Hyperspectral imaging (HSI) and multispectral imaging (MSI) technologies have the
potential to transform the fields of digital and computational pathology. Traditional digitized …

Rather than simply acting as a photographic camera capturing two‐dimensional (x, y)
intensity images or a spectrometer acquiring spectra (λ), a hyperspectral imager measures …

To solve the problem of supervised convolutional neural network (CNN) models suffering
from limited samples, a two-channel CNN is developed for medical hyperspectral images …

Autofluorescence of blood has been explored as a label free approach for detection of cell
types, as well as for diagnosis and detection of infection, cancer, and other diseases …

Hyperspectral imaging (HSI) techniques play an important role in the food industry for
providing rapid, nondestructive, and chemical‐free detection method, whereas a microscope …

We review how the hyperspectral dark field analysis gives us quantitative insights into the
manner that different nanoscale materials interact with their environment and how this …

Abstract Objective and Impact Statement. We propose a rapid and accurate blood cell
identification method exploiting deep learning and label-free refractive index (RI) …

Hematological analysis, via a complete blood count (CBC) and microscopy, is critical for
screening, diagnosing, and monitoring blood conditions and diseases but requires complex …

Observing and identifying blood cells is a direct way for early diagnosis of blood diseases.
Traditional blood cell recognition methods are usually time-consuming and laborious tasks …

Blood cell analysis is one of the standard clinical tests. Despite the widespread use of
exogenous markers for blood cell quantification, label-free optical methods are still of high …