Hierarchical pose estimation for human gait analysis.

Articulated structures like the human body have many degrees of freedom. This makes an evaluation of the configuration's likelihood very challenging. In this work we propose new linked hierarchical graphical models which are able to efficiently evaluate likelihoods of articulated structures by sharing visual primitives. Instead of evaluating all configurations of the human body separately we take advantage of the fact that different configurations of the human body share body parts, and body parts, in turn, share visual primitives. A hierarchical Markov random field is used to integrate the sharing of visual primitives in a probabilistic framework. We propose a scalable hierarchical representation of the human body and show that this representation is especially well suited for human gait analysis from a frontal camera perspective. Furthermore, the results of the evaluation on a gait dataset show that sharing primitives substantially accelerates the evaluation and that our hierarchical probabilistic framework is a robust method for scalable detection of the human body.

Monitoring systems for the support of home care.

In this article, the design of a system for the ambient, unobtrusive and automatic monitoring of Activities of Daily Living (ADL) is described. In the context of the growing imbalance between (potentially young) caregivers and (most often older) people receiving care, technical monitoring systems may help to organise care more efficiently and to identify degrading abilities very early to trigger preventive measures. To improve the acceptance of the system described in this article, the selection process of the sensors to be integrated into the flat or to be worn by the older people has been steered by the results of focus group interviews with older people, their relatives and professional caregivers. The interviews revealed that these people would in general accept such systems, but security, mobility and communication aspects have to be clearly and appropriately addressed. In an experimental study the recognition rate of the activity 'preparation and intake of food or beverages' has been measured with two age groups (6 subjects, age between 25 and 40/mean 30 years and 5 subjects, age between 72 and 84/mean 75.3 years). The food preparation was detected with a sensitivity of 74.7% and a specificity of 84.2% using a vision sensor.

Automatic registration of serial sections of mouse lymph node by using Image-Reg.

The first step towards the three-dimensional (3D) reconstruction of histological structures from serial sectioned tissue blocks is the proper alignment of microscope image sequences. We have accomplished an automatic rigid registration program, named Image-Reg, to align serial sections from mouse lymph node and Peyer's patch. Our approach is based on the calculation of the pixel-correlation of objects in adjacent images. The registration process is mainly divided into two steps. Once the foreground images have been segmented from the original images, the first step (primary alignment) is performed on the binary images of segmented objects; this process includes rotation by using the moments and translation through the X, Y axes by using the centroid. In the second step, the matching error of two binary images is calculated and the registration results are refined through multi-scale iterations. In order to test the registration performance, Image-Reg has been applied to an image and its transformed (rotated) version and subsequently to an image sequence of three serial sections of mouse lymph node. In addition, to compare our algorithm with other registration methods, three other approaches, viz. manual registration with Reconstruct, semi-automatic landmark registration with Image-Pro Plus and the automatic phase-correlation method with Image-Pro Plus, have also been applied to these three sections. The performance of our program has been also tested on other two-image data sets. These include: (a) two light microscopic images acquired by the automatic microscope (stitched with other software); (b) two images fluorescent images acquired by confocal microscopy (tiled with other software). Our proposed approach provides a fast and accurate linear alignment of serial image sequences for the 3D reconstruction of tissues and organs.

Six-color segmentation of multicolor images in the infection studies of Listeria monocytogenes.

Multiple immunofluorescent staining is a powerful strategy for visualizing the spatial and temporal relationship between antigens, cell populations, and tissue components in histological sections. To segment different cell populations from the multicolor image generated by immunostaining based on color addition theory, a systems approach is proposed for automatic segmentation of six colors. After image acquisition and processing, images are automatically segmented with the proposed approach and six-pseudo channels for individual or colocalized fluorescent dye are generated to distinguish different cell types. The principle of this approach is the classification of each pixel into one of six colors (red, green, blue, yellow, magenta, and cyan) by choosing the minimal angular deviation between the RGB vector of the given pixel and six classically defined edge vectors. In the present infection studies of Listeria monocytogenes, the new multicolor staining methods based on the color addition were applied and the proposed color segmentation was performed for multicolor analysis. Multicolor analysis was accomplished to study the migration and interaction of Listeria and different cell subpopulations such as CD4CD25 double positive T regulatory cells; we also visualized simultaneously the B cells, T cells, dendritic cells, macrophages, and Listeria in another experiment. After Listeria infection, ERTR9 macrophages and dendritic cells formed cluster with Listeria in the infection loci. The principle of color addition and the systems approach for segmentation may be widely applicable in infection and immunity studies requiring multicolor imaging and analysis. This approach can also be applied for image analysis in the multicolor in vivo imaging, multicolor FISH or karyotyping or other studies requiring multicolor analysis.

Use of Autostitch for automatic stitching of microscope images.

Image stitching is the process of combining multiple images to produce a panorama or larger image. In many biomedical studies, including those of cancer and infection, the use of this approach is highly desirable in order to acquire large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we describe the application of Autostitch, viz. software that is normally used for the generation of panoramas in photography, in the seamless stitching of microscope images. First, we tested this software on image sets manually acquired by normal light microscopy and compared the performance with a manual stitching approach performed with Paint Shop Pro. Secondly, this software was applied to an image stack acquired by an automatic microscope. The stitching results were then compared with that generated by a self-programmed rectangular tiling macro integrated in Image J. Thirdly, this program was applied in the image stitching of images from electron microscopy. Thus, the automatic stitching program described here may find applications in convenient image stitching and virtual microscopy in the biomedical research.

Six-colour fluorescent imaging of lymphoid tissue based on colour addition theory.

Multi-colour imaging of immunofluorescently labelled tissue using confocal microscopy was accomplished by using colour addition theory. This new technique includes several improvements for immunolabelling: (1) the co-localization of two or more markers on one cell for the identification of specific cell populations; (2) the co-localization of two fluorescent dyes from secondary reagents for the identification of the cells; (3) a multi-step staining protocol with two primary antibodies originating from the same host species or with two or three biotin-conjugated primary antibodies. After image acquisition, colour segmentation/unmixing are applied to the single multi-colour image to generate multi-pseudo-channels for individual or co-localized fluorescent dyes. With this new technique, we have been able to visualize six cell populations simultaneously in the mouse lymph node and intestine. The efficiency of this method has also been demonstrated in the three-dimensional reconstruction of thick sections from mouse ileum. Our method is simple, efficient, and may be indispensable in experimental cell and tissue studies requiring multiple immunolabelling.