This article is the first in a series relating to the application of microscopy to forensic science. As such, the article is intended to be purely introductory in nature. Future articles will be specific both as to the forensic challenge and the solution as allowed by the creative application of microscopy.

Microscopy has played an integral part in forensic science since the early part of this century. In 1928, E. Locard established the practical and theoretical underpinnings of the microscopic examination of trace amounts of evidence. The “exchange principle of evidence” was so developed:

Whenever two objects come into contact there is always a transfer of material. The methods of detection may not be sensitive enough to demonstrate this or the decay rate may be so rapid that all evidence of transfer has vanished after a given time. Nonetheless, the transfer has taken place.

Bright-field illumination is widely used as standard technique for examination of transparent specimens characterized by an appropriate optical density so that the transmitted light is partially absorbed when passing the specimens (for example, stained histological sections and blood smears). On the other hand, thin and colorless low-density specimens, such as unstained living cells that do not reduce the amplitude of the transmitted light, cannot be well perceived in bright field because of their ultra-low natural contrast. These so-called phase specimens can be examined when an apparatus for phase contrast is used. Phase contrast can be carried out with special objectives fitted with a phase ring situated within or near their back focal plane. Moreover, the condenser must be fitted with annular light masks (light annuli) that are projected onto the plane of the objective's phase ring so that both components, light annuli and phase rings, are optically congruent and conjugate.

Computer Microvision is a microscopy technique originally developed to study sound-induced motions of sensory cells in the inner ear - motions that are on the order of picometers-i.e., smaller than the radius of a hydrogen atom. Three-dimensional micrornovies of inner ear cells moving in response to sound were analyzed to quantify motions with nanometer precision. Recently we have adapted the technique for in situ measurement of motions of micro-electron mechanical (MEMS) devices.

In Computer Microvision systems, images of MEMS are magnified with an optical microscope and projected onto a CCD camera. Stroboscopic illumination is used to obtain stopaction images of the moving structures. Stop-action images from multiple focal planes provide information about 3D structure and 3D motion. Image analysis algorithms determine motions of all visible structures with nanometer accuracy. The system can measure motions at frequencies as high as 5 MHz with nanometer resolution, i.e., well below the wavelength of light.

In a recent microscopy discussion group, a correspondent questioned the use of a contrast enhancement method applied to a microscopy image for publication. What kinds of image processing, folk asked, are “acceptable” in a general sense? What kinds of image processing should be noted in the text or caption and what kind of images should be archived?

It is an interesting set of questions, and I face them wearing three hats, I am a forensic pathologist who performs forensic image interpretation in the investigation of homicide and assault, an anatomic pathologist with an interest in confocal microscopy, and a computer scientist with training in image processing and computer vision. Image processing is part and parcel of my everyday work. I use tools such as contrast enhancement, debarring, and photogrammetry for image interpretation. I build tools for visualization in my confocal work. I collaborate in the design of data acquisition devices for the evaluation of crime scenes and bodily injury.

A microscopist is presented with a special problem when asked to characterize a population of particles. In order to adequately describe the sample, it may be necessary to examine hundreds or even thousands of individual particles, recording the size, shape, identity or other parameters of interest. To manually characterize a statistically significant fraction of the sample could require many hours of tedious work at the scope, followed by still more tedious hours of data reduction. What is needed is a technique to automate the repetitive parts of this process; the recognition and characterization of particles in the sample and the reduction of data and presentation of results. This technique is automated particle analysis.

There are two principal techniques for obtaining diffraction patterns in the transmission electron microscope (TEM). They are selected-area diffraction (SAD) and convergent-beam diffraction (CBED). CBED is quicker and easier to use, and it provides a much richer characterization of the sample. Thus, it is clear that CBED should be used in the vast majority of cases. It should be the diffraction technique that students learn first, and students should be taught to consider it the standard method of doing diffraction in the TEM.

Historically, one of the first jobs performed by the new instrument called a “transmission electron microscope” (TEM) was the determination of particle size and distribution. Particle size is still important in controlling the properties of sub-micron and nanoparticle products. The width and average particle size can determine the light scattering properties of a pigment like TiO2, for example. The cost of installing a TEM facility and TEM sample preparation issues makes TEM analysis expensive and labor intensive. So decades ago, nitrogen BET (Brunauer, Emmett, and Teller) surface area determinations were used on sub-micron powders and pigments to minimize these costs. The BET measurement of the exposed external surface area of a material is made by detecting and measuring the amount of nitrogen given off after absorption, assuming one atomic layer of nitrogen is adsorbed.