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3D phase imaging recovers an object’s volumetric refractive index from intensity and/or holographic measurements. Partially coherent methods, such as illumination-based differential phase contrast (DPC), are particularly simple to implement in a commercial brightfield microscope. 3D DPC acquires images at multiple focus positions and with different illumination source patterns in order to reconstruct 3D refractive index. Here, we present a practical extension of the 3D DPC method that does not require a precise motion stage for scanning the focus and uses optimized illumination patterns for improved performance. The user scans the focus by hand, using the microscope’s focus knob, and the algorithm self-calibrates the axial position to solve for the 3D refractive index of the sample through a computational inverse problem. We further show that the illumination patterns can be optimized by an end-to-end learning procedure. Combining these two, we demonstrate improved 3D DPC with a commercial microscope whose only hardware modification is LED array illumination.

3D differential phase contrast (3D DPC) microscopy uses asymmetric illumination patterns and axial scanning to recover volumetric maps of refractive index. To avoid the expense of automated axial scanning, we demonstrate 3D DPC without a z-stage by hand spinning the microscope’s defocus knob to scan the object axially while updating illumination patterns on the LED-array microscope. We utilize an inverse problem optimization to retrieve the sample’s volumetric information with measurements from unknown axial positions by jointly solving for each measurement’s axial position. Finally, we explore how to optimize the LED-array illumination patterns for varying axial sampling rates.

Phase imaging provides quantitative structural data about biological samples as an alternative or complementary contrast method to the functional information given by fluorescence imaging. In certain cases, fluorescence imaging is undesirable because it may harm the development of living cells or add time and complexity to imaging pipelines. However, current 3D phase reconstruction methods, such as optical diffraction tomography [1], are often limited to a single-scattering approximation. This limits the amount of scattering that such 3D reconstruction algorithms can successfully handle, and therefore effectively limits the sample thickness that can be successfully reconstructed. More recent methods such as 3D Fourier ptychographic microscopy (FPM) have used intensity-only images combined with multiple-scattering models in order to reconstruct 3D volumes [2]. In practice, however, continuous biological samples on the order of 100 um thick are not well-reconstructed by 3D FPM, due to a lack of diverse information across the volume which creates an ill-posed inverse problem. To mitigate this, we introduce simultaneous detection coding in the form of pupil control to the 3D FPM capture scheme. Simple pupil coding schemes enabled us to capture diverse information across our volume. In concert with a beam propagation model that takes into account multiple scattering, this combination of illumination- and detection-side coding allows us to more stably reconstruct 3D phase for larger-scale biological samples. [1] E. Wolf, “Three-dimensional structure determination of semi-transparent objects from holographic data,” Opt. Commun. 1, 153–156 (1969). [2] L. Tian and L. Waller, “3D intensity and phase imaging from light field measurements in an LED array microscope,” Optica, 2, 104-111 (2015).

3D imaging methods are limited in accuracy, depth, and resolution when ap plied to thick, multiply-scattering biological samples. We introduce pupil coding in conjunction with illumination coding for 3D Fourier ptychography, resulting in improved reconstruction of large clusters of cells.

The revolution in low-cost consumer photography and computation provides fertile opportunity for a disruptive reduction in the cost of biomedical imaging. Conventional approaches to low-cost microscopy are fundamentally restricted, however, to modest field of view (FOV) and/or resolution. We report a low-cost microscopy technique, implemented with a Raspberry Pi single-board computer and color camera combined with Fourier ptychography (FP), to computationally construct 25-megapixel images with sub-micron resolution. New image-construction techniques were developed to enable the use of the low-cost Bayer color sensor, to compensate for the highly aberrated re-used camera lens and to compensate for misalignments associated with the 3D-printed microscope structure. This high ratio of performance to cost is of particular interest to high-throughput microscopy applications, ranging from drug discovery and digital pathology to health screening in low-income countries. 3D models and assembly instructions of our microscope are made available for open source use.

Fourier ptychography captures intensity images with varying source patterns (illumination angles) in order to computationally reconstruct large space-bandwidth-product images. Accurate knowledge of the illumination angles is necessary for good image quality; hence, calibration methods are crucial, despite often being impractical or slow. Here, we propose a fast, robust, and accurate self-calibration algorithm that uses only experimentally-collected data and general knowledge of the illumination setup. First, our algorithm makes a direct estimate of the brightfield illumination angles based on image processing. Then, a more computationally-intensive spectral correlation method is used inside the iterative solver to further refine the angle estimates of both brightfield and darkfield images. We demonstrate our method for correcting large and small misalignment artifacts in both 2D and 3D Fourier ptychography with different source types: an LED array, a galvo-steered laser, and a high-NA quasi-dome LED illuminator., 8 pages, 7 figures

We present a microscope system for high-resolution complex-field tomography from intensity-only measurements with illumination angle scanning. Preliminary results using a multi-slice framework show promise in visualizing the 3D structure of a cluster of 3 µm transparent microspheres.

