Automated assembly inspection using a multiscale algorithm trained on synthetic images

Includes bibliographical references.An important part of a robust automated assembly process is an accurate and efficient method for the inspection of finished assemblies. This paper presents a novel multiscale assembly inspection algorithm that is used to detect errors in an assembled product. The algorithm is trained on synthetic images generated using the CAD model of the different components of the assembly. The CAD model guides the inspection algorithm through its training stage by addressing the different types of variations that occur during manufacturing and assembly. Those variations are classified into those that can affect the functionality of the assembled product and those that are unrelated to its functionality. Using synthetic images in the training process adds to the versatility of the technique by removing the need to manufacture multiple prototypes and control the lighting conditions. Once trained on synthetic images, the algorithm can detect assembly errors by examining real images of the assembled product. The effectiveness of the system is illustrated on a typical mechanical assembly.This work was supported by National Science Foundation grant number CDR 8803017 to the Engineering Research Center for Intelligent Manufacturing Systems, National Science Foundation grant number MIP93-00560, an AT&T Bell Laboratories PhD Scholarship, and the NEC corporation

Automated visual assembly inspection

Includes bibliographical references (pages 699-700).This chapter has discussed an intelligent assembly inspection system that uses a multiscale algorithm to detect errors in assemblies after the algorithm is trained on synthetic CAD images of correctly assembled products. It was shown how the CAD information of an assembly along with fast rendering techniques on specialized graphics machines can be used for the automation of the work-cell camera and light placement. The current emphasis in the manufacturing industry on concurrent engineering will only cause this integration between the CAD model of products and its manufacturing inspection to grow in value

Camera and light placement for automated assembly inspection

Includes bibliographical references.Visual assembly inspection can provide a low cost, accurate, and efficient solution to the automated assembly inspection problem, which is a crucial component of any automated assembly manufacturing process. The performance of such an inspection system is heavily dependent on the placement of the camera and light source. This article presents new algorithms that use the CAD model of a finished assembly for placing the camera and light source to optimize the performance of an automated assembly inspection algorithm. This general-purpose algorithm utilizes the component material properties and the contact information from the CAD model of the assembly, along with standard computer graphics hardware and physically accurate lighting models, to determine the effects of camera and light source placement on the performance of an inspection algorithm. The effectiveness of the algorithms is illustrated on a typical mechanical assembly.This work was supported by National Science Foundation grant number CDR 8803017 to the Engineering Research Center for Intelligent Manufacturing Systems, National Science Foundation grant number MIP93-00560, an AT&T Bell Laboratories PhD Scholarship, and the NEC Corporation

Population screening for glaucoma in UK : current recommendations and future directions

Funding Information: APK is funded by a UKRI Future Leaders Fellowship and an Alcon Research Institute Young Investigator Award.Effective population screening for glaucoma would enable earlier diagnosis and prevention of irreversible vision loss. The UK National Screening Committee (NSC) recently published a review that examined the viability, effectiveness and appropriateness of a population-based screening programme for primary open-angle glaucoma (POAG). In our article, we summarise the results of the review and discuss some future directions that may enable effective population screening for glaucoma in the future. Two key questions were addressed by the UK NSC review; is there a valid, accurate screening test for POAG, and does evidence exist that screening reduces morbidity from POAG compared with standard care. Six new studies were identified since the previous 2015 review. The review concluded that screening for glaucoma in adults is not recommended because there is no clear evidence for a sufficiently accurate screening test or for better outcomes with screening compared to current care. The next UK NSC review is due to be conducted in 2023. One challenge for POAG screening is that the relatively low disease prevalence results in too many false-positive referrals, even with an accurate test. In the future, targeted screening of a population subset with a higher prevalence of glaucoma may be effective. Recent developments in POAG polygenic risk prediction and deep learning image analysis offer potential avenues to identifying glaucoma-enriched sub-populations. Until such time, opportunistic case finding through General Ophthalmic Services remains the primary route for identification of glaucoma in the UK and greater public awareness of the service would be of benefit.Publisher PDFPeer reviewe

Residential area deprivation and risk of subsequent hospital admission in a British population: the EPIC-Norfolk cohort.

