ABSTRACT
Fourier ptychographic microscopy (FPM) needs to realize well-accepted reconstruction by image segmentation and discarding problematic data due to artifacts caused by vignetting. However, the imaging results have long suffered from uneven color blocks and the consequent digital stitching artifacts, failing to bring satisfying experiences to researchers and users over the past decade since the invention of FPM. In fact, the fundamental reason for vignetting artifacts lies in that the acquired data does not match the adopted linear-space-invariant (LSI) forward model, i.e., the actual object function is modulated by a quadratic phase factor during data acquisition, which has been neglected in the advancement of FPM. In this Letter, we rederive a linear-space-variant (LSV) model for FPM and design the corresponding loss function for FPM, termed LSV-FPM. Utilizing LSV-FPM for optimization enables the efficient removal of wrinkle artifacts caused by vignetting in the reconstruction results, without the need of segmenting or discarding images. The effectiveness of LSV-FPM is validated through data acquired in both 4f and finite conjugate single-lens systems.
ABSTRACT
Fourier ptychographic microscopy (FPM) emerged as a prominent imaging technique in 2013, attracting significant interest due to its remarkable features such as precise phase retrieval, expansive field of view (FOV), and superior resolution. Over the past decade, FPM has become an essential tool in microscopy, with applications in metrology, scientific research, biomedicine, and inspection. This achievement arises from its ability to effectively address the persistent challenge of achieving a trade-off between FOV and resolution in imaging systems. It has a wide range of applications, including label-free imaging, drug screening, and digital pathology. In this comprehensive review, we present a concise overview of the fundamental principles of FPM and compare it with similar imaging techniques. In addition, we present a study on achieving colorization of restored photographs and enhancing the speed of FPM. Subsequently, we showcase several FPM applications utilizing the previously described technologies, with a specific focus on digital pathology, drug screening, and three-dimensional imaging. We thoroughly examine the benefits and challenges associated with integrating deep learning and FPM. To summarize, we express our own viewpoints on the technological progress of FPM and explore prospective avenues for its future developments.
Subject(s)
Imaging, Three-Dimensional , Microscopy , Microscopy/methods , Prospective Studies , Fourier AnalysisABSTRACT
Among measures tackling the impacts of the COVID-19 pandemic, the selling of private insurance policies covering individual infection is overlooked by the ethics literature. To record the "COVID Claimania" in Taiwan and to assess its ethical implications, we collected 38 policies from 10 insurers sold between January 2020 and May 2022 and found that their risk calculation of the COVID-19 prevalence ranged from 0.5% to 11.08%. In reality, the prevalence by the end of 2022 was 37% in Taiwan. Selling private insurance policies is ethically problematic in three ways. First, it represents the insurance industry's irresponsible risk-taking profit-seeking behaviors. Second, it would jeopardize the effectiveness of the disease-prevention measures by inducing uncontrollable moral hazards. Third, it would expose the insurance companies to unbearable financial risks and cause substantial negative external impacts. The government should intervene in the private insurance market in preparation for future public health emergencies.