This article summarizes presentations at Sculpted Light in the Brain 2017.

Microscope lenses can have either large field of view (FOV) or high resolution, not both. Computational microscopy based on illumination coding circumvents this limit by fusing images from different illumination angles using nonlinear optimization algorithms. The result is a Gigapixel-scale image having both wide FOV and high resolution. We demonstrate an experimentally robust reconstruction algorithm based on a 2nd order quasi-Newton's method, combined with a novel phase initialization scheme. To further extend the Gigapixel imaging capability to 3D, we develop a reconstruction method to process the 4D light field measurements from sequential illumination scanning. The algorithm is based on a ‘multi-slice’ forward model that incorporates both 3D phase and diffraction effects, as well as multiple forward scatterings. To solve the inverse problem, an iterative update procedure that combines both phase retrieval and ‘error back-propagation’ is developed. To avoid local minimum solutions, we further develop a novel physical model-based initialization technique that accounts for both the geometric-optic and 1st order phase effects. The result is robust reconstructions of Gigapixel 3D phase images having both wide FOV and super resolution in all three dimensions. Experimental results from an LED array microscope were demonstrated.

We demonstrate an inexpensive programmable color LED array illuminator with 0.98 numerical aperture (NA), coupled with an auto-calibration procedure, to enable a simple and efficient setup for high-angle Fourier Ptychography in a commercial microscope.

Accurate and fast simulation of light propagating through 3D biological cells is important to the development of new computational imaging systems. We compare the finite-difference time-domain (FDTD), multislice, first Born approximation, and series-expanded Born (SEAGLE) simulation methods.

Purpose – The purpose of this paper is to examine the challenges that health care organizations face in nurturing and sustaining cultures that ensure the delivery of continually improving, high quality and compassionate care for patients and other service users. Design/methodology/approach – Based on an extensive review of the literature, the authors examine the current and very challenging context of health care and highlight the core cultural elements needed to enable health care organizations to respond effectively to the challenges identified. Findings – The role of leadership is found to be critical for nurturing high-quality care cultures. In particular, the authors focus on the construct of collective leadership and examine how this type of leadership style ensures that all staff take responsibility for ensuring high-quality care for patients. Practical implications – Climates for quality and safety can be accomplished by the development of strategies that ensure leaders, leadership skills and leadership cultures are appropriate to meet the challenges health care organizations face in delivering continually improving, high quality, safe and compassionate patient care. Originality/value – This paper provides a comprehensive integration of research findings on how to foster quality and safety climates in healthcare organizations, synthesizing insights from academic literature, practitioner reports and policy documents to propose clear, timely and much needed practical guidelines for healthcare organizations both nationally and internationally.

Optical diffraction tomography (ODT) reconstructs a samples volumetric refractive index (RI) to create high-contrast, quantitative 3D visualizations of biological samples. However, standard implementations of ODT use interferometric systems, and so are sensitive to phase instabilities, complex mechanical design, and coherent noise. Furthermore, their reconstruction framework is typically limited to weakly-scattering samples, and thus excludes a whole class of multiple-scattering samples. Here, we implement a new 3D RI microscopy technique that utilizes a computational multi-slice beam propagation method to invert the optical scattering process and reconstruct high-resolution (NA>1.0) 3D RI distributions of multiple-scattering samples. The method acquires intensity-only measurements from different illumination angles, and then solves a non-linear optimization problem to recover the sample 3D RI distribution. We experimentally demonstrate reconstruction of samples with varying amounts of multiple scattering: a 3T3 fibroblast cell, a cluster of C. elegans embryos, and a whole C. elegans worm, with lateral and axial resolutions of 250 nm and 900 nm, respectively., 24 pages, 8 figures

As leadership development becomes prevalent around the world, it is critical to understand the expectations and needs of participants attending leadership development programs and whether cross-country differences exist in those needs. This study examines the leadership challenges faced by 763 participants of leadership development programs from seven different countries (China/Hong Kong, Egypt, India, Singapore, Spain, the United Kingdom, and the United States) and evaluates how important they perceive certain leadership competencies are to success in their respective organization. Qualitative data reveal that the challenges leaders face are relatively similar across countries, although small variations exist. Developing Managerial Effectiveness, Inspiring Others, Developing Employees, Leading a Team, Guiding Change, and Managing Internal Stakeholders and Politics were challenges that ranked consistently among the top challenges in each country. Quantitative data from the same sample showed that the leadership competencies of Leading Employees, Resourcefulness, and Change Management were consistently seen as being important to success in managers’ organizations in all countries. Teaching managers to overcome the aforementioned challenges, and enhancing the previously mentioned competencies, is likely to contribute to the effectiveness of leadership development programs and initiatives independently of the country in which the manager resides. Both qualitative and quantitative data suggest cultural convergence when it comes to the needs of participants in leadership development programs around the world. Implications of findings for participant-focused leadership development and practical executive education are discussed.

Multisource feedback instruments are a widely used tool in human resource management. However, comprehensive validation studies remain scarce and there is a lack of statistical models that account appropriately for the complex data structure. Because both peers and subordinates are nested within the target but stem from different populations, the assumption of traditional multilevel structural equation models that the sample on a lower level stems from the same population is violated. We present a multilevel confirmatory factor analysis multitrait–multimethod (ML–CFA–MTMM) model that considers this peculiarity of multisource feedback instruments. The model is applied to 2 scales of the Benchmarks® instrument and it is demonstrated how measures of reliability and of convergent and discriminant validity can be obtained using multilevel structural equation modeling software. We discuss the results as well as some implications and guidelines for the use of the model.

Fourier ptychography is a computational illumination method for gigapixel-scale reconstruction of high-resolution phase and amplitude information from low-resolution images. We describe an algorithmic self-calibration method for illumination angles and apply it to a dual-axis galvo system with laser illumination.

We agree with Holt and Seki (2012) that tools for assessing and developing leaders have not kept up with the paradoxical realities faced today by global leaders. One such reality is that coworkers from different parts of the world have different mental models of what effective leadership entails. The same leadership characteristic or behavior can be seen as effective in one context and ineffective in another. This is particularly salient in today’s organizational context with global leaders working across cultures. But what if assessments for global leaders could take this fact into account? This is what we have been exploring, an approach to assess and develop leaders that is grounded in information-categorization theories of leadership, such as implicit leadership theories (ILTs; Lord & Maher, 1991), and the organizational fit or congruence literature (e.g., Ostroff & Judge, 2007) from the domain of organizational behavior. Applying ILTs and fit to the practice of 360-degree feedback moves the field away from the traditional approaches of assessing leadership that assume one set of global skills or abilities exists and that a certain optimum level of competence is needed for effective leadership. We believe that such an optimum is not objective, not even intersubjective, but that leadership is ‘‘in the eye of the beholder.’’ This ILT approach

PurposeThe move of organizations towards corporate global responsibility (CGR) is often a major change process that requires leadership throughout the organization. Despite an array of studies on managerial competencies in this area, previous research on leadership for CGR has not studied the actual leadership practices that are employed in a company's journey to CGR. The paper aims to fill this gap and to show how leadership for CGR is enacted by individuals and organizations that are highly successful CGR leaders.Design/methodology/approachThe paper uses a comparative case‐study approach of five multinational companies that are recognized as industry leaders for CGR. A total of 54 semi‐structured interviews with senior managers were complemented by ten focus groups and an examination of company reports, value charters and mission statements. Interviews as the main source of information were double‐coded in a three‐step process with the goal of knowledge development.FindingsThe paper identifies eight interrelated categories of leadership practices for global responsibility: developing CGR vision, strategy, and goals; integrating CGR into business decisions and operations; top management role modeling of CGR; engaging across boundaries; employee development and empowerment; systematic communication about CGR; developing accountability for CGR; and visible integrity in management behavior and decision making.Practical implicationsThe findings suggest that focusing on these leadership practices helps organizations build a strong leadership culture that is supportive of CGR.Originality/valueThe examination of actual leadership practices on multiple levels complements the existing knowledge on individual management competencies that are useful for driving CGR in organizations.

360-degree feedback from a variety of rater sources yields important information about leaders' styles, strengths and weaknesses for development. Results where observer ratings are discrepant (i.e., different) from self-ratings are often seen as indicators of problematic leadership relationships, skills, or lack of self-awareness. Yet research into the antecedents of such self-observer rating discrepancy suggests the presence of systematic influences, such as cultural values. The present study investigates the variation of rating discrepancies on three leadership skills (decision making, leading employees, and composure) in dependence of one exemplary culture dimension (power distance) on data from 31 countries using multilevel structural equation modelling. Results show that cultural values indeed predict self-observer rating discrepancies. Thus, systemic and contextual influences such as culture need to be taken into consideration when interpreting the importance and meaning of self-observer rating discrepancies in 360-degree instruments.