Pixel-wise rational model for a structured light system

This Letter presents a novel structured light system model that effectively considers local lens distortion by pixel-wise rational functions. We leverage the stereo method for initial calibration and then estimate the rational model for each pixel. Our proposed model can achieve high measurement accuracy within and outside the calibration volume, demonstrating its robustness and accurac

Desarrollo e implementación de un perfilómetro óptico por triangulación láser

Profilometers are instruments commonly used in surface metrology tasks. These instruments play a key role in the industry, such as in manufacturing and quality assurance. However, conventional profilometry techniques require direct contact with the object. In this work, we developed a practical and low-cost optical profilometer for contactless profilometry. The proposed profilometer is based on a laser triangulation system. A laser spot is projected onto the surface of an object, which is captured by a camera. The images are processed to detect the laser spot's location and obtain the object's surface height through calibration. We designed and built the translation stage to process the object's surface. Finally, encouraging results show that the profilometer provides high accuracy with fast acquisition. © 2020 IEEE

Modeling a Structured Light System with Open-Source Software

We propose modeling a structured light system with open-source computer graphics software to perform experimental verifications independently of the physical system. Encouraging experimental results show the capabilities of the digital twin. © 2022 The Author(s

Method for large-scale structured-light system calibration

We propose a multi-stage calibration method for increasing the overall accuracy of a large-scale structured light system by leveraging the conventional stereo calibration approach using a pinhole model. We first calibrate the intrinsic parameters at a near distance and then the extrinsic parameters with a low-cost large-calibration target at the designed measurement distance. Finally, we estimate pixel-wise errors from standard stereo 3D reconstructions and determine the pixel-wise phase-to-coordinate relationships using low-order polynomials. The calibrated pixel-wise polynomial functions can be used for 3D reconstruction for a given pixel phase value. We experimentally demonstrated that our proposed method achieves high accuracy for a large volume: sub-millimeter within 1200(H) × 800 (V) × 1000(D) mm3

Fourier Transform Profilometry in LabVIEW

Fourier transform profilometry (FTP) is an established non-contact method for 3D sensing in many scientific and industrial applications, such as quality control and biomedical imaging. This phase-based technique has the advantages of high resolution and noise robustness compared to intensity-based approaches. In FTP, a sinusoidal grating is projected onto the surface of an object, the shape information is encoded into a deformed fringe pattern recorded by a camera. The object shape is decoded by calculating the Fourier transform, filtering in the spatial frequency domain, and calculating the inverse Fourier transform; afterward, a conversion of the measured phase to object height is carried out. FTP has been extensively studied and extended for achieving better slope measurement, better separation of height information from noise, and robustness to discontinuities in the fringe pattern. Most of the literature on FTP disregards the software implementation aspects. In this chapter, we return to the basics of FTP and explain in detail the software implementation in LabVIEW, one of the most used data acquisition platforms in engineering. We show results on three applications for FTP in 3D metrology

Skin color correction via convolutional neural networks in 3D fringe projection profilometry

Fringe Projection Profilometry (FPP) with Digital Light Projector technology is one of the most reliable 3D sensing techniques for biomedical applications. However, besides the fringe pattern images,often a color texture image is needed for an accurate medical documentation. This image may be acquired either by projecting a white image or a black image and relying on ambient light. Color Constancy is essential for a faithful digital record, although the optical properties of biological tissue make color reproducibility challenging. Furthermore, color perception is highly dependent on the illuminant. Here, we describe a deep learning-based method for skin color correction in FPP. We trained a convolutional neural network using a skin tone color palette acquired under different illumination conditions to learn the mapping relationship between the input color image and its counterpart in the sRGB color space. Preliminary experimental results demonstrate the potential for this approach

Three-dimensional multimodal medical imaging system based on freehand ultrasound and structured light

We propose a three-dimensional (3D) multimodal medical imaging system that combines freehand ultrasound and structured light 3D reconstruction in a single coordinate system without requiring registration. To the best of our knowledge, these techniques have not been combined as a multimodal imaging technique. The system complements the internal 3D information acquired with ultrasound with the external surface measured with the structured light technique. Moreover, the ultrasound probe’s optical tracking for pose estimation was implemented based on a convolutional neural network. Experimental results show the system’s high accuracy and reproducibility, as well as its potential for preoperative and intraoperative applications. The experimental multimodal error, or the distance from two surfaces obtained with different modalities, was 0.12 m

Detection and removal of dust artifacts in retinal images via sparse-based inpainting

Dust particle artifacts are present in all imaging modalities but have more adverse consequences in medical images like retinal images. They could be mistaken as small lesions, such as microaneurysms. We propose a method for detecting and accurately segmenting dust artifacts in retinal images based on multi-scale template-matching on several input images and an iterative segmentation via an inpainting approach. The inpainting is done through dictionary learning and sparse-based representation. The artifact segmentation is refined by comparing the original image to the initial restoration. On average, 90% of the dust artifacts were detected in the test images, with state-of-theart restoration results. All detected artifacts were accurately segmented and removed. Even the most challenging artifacts located on top of blood vessels were removed. Thus, ensuring the continuity of the retinal structures. The proposed method successfully detects and removes dust artifacts in retinal images, which could be used to avoid false-positive lesion detections or as an image quality criterion. An implementation of the proposed algorithm can be accessed and executed through a Code Ocean compute capsul

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030