Olivier Cros

Structural analysis of micro-channels in human temporal bone

Recently, numerous micro-channels have been discovered in the human temporal bone by micro-CT-scanning. Preliminary structure of these channels has suggested they contain a new separate blood supply for the mucosa of the mastoid air cells, which may have important functional implications. This paper proposes a structural analysis of the microchannels to corroborate this role. A local structure tensor is first estimated. The eigenvalues obtained from the estimated local structure tensor were then used to build probability maps representing planar, tubular, and isotropic tensor types. Each tensor type was assigned a respective RGB color and the full structure tensor was rendered along with the original data. Such structural analysis provides new and relevant information about the micro-channels but also their connections to mastoid air cells. Before carrying a future statistical analysis, a more accurate representation of the micro-channels in terms of local structure tensor analysis using adaptive filtering is needed.

Non-ring Filters for Robust Detection of Linear Structures

Many applications in image analysis include the problem of linear structure detection, e.g. segmentation of blood vessels in medical images, roads in satellite images, etc. A simple and efficient solution is to apply linear filters tuned to the structures of interest and extract line and edge positions from the filter output. However, if the filter is not carefully designed, artifacts such as ringing can distort the results and hinder a robust detection. In this paper, we study the ringing effects using a common Gabor filter for linear structure detection, and suggest a method for generating non-ring filters in 2D and 3D. The benefits of the non-ring design are motivated by results on both synthetic and natural images.

Surface and curve skeleton from a structure tensor analysis applied on mastoid air cells in human temporal bones

The mastoid of human temporal bone contains numerous air cells connected to each others. In order to gain further knowledge about these air cells, a more compact representation is needed to obtain an estimate of the size distribution of these cells. Already existing skeletonization methods often fail in producing a faithful skeleton mostly due to noise hampering the binary representation of the data. This paper proposes a different approach by extracting geometrical information embedded in the Euclidean distance transform of a volume via a structure tensor analysis based on quadrature filters, from which a secondary structure tensor allows the extraction of surface skeleton along with a curve skeleton from its eigenvalues. Preliminary results obtained on a X-ray micro-CT scans of a human temporal bone show very promising results.

Enhancement of micro-channels within the human mastoid bone based on local structure tensor analysis

Numerous micro-channels have recently been discovered in the human temporal bone by x-ray micro-CT-scanning. After a preliminary study suggesting that these micro-channels form a separate blood supply for the mucosa of the mastoid air cells, a structural analysis of the micro-channels using a local structure tensor was carried out. Despite the high-resolution of the micro-CT scan, presence of noise within the air cells along with missing information in some micro-channels suggested the need of image enhancement. This paper proposes an adaptive enhancement of the micro-channels based on a local structure analysis while minimizing the impact of noise on the overall data. Comparison with an anisotropic diffusion PDE based scheme was also performed.

Image Analysis and Visualization of the Human Mastoid Air Cell System

Recently, numerous micro-channels have been discovered in the human temporal bone by micro-CT-scanning. Preliminary structure of these channels has suggested they contain a new separate blood supply for the mucosa of the mastoid air cells, which may have important functional implications. This paper proposes a structural analysis of the microchannels to corroborate this role. A local structure tensor is first estimated. The eigenvalues obtained from the estimated local structure tensor were then used to build probability maps representing planar, tubular, and isotropic tensor types. Each tensor type was assigned a respective RGB color and the full structure tensor was rendered along with the original data. Such structural analysis provides new and relevant information about the micro-channels but also their connections to mastoid air cells. Before carrying a future statistical analysis, a more accurate representation of the micro-channels in terms of local structure tensor analysis using adaptive filtering is needed.

Mastoid structural properties determined by imaging analysis of high resolution CT-scanning

Hypothesis: The structure of the mastoid air cells can be described by quantitative imaging analysis of high-resolution CT-scans, which may contribute to understand its function in normal and pathological ears. Background: Negative middle ear pressure is a common factor in middle ear diseases resulting from an imbalance between mastoid gas exchange and Eustachian tube function. While the Eustachian tube function has been the main focus of research, more recent studies indicate that the mastoid may play an active role in pressure regulation. The mastoid structure with numerous air cells reflects a large area to volume ratio (AV-ratio) adapted to efficient gas exchange. Imaging analysis applied to high resolution CT-scanning can describe quantitative measures, which may reveal important information about mastoid function and its role in healthy and diseased ears. Materials and methods: Quantitative analysis was performed on a series of unselected high resolution CT-scans (voxel size: 0.29 _ 0.29 _ 0.625 mm) from 36 ears in 24 patients. Area and volume were determined using Cavalieri’