Optical-resolution photoacoustic microscopy (OR-PAM) has been widely used for imaging blood vessel and oxygen saturation of hemoglobin (sO2), providing high-resolution functional images of living animals in vivo. However, most of them require one or multiple bulky and costly pulsed lasers, hindering their applicability in preclinical and clinical settings. In this paper, we demonstrate a reflection-mode low-cost high-resolution OR-PAM system by using two cost-effective and compact laser diodes (LDs), achieving microvasculature and sO2 imaging with a high lateral resolution of ∼6 µm. The cost of the excitation sources has dramatically reduced by ∼20–40 times compared to that of the pulsed lasers used in state-of-the-art OR-PAM systems. A blood phantom study was performed to show a determination coefficient R2 of 0.96 in linear regression analysis. Experimental results of in vivo mouse ear imaging show that the proposed dual-wavelength LD-based PAM system can provide high-resolution functional images at a low cost.
Hematologists evaluate alterations in blood cell enumeration and morphology to confirm the peripheral blood smear findings through manual microscopic examination. However, routine peripheral blood smear analysis is both time-consuming and labor-intensive. Here, we propose a smartphone-based autofluorescence microscopy (Smart-AM) system for imaging label-free blood smears at sub-cellular resolution and performing hematological analysis. Smart-AM enables rapid, high-quality, and label-free visualization of morphological features of different blood cells (leukocytes, erythrocytes, and thrombocytes) and abnormal variations in blood cells. Moreover, assisted with deep learning algorithms, this technique can automatically detect and classify different leukocytes with high accuracy, and transform the autofluorescence images into virtual Giemsa-stained images maintaining significant cellular features. The proposed technique is portable, cost-effective, and user-friendly, making it significant for broad point-of-care applications.
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