OBJECTIVES:To investigate whether residential area deprivation index predicts subsequent admissions to hospital and time spent in hospital independently of individual social class and lifestyle factors. DESIGN:Prospective population-based study. SETTING:The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) study. PARTICIPANTS:11 214 men and 13 763 women in the general population, aged 40-79 years at recruitment (1993-1997), alive in 1999. MAIN OUTCOME MEASURE:Total admissions to hospital and time spent in hospital during a 19-year time period (1999-2018). RESULTS:Compared to those with residential Townsend Area Deprivation Index lower than the average for England and Wales, those with a higher than average deprivation index had a higher likelihood of spending >20 days in hospital multivariable adjusted OR 1.18 (95% CI 1.07 to 1.29) and having 7 or more admissions OR 1.11 (95% CI 1.02 to 1.22) after adjustment for age, sex, smoking status, education, social class and body mass index. Occupational social class and educational attainment modified the association between area deprivation and hospitalisation; those with manual social class and lower education level were at greater risk of hospitalisation when living in an area with higher deprivation index (p-interaction=0.025 and 0.020, respectively), while the risk for non-manual and more highly educated participants did not vary greatly by area of residence. CONCLUSION:Residential area deprivation predicts future hospitalisations, time spent in hospital and number of admissions, independently of individual social class and education level and other behavioural factors. There are significant interactions such that residential area deprivation has greater impact in those with low education level or manual social class. Conversely, higher education level and social class mitigated the association of area deprivation with hospital usage

Towards modifying the genetic predisposition for glaucoma: An overview of the contribution and interaction of genetic and environmental factors

Glaucoma, the leading cause of irreversible blindness worldwide, is a complex human disease, with both genetic and environmental determinants. The availability of large-scale, population-based cohorts and biobanks, combining genotyping and detailed phenotyping, has greatly accelerated research into the aetiology of glaucoma in recent years. Hypothesis-free genome-wide association studies have furthered our understanding of the complex genetic architecture underpinning the disease, while epidemiological studies have provided advances in the identification and characterisation of environmental risk factors. It is increasingly recognised that the combined effects of genetic and environmental factors may confer a disease risk that reflects a departure from the simple additive effect of the two. These gene-environment interactions have been implicated in a host of complex human diseases, including glaucoma, and have several important diagnostic and therapeutic implications for future clinical practice. Importantly, the ability to modify the risk associated with a particular genetic makeup promises to lead to personalised recommendations for glaucoma prevention, as well as novel treatment approaches in years to come. Here we provide an overview of genetic and environmental risk factors for glaucoma, as well as reviewing the evidence and discussing the implications of gene-environment interactions for the disease

Motion-Capture-Enabled Software for Gestural Control of 3D Models

Current state-of-the-art systems use general-purpose input devices such as a keyboard, mouse, or joystick that map to tasks in unintuitive ways. This software enables a person to control intuitively the position, size, and orientation of synthetic objects in a 3D virtual environment. It makes possible the simultaneous control of the 3D position, scale, and orientation of 3D objects using natural gestures. Enabling the control of 3D objects using a commercial motion-capture system allows for natural mapping of the many degrees of freedom of the human body to the manipulation of the 3D objects. It reduces training time for this kind of task, and eliminates the need to create an expensive, special-purpose controller

Differentiating glaucoma from chiasmal compression using optical coherence tomography: the macular naso-temporal ratio

