Fully automatic segmentation of craniomaxillofacial CT scans for computer-assisted orthognathic surgery planning using the nnU-Net framework

Objectives To evaluate the performance of the nnU-Net open-source deep learning framework for automatic multi-task segmentation of craniomaxillofacial (CMF) structures in CT scans obtained for computer-assisted orthognathic surgery. Methods Four hundred and fifty-three consecutive patients having undergone high-definition CT scans before orthognathic surgery were randomly distributed among a training/validation cohort (n = 300) and a testing cohort (n = 153). The ground truth segmentations were generated by 2 operators following an industry-certified procedure for use in computer-assisted surgical planning and personalized implant manufacturing. Model performance was assessed by comparing model predictions with ground truth segmentations. Examination of 45 CT scans by an industry expert provided additional evaluation. The model's generalizability was tested on a publicly available dataset of 10 CT scans with ground truth segmentations of the mandible. Results In the test cohort, mean volumetric Dice Similarity Coefficient (vDSC) & surface Dice Similarity Coefficient at 1mm (sDSC) were 0.96 & 0.97 for the upper skull, 0.94 & 0.98 for the mandible, 0.95 & 0.99 for the upper teeth, 0.94 & 0.99 for the lower teeth and 0.82 & 0.98 for the mandibular canal. Industry expert segmentation approval rates were 93% for the mandible, 89% for the mandibular canal, 82% for the upper skull, 69% for the upper teeth and 58% for the lower teeth. Conclusion While additional efforts are required for the segmentation of dental apices, our results demonstrated the model's reliability in terms of fully automatic segmentation of preoperative orthognathic CT scans.

Trends in the Enterprise Resource Planning Market Landscape

This article provides a brief discussion of ERPs, including how they can be defined, their component parts, and the evolution of technologies since the 1940s. The article then offers a general overview of the current ERP vendor market landscape based on academic journals and industry reports. The article’s methodological approach is a review of both academic literature and industry expert reports, which the author performed to trace trends within the landscape. Results of the analysis demonstrate that the rapidly evolving market landscape dates back at least six decades, and there are many large, longstanding ERP vendors. Yet, opportunities like cloud computing may result in niche products in existing industry players or through start-ups. Nonetheless, technologies such as blockchain are emerging. It remains to be seen how they will impact the ERP market.

Is corporate governance of private equity targets more effective for risk mitigation?

Private equity is a source of finance and a governance device characterised by active monitoring through sponsors that intervene in targets’ corporate governance. As sponsors are skilled and motivated acquirors, we investigated whether corporate governance mechanisms mitigate leveraged targets’ risk of financial distress differently compared to non-acquired companies through the lenses of agency theory and resource-based theories. We found that targets and non-acquired companies are not significantly different in terms of corporate governance features, but sponsors are skilled enough to choose corporate governance members to mitigate risk more, especially when boards are smaller, have busier industry expert directors, and mandate execution to more managers. These results can be useful to targets, targets’ investors and lenders, and policymakers.

Ownership structure and auditor selection

Purpose This paper aims to investigate the effect that ownership structure (public vs private) has on the demand for high-quality auditors, specifically in the US banking industry. Design/methodology/approach The authors predict that public banks are more likely to hire a high-quality auditor than private banks and pay a higher audit fee premium for that high-quality auditor (due to higher agency costs, more demand for financial information and higher litigation risk). The authors analyze 2008–2014 banking data from the Federal Reserve using probit and OLS regression analysis to examine if there is a higher probability that public banks choose higher quality auditors and pay higher audit fees when they do so. Findings The results show that private banks are less likely to hire Big 4 auditors and industry-expert auditors than public banks. The authors also find that both private and public banks pay higher audit fees for Big 4 and industry-expert auditors, and that public banks pay a higher premium for Big 4 auditors and industry experts than private banks. Research limitations/implications The findings may not be fully generalizable to other types of firms, as banking is a heavily regulated and complex industry. However, inferences from this study may be generalizable to other similar industries such as insurance or health care. Practical implications The results of this paper imply that public and private banks have differing priorities when hiring their financial statement auditor. This may be of interest to investors and auditing regulators. Social implications The findings of this paper underscore the value of hiring an industry-expert auditor in an industry that is highly complex and regulated. This may be of interest to managers and policymakers. Originality/value Due to data restrictions, the emphasis of prior literature on the banking industry has been on public banks. This study is the first to analyze the differences between public and private banks’ demand for audit services.

‘There is scope for optimism’

Dental industry expert Edmund Proffitt calls for a collaborative approach to the road to recovery

The Impact of Industry Expert Adjuncts on Students' Course Experiences

As a reality of modern higher education, the use of adjunct instructors to teach courses is a common practice, often viewed through institutional constraints. This paper uses a different lens to examine the experiences of students in courses taught by adjunct instructors who are primarily employed in industry. It explores the affordances these instructors bring into the classroom including timely knowledge and skills from outside the academic institution. This work is a methodological pilot in a longer design-based project studying industry expert adjuncts as college teachers by analyzing their impact through students' perceptions of their experiences.