Immunofluorescence imaging as a tool for studying the pharmacokinetics of a human monoclonal single chain fragment antibody

Histology image analysis for carcinoma detection and grading

This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems.

Fluorescent peptide probes for in vivo diagnostic imaging

Recently, many novel peptide-based near-infrared (NIR) fluorescent molecular probes have been developed for in vivo biomedical imaging. To report specific information of biological targets, the probes were individually designed according to the unique property or functions of their targets. These peptide-based probes can be classified into targeting, crosslinking, and enzyme-activatable probes. Several of them have been tested in various in vitro and in vivo models, and the obtained imaging information has been applied to disease detection, medical diagnosis, and drug evaluations.