BACKGROUND/AIMS: The analysis of visual field loss patterns is clinically useful to guide differential diagnosis of visual pathway pathology. This study investigates whether a novel index of macular atrophy patterns can discriminate between chiasmal compression and glaucoma. METHODS: A retrospective series of patients with preoperative chiasmal compression, primary open-angle glaucoma (POAG) and healthy controls. Macular optical coherence tomography (OCT) images were analysed for the macular ganglion cell and inner plexiform layer (mGCIPL) thickness. The nasal hemi-macula was compared with the temporal hemi-macula to derive the macular naso-temporal ratio (mNTR). Differences between groups and diagnostic accuracy were explored with multivariable linear regression and the area under the receiver operating characteristic curve (AUC). RESULTS: We included 111 individuals (31 with chiasmal compression, 30 with POAG and 50 healthy controls). Compared with healthy controls, the mNTR was significantly greater in POAG cases (β=0.07, 95% CI 0.03 to 0.11, p=0.001) and lower in chiasmal compression cases (β=-0.12, 95% CI -0.16 to -0.09, p<0.001), even though overall mGCIPL thickness did not discriminate between these pathologies (p=0.36). The mNTR distinguished POAG from chiasmal compression with an AUC of 95.3% (95% CI 90% to 100%). The AUCs when comparing healthy controls to POAG and chiasmal compression were 79.0% (95% CI 68% to 90%) and 89.0% (95% CI 80% to 98%), respectively. CONCLUSIONS: The mNTR can distinguish between chiasmal compression and POAG with high discrimination. This ratio may provide utility over-and-above previously reported sectoral thinning metrics. Incorporation of mNTR into the output of OCT instruments may aid earlier diagnosis of chiasmal compression

The Relationships Between Skeletal Muscle Index and Bone Variables in a Group of Young Adults

International audienceThe purpose of this study was to investigate the relationships between skeletal muscle index (SMI) and bone variables in a group of young adults. Three hundred and thirty-five young adults (129 men and 206 women) whose ages ranged from 18 to 35 yr voluntarily participated in this study. Weight and height were measured, and body mass index (BMI) was calculated. Body composition, bone mineral content (BMC), bone mineral density (BMD), geometric indices of hip bone strength and trabecular bone score (TBS) were determined for each individual by Dual-energy X-ray absorptiometry (DXA). Appendicular skeletal mass (ASM, in kg) was calculated by summing the muscle masses of the 4 limbs, assuming that all nonfat and nonebone mass is skeletal muscle. Skeletal muscle index (SMI) was defined as ASM/height². In young men, SMI was positively correlated to WB BMC (r = 0.63; p < 0.001), WB BMD (r = 0.53; p < 0.001), L1-L4 BMC (r = 0.33; p < 0.001), L1-L4 BMD (r = 0.30; p < 0.001), L1-L4 TBS (r = 0.26; p < 0.01), TH BMC (r = 0.61; p < 0.001), TH BMD (r = 0.46; p < 0.001), FN BMC (r = 0.51; p < 0.001), FN BMD (r = 0.46; p < 0.001), FN cross-sectional area (CSA) (r = 0.56; p < 0.001), FN cross-sectional moment of inertia (CSMI) (r = 0.52; p < 0.001) and FN section modulus (Z) (r = 0.54; p < 0.001) but negatively correlated to FN strength index (SI) (r = -0.24; p < 0.01). In young women, SMI was positively correlated to WB BMC (r = 0.61; p < 0.001), WB BMD (r = 0.60; p < 0.001), L1-L4 BMC (r = 0.35; p < 0.001), L1-L4 BMD (r = 0.33; p < 0.001), L1-L4 TBS (r = 0.29; p < 0.001), TH BMC (r = 0.61; p < 0.001), TH BMD (r = 0.53; p < 0.001), FN BMC (r = 0.45; p < 0.001), FN BMD (r = 0.49; p < 0.001), FN CSA (r = 0.60; p < 0.001), FN CSMI (r = 0.52; p < 0.001), and FN Z (r = 0.40; p < 0.001) but negatively correlated to FN SI (r = -0.20; p < 0.01). The current study suggests that SMI is a positive determinant of bone mineral density and geometric indices of hip bone strength in young adults