patient’s body is possible by using a single depth sensor without having to use markers. Full article

Pedicle screw insertion is considered a complex surgery among Orthopaedics surgeons. Exclusively to prevent postoperative complications associated with pedicle screw insertion, various types of image intensity registration-based navigation systems have been developed. These systems are computation-intensive, have a small capture range and have local maxima issues. On the other hand, deep learning-based techniques lack registration generalizability and have data dependency. To overcome these limitations, a patient-specific hybrid 3D-2D registration principled framework was designed to map a pedicle screw trajectory between intraoperative X-ray image and preoperative CT image. An anatomical landmark-based 3D-2D Iterative Control Point (ICP) registration was performed to register a pedicular marker pose between the X-ray images and axial preoperative CT images. The registration framework was clinically validated by generating projection images possessing an optimal match with intraoperative X-ray images at the corresponding control point registration. The effectiveness of the registered trajectory was evaluated in terms of displacement and directional errors after reprojecting its position on 2D radiographic planes. The mean Euclidean distances for the Head and Tail end of the reprojected trajectory from the actual trajectory in the AP and lateral planes were shown to be 0.6–0.8 mm and 0.5–1.6 mm, respectively. Similarly, the corresponding mean directional errors were found to be ${4.9}^0$ and $2^0$. The mean trajectory length difference between the actual and registered trajectory was shown to be 2.67 mm. The approximate time required in the intraoperative environment to axially map the marker position for a single vertebra was found to be 3 min. Utilizing the markerless registration techniques, the designed framework functions like a screw navigation tool, and assures the quality of surgery being performed by limiting the need of postoperative CT. Full article

About 50% of melanomas harbour a BRAF mutation. Of these 50%, 10% have a V600K mutation. Although it is the second most common driver mutation after V600E, no specific studies have been conducted to identify a clinical and therapeutic gold standard for this patient subgroup. We analysed articles, including registrative clinical trials, to identify common clinical and biological traits of the V600K melanoma population, including different adopted therapeutic strategies. Melanoma V600K seems to be more frequent in Caucasian, male and elderly populations with a history of chronic sun damage and exposure. Prognosis is poor and no specific prognostic factor has been identified. Recent findings have underlined how melanoma V600K seems to be less dependent on the ERK/MAPK pathway, with a higher expression of PI3KB and a strong inhibition of multiple antiapoptotic pathways. Both target therapy with BRAF inhibitors + MEK inhibitors and immunotherapy with anti-checkpoint blockades are effective in melanoma V600K, although no sufficient evidence can currently support a formal recommendation for first line treatment choice in IIIC unresectable/IV stage patients. Still, melanoma V600K represents an unmet medical need and a marker of poor prognosis for cutaneous melanoma. Full article