1,298 research outputs found
Modelling shape and parameterising style: an approach to the design of high-fashion shoe lasts
No full textA shoe's shape, captured by the shoe last, is designed based on the anatomical parameters of the foot. However, changing footwear fashions result in a variety of shapes and styles of last, which complicates the determination of ergonomic shoe forms. We propose a method for simple customisation of a shoe's style while retaining an ergonomic fit. 3D foot scans were used initialise the design of a shoe last based on the average foot shape of the target population. The shoe styles are then modelled as changes to the toe box, which is style dependent and thus, free to model, and the height of the heel lift, which is based on 3D geometric calculations linked to the anthropometric parameters of the foot. The proposed method was tested using consumer surveys. The results of the surveys showed an increase in comfort and satisfaction compared to shoe samples made with standard commercial lasts
Ki-67 is a PP1-interacting protein that organises the mitotic chromosome periphery
No full textCopyright @ 2014 Booth et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.When the nucleolus disassembles during open mitosis, many nucleolar proteins and RNAs associate with chromosomes, establishing a perichromosomal compartment coating the chromosome periphery. At present nothing is known about the function of this poorly characterised compartment. In this study, we report that the nucleolar protein Ki-67 is required for the assembly of the perichromosomal compartment in human cells. Ki-67 is a cell-cycle regulated protein phosphatase 1-binding protein that is involved in phospho-regulation of the nucleolar protein B23/nucleophosmin. Following siRNA depletion of Ki-67, NIFK, B23, nucleolin, and four novel chromosome periphery proteins all fail to associate with the periphery of human chromosomes. Correlative light and electron microscopy (CLEM) images suggest a near-complete loss of the entire perichromosomal compartment. Mitotic chromosome condensation and intrinsic structure appear normal in the absence of the perichromosomal compartment but significant differences in nucleolar reassembly and nuclear organisation are observed in post-mitotic cells
CAD WALK: Computer-Aided Diagnosis of Foot Problems using Metric Learning
No full textDr. Brian Booth, lead researcher in the CAD WALK project, was invited to speak at the Expert Group Antwerp Molecular Imaging (EGAMI) workshop at the University of Antwerp. EGAMI is a multi-disciplinary group at the University of Antwerp whose goal is to enable the translation of molecular imaging research into industrial applications. It is hoped that by enabling this research translation, EGAMI will help improve clinical diagnoses and patient health.
The topic of the workshop was "The Impact of Imaging Research" and the invited speakers introduced various avenues that can increase research impact. The most commonly-mentioned themes included valorisation (the translation of research into products and services) and public outreach. Speakers also discussed various funding opportunities that encourage these activities.
"The EU's Marie Curie Actions strongly encourage the transfer of research into products", says Booth. "They do so by requiring their projects to have an international, inter-sector, and interdisciplinary focus. In that way, CAD WALK is a decent example of how this can be done. That being said, the valorisation aspect of CAD WALK has yet to begin, so my advice is pretty limited there".
While Dr. Booth had little to add on the topic of valorisation, he was more adamant about the need for researchers to increase public outreach efforts. "It is hard to get the average person to support what you do if they don't know who you are, don't feel that you care about them, and don't see the effort that you're putting in", says Booth. "We have to make a better effort to be accessible, transparent, and understandable".</p
Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis
No full textAbstract: The high prevalence of foot pain, and its relation to foot shape, indicates the need for an expert system to identify foot shape abnormalities. Yet, to date, no such expert system exists that examines the full 3D foot shape and produces an intuitive explanation of why a foot is abnormal. In this work, we present the first such expert system that satisfies those goals. The system is based on the concept of model-based outlier detection: a statistical shape model (SSM) is generated from 186 3D optical foot scans of healthy feet. This model acts as a knowledge base which is then parameterized by one's demographic characteristics (e.g., age, weight, height, shoe size) through a multivariate regression. This regression introduces model flexibility as it allows the model to be fine tuned to a specific individual. This fine tuned model is then used as a baseline to which the individual's 3D foot scan can be compared using standard statistical tests (e.g. t-tests). These statistical tests are performed at each vertex along the foot surface to identify the degree and location of shape outliers. Our expert system was validated on foot scans from patients with hallux valgus and abnormal foot arches. As expected, our results varied per patient, confirming that feet with the same clinical classification still show high shape variability. Additionally, the foot shape abnormalities identified by our system not only agreed with the expected location and severity of the tested foot deformities, but our analysis of the full 3D foot shape was able to completely characterize the extent of those abnormalities for the first time. These results show that the combination of statistical shape modelling, multivariate regression, and statistical testing is powerful enough to perform outlier detection for 3D foot shapes. The resulting insights provided by this system could prove useful in both shoe design and clinical diagnosis. (C) 2020 Elsevier Ltd. All rights reserved
Statistical Shape and Pose Model of the Forearm for Custom Splint Design
No full textAbstract: Custom splint design is becoming more common. However, poor 3D scan quality can negatively impact the design accuracy. This paper describes a method to build a 3D statistical shape and pose model of the forearm from 3dMD scans. The model is used to assist the registration of previously unseen forearms in a wide range of poses. We show that this model-based surface registration results in a good geometric fit, with accurate anatomical correspondences. This method could be used to upgrade low-resolution scans using a high-resolution model
Outlier detection for foot complaint diagnosis : modeling confounding factors using metric learning
No full textAbstract: Diagnosing foot complaints using plantar pressure videos is complicated by the presence of confounding factors (e.g. age, weight). Outlier detection could help with diagnosis, but these confounding factors result in data that is not independent and identically distributed (IID) with respect to a specific patient. To address this non-IID problem, we propose the modeling of confounding factors using metric learning. A distance metric is learned on the confounding factors in order to model their impact on the plantar pressures. This metric is then employed to weight plantar pressures from healthy controls when generating a patient-specific statistical baseline. Statistical parametric mapping is then used to compare the patient to this statistical baseline. We show that using metric learning reduces variance in these statistical baselines, which then improves the sensitivity of the outlier detection. These improvements in outlier detection get us one step closer to accurate computer-aided diagnosis of foot complaints
Encoding Stability into Laser Powder Bed Fusion Monitoring Using Temporal Features and Pore Density Modelling
No full textIn laser powder bed fusion (LPBF), melt pool instability can lead to the development of pores in printed parts, reducing the part’s structural strength. While camera-based monitoring systems have been introduced to improve melt pool stability, these systems only measure melt pool stability in limited, indirect ways. We propose that melt pool stability can be improved by explicitly encoding stability into LPBF monitoring systems through the use of temporal features and pore density modelling. We introduce the temporal features, in the form of temporal variances of common LPBF monitoring features (e.g., melt pool area, intensity), to explicitly quantify printing stability. Furthermore, we introduce a neural network model trained to link these video features directly to pore densities estimated from the CT scans of previously printed parts. This model aims to reduce the number of online printer interventions to only those that are required to avoid porosity. These contributions are then implemented in a full LPBF monitoring system and tested on prints using 316L stainless steel. Results showed that our explicit stability quantification improved the correlation between our predicted pore densities and true pore densities by up to 42%
Andrew D. Booth – Britain’s Other “Fourth Man”
No full textInternational audienceAndrew Donald Booth (1918-2009) was the leader of a team of computer pioneers at Birkbeck College in the University of London, UK. Booth worked with limited resources, both human and financial, and concentrated on building smaller machines. This paper presents an outline of his career in the UK which, the author believes, has not received the attention it deserves in comparison to a number of his UK contemporaries
Towards material and process agnostic features for the classification of pore types in metal additive manufacturing
No full textThe manufacturing of metal parts via powder-bed fusion is often still facing quality issues due to microstructural porosity. Minimizing this porosity remains a priority and requires the optimization of printing process parameters. While the analysis of printed parts using X-ray computed tomography
can localize and identify the pore types (e.g. keyhole or lack-of-fusion pores), these pore types can be difficult to identify across printer settings and print materials. Therefore, there is a need for a material and process agnostic approach. This work presents such an approach by considering a set of geometric pore features that do not differ considerably across print scenarios. These features are then leveraged for supervised pore type classification. The distributions of pore features were analyzed in different materials and under varying laser parameters, showing that they behave in a generic way. For classification, it is observed that they outperform other features leveraged in the state-of-the-art for pore classification in a single material, reaching up to 93.0% accuracy. Additionally, accuracies up to 90.2% for cross-material classification were observed by training on pores of one material and validating on another. These results
pave the way to a general-purpose pore classification method usable across materials and process conditionssponsorship: imec ICON Vlaio|‘Vision in the Loop’ (HBC.2019.2808)status: Published onlin
Off-axis high-speed camera-based real-time monitoring and simulation study for laser powder bed fusion of 316L stainless steel
No full textsponsorship: Flanders Make|HBC.2019.2808status: Published onlin
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