Nak H. Kim

Shape description of biological objects via stereo light microscopy

Computational stereo vision techniques are applied to the analysis of the three-dimensional (3-D) shape of biological specimens imaged through a stereo light microscope. 3-D shape descriptions are derived by integrating binocular and monocular measurements. Microscopic biological objects viewed through a light microscope generally have ill-defined boundaries in shape and reflectance and often exhibit transparency. In addition, the limited illumination available in the light microscope often makes it difficult to obtain images of sufficiently high contrast. In the approach presented, a new matching algorithm is introduced using intensity gradient information to solve the problem. Shape descriptions are computed by exploiting a number of additional processing steps. Two different classes of shapes are considered, which lead to two distinct approaches for 3-D analysis: solid objects and vascular networks. The first class of objects is described using a visible surface representation, while the second is expressed in terms of a set of space curves. The efficacy of each approach is demonstrated using microscopic-scale solid and microvascular specimens. >

A microcomputer-based vision system for area measurement

A vision system for measuring the area of an arbitrarily shaped object is described. The algorithm consists of a gray-level thresholding technique combined with a region correction procedure based on mathematical morphology. All processing steps are carried out on a microcomputer system equipped with a video digitizer. The algorithm has been successfully applied to a number of images of medical interest including skin wounds and various microscopic-scale objects such as cell cross-sections and multicellular tissues. Excellent agreement between results obtained by the automatic method and by using standard mechanical means has been established experimentally. The approach is demonstrated by a number of experimental examples.

3-D model of vascular network in rat skin obtained by stereo vision techniques.

The quantitative analysis of the depth of injury, penetration of therapeutic agents in tissues, and the regeneration of vascular patency after a graded degree of thermal injury requires a knowledge of the shape and spatial configuration of the vascular networks in the tissue. We have applied computational stereo vision techniques to describe the 3‐D configuration of microvessels in full thickness rat skin vascular casts produced by perfusion of Yellow Microfil latex solution through the aorta. The principal concern is to describe the 3‐D structure of vascular networks using a set of 3‐D space curves. This representation is computed by integrating monocular and binocular processing; the 2‐D curve representation of blood vessels computed through monocular analysis is integrated with disparity data to yield a space curve representation for each vessel. A connection diagram is also computed to indicate the connections existing among the computed space curve representations.

Computing 3-D symbolic representation of blood vessels from stereo-microscopic images

The authors consider the three-dimensional analysis of vacular networks from stereo-microscopic images. The principal concern is to describe their 3-D structure using a set of parametric space curves. This representation is computed by integrating monocular and binocular processing: the 2-D curve representation of blood vessels computed by monocular analysis is integrated with disparity data to yield a space curve representation. A connection graph is computed to indicate the connection among space curves. The efficacy of the approach was demonstrated using vascular cast images.<<ETX>>

Computing shape changes in SOLANUM tuberosa slices viewed through a stereo microscope

A research effort is described to compute the 3-D shape parameters of biological objects observed through a stereoscope light microscope. An algorithm for computing global shape parameters from microscopic images is presented. Algorithms for computation of global shape parameters from images obtained through a stereo light microscope are developed and applied to characterize the shape parameters of small piece of potato slices when exposed to hyperosmotic sugar solutions.<<ETX>>