Malaria detection through microscopic examination of stained blood smears is a diagnostic challenge that heavily relies on the expertise of trained microscopists. This paper presents an automated analysis method for detection and staging of red blood cells infected by the malaria parasite Plasmodium falciparum at trophozoite or schizont stage. Unlike previous efforts in this area, this study uses quantitative phase images of unstained cells. Erythrocytes are automatically segmented using thresholds of optical phase and refocused to enable quantitative comparison of phase images. Refocused images are analyzed to extract 23 morphological descriptors based on the phase information. While all individual descriptors are highly statistically different between infected and uninfected cells, each descriptor does not enable separation of populations at a level satisfactory for clinical utility. To improve the diagnostic capacity, we applied various machine learning techniques, including linear discriminant classification (LDC), logistic regression (LR), and k-nearest neighbor classification (NNC), to formulate algorithms that combine all of the calculated physical parameters to distinguish cells more effectively. Results show that LDC provides the highest accuracy of up to 99.7% in detecting schizont stage infected cells compared to uninfected RBCs. NNC showed slightly better accuracy (99.5%) than either LDC (99.0%) or LR (99.1%) for discriminating late trophozoites from uninfected RBCs. However, for early trophozoites, LDC produced the best accuracy of 98%. Discrimination of infection stage was less accurate, producing high specificity (99.8%) but only 45.0%-66.8% sensitivity with early trophozoites most often mistaken for late trophozoite or schizont stage and late trophozoite and schizont stage most often confused for each other. Overall, this methodology points to a significant clinical potential of using quantitative phase imaging to detect and stage malaria infection without staining or expert analysis.

Digital holography offers a unique method for studying microscopic objects using quantitative measurements of the optical phase delays of transmitted light. The optical phase may be integrated across the object to produce an optical volume measurement, a parameter related to dry mass by a simple scaling factor. While digital holography is useful for comparing the properties of microscopic objects, especially cells, we show here that quantitative comparisons of optical phase can be influenced by the focal plane of the measurement. Although holographic images can be refocused digitally using Fresnel propagation, ambiguity can result if this aspect is not carefully controlled. We demonstrate that microscopic objects can be accurately profiled by employing a digital refocusing method to analyze phase profiles of polystyrene microspheres and red blood cells.

Subthreshold micropulse yellow laser photocoagulation showed short-term efficacy in treating chronic CSC without retinal damage. However, prospective, randomized, and comparative large-scale studies are needed to evaluate the efficacy and safety of this treatment.

Plasmodium falciparum infection causes structural and biochemical changes in red blood cells (RBCs). To quantify these changes, we apply a novel optical technique, quantitative phase spectroscopy (QPS) to characterize individual red blood cells (RBCs) during the intraerythrocytic life cycle of P. falciparum. QPS captures hyperspectral holograms of individual RBCs to measure spectroscopic changes across the visible wavelength range (475–700 nm), providing complex information, i.e. amplitude and phase, about the light field which has interacted with the cell. The complex field provides complimentary information on hemoglobin content and cell mass, which are both found to dramatically change upon infection by P. falciparum. Hb content progressively decreases with parasite life cycle, with an average 72.2% reduction observed for RBCs infected by schizont-stage P. falciparum compared to uninfected cells. Infection also resulted in a 33.1% reduction in RBC’s optical volume, a measure of the cells’ non-aqueous components. Notably, optical volume is only partially correlated with hemoglobin content, suggesting that changes in other dry mass components such as parasite mass may also be assessed using this technique. The unique ability of QPS to discriminate individual healthy and infected cells using spectroscopic changes indicates that the approach can be used to detect disease.

FG-assisted augmented AMT was easily performed for repairing large corneal perforations. This surgical method was very helpful in stabilizing the wound in the early postoperative period.