Annual Review of Biomedical Engineering 

About: Annual Review of Biomedical Engineering is an academic journal published by Annual Reviews. The journal publishes majorly in the area(s): Medicine & Regenerative medicine. It has an ISSN identifier of 1523-9829. Over the lifetime, 430 publications have been published receiving 93956 citations. The journal is also known as: Annu Rev Biomed Eng & Annual reviews..

The effect of nanoparticle size, shape, and surface chemistry on biological systems.

Abstract: An understanding of the interactions between nanoparticles and biological systems is of significant interest. Studies aimed at correlating the properties of nanomaterials such as size, shape, chemical functionality, surface charge, and composition with biomolecular signaling, biological kinetics, transportation, and toxicity in both cell culture and animal experiments are under way. These fundamental studies will provide a foundation for engineering the next generation of nanoscale devices. Here, we provide rationales for these studies, review the current progress in studies of the interactions of nanomaterials with biological systems, and provide a perspective on the long-term implications of these findings.

Soft Lithography in Biology and Biochemistry

Abstract: ▪ Abstract Soft lithography, a set of techniques for microfabrication, is based on printing and molding using elastomeric stamps with the patterns of interest in bas-relief. As a technique for fabricating microstructures for biological applications, soft lithography overcomes many of the shortcomings of photolithography. In particular, soft lithography offers the ability to control the molecular structure of surfaces and to pattern the complex molecules relevant to biology, to fabricate channel structures appropriate for microfluidics, and to pattern and manipulate cells. For the relatively large feature sizes used in biology (≥50 μm), production of prototype patterns and structures is convenient, inexpensive, and rapid. Self-assembled monolayers of alkanethiolates on gold are particularly easy to pattern by soft lithography, and they provide exquisite control over surface biochemistry.

Deep Learning in Medical Image Analysis

Abstract: This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

Current methods in medical image segmentation.

Abstract: ▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by automating or facilitating the delineation of anatomical structures and other regions of interest. We present a critical appraisal of the current status of semiautomated and automated methods for the segmentation of anatomical medical images. Terminology and important issues in image segmentation are first presented. Current segmentation approaches are then reviewed with an emphasis on the advantages and disadvantages of these methods for medical imaging applications. We conclude with a discussion on the future of image segmentation methods in biomedical research.

Neural stimulation and recording electrodes.

Abstract: Electrical stimulation of nerve tissue and recording of neural electrical activity are the basis of emerging prostheses and treatments for spinal cord injury, stroke, sensory deficits, and neurological disorders. An understanding of the electrochemical mechanisms underlying the behavior of neural stimulation and recording electrodes is important for the development of chronically implanted devices, particularly those employing large numbers of microelectrodes. For stimulation, materials that support charge injection by capacitive and faradaic mechanisms are available. These include titanium nitride, platinum, and iridium oxide, each with certain advantages and limitations. The use of charge-balanced waveforms and maximum electrochemical potential excursions as criteria for reversible charge injection with these electrode materials are described and critiqued. Techniques for characterizing electrochemical properties relevant to stimulation and recording are described with examples of differences in the in vitro and in vivo response of electrodes.