Deep-learning methods for computational pathology require either manual annotation of gigapixel whole-slide images (WSIs) or large datasets of WSIs with slide-level labels and typically suffer from poor domain adaptation and interpretability. Here we...
BACKGROUND: To effectively detect and investigate various cell-related diseases, it is essential to understand cell behaviour. The ability to detection mitotic cells is a fundamental step in diagnosing cell-related diseases. Convolutional neural netw...
Fourier ptychographic microscopy is a promising imaging technique which can circumvent the space-bandwidth product of the system and achieve a reconstruction result with wide field-of-view (FOV), high-resolution and quantitative phase information. Ho...
Detection of cells and particles in microscopy images is a common and challenging task. In recent years, detection approaches in computer vision achieved remarkable improvements by leveraging deep learning. Microscopy images pose challenges like smal...
Environmental science and pollution research international
Feb 22, 2021
Rapid environmental microorganism (EM) classification under microscopic images would help considerably identify water quality. Because of the development of artificial intelligence, a deep convolutional neural network (CNN) has become a major solutio...
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Feb 17, 2021
Structured illumination microscopy (SIM) is widely used in biological imaging for its high resolution, fast imaging speed, and simple optical setup. However, when imaging thick samples, the structured illumination patterns in SIM will suffer from opt...
Crown-like structures (CLSs) are adipose microenvironments of macrophages engulfing adipocytes. Their histological density in visceral adipose tissue (VAT) predicts metabolic disorder progression in obesity and is believed to initiate obesity comorbi...
We present sensing time-lapse morphogenesis of living bone cells under micro-fluidic shear stress (FSS) by digital holographic (DH) microscopy. To remove the effect of aberrations on quantitative measurements, we propose a numerical and automatic met...
Light-field microscopy has emerged as a technique of choice for high-speed volumetric imaging of fast biological processes. However, artifacts, nonuniform resolution and a slow reconstruction speed have limited its full capabilities for in toto extra...
One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed. In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM imag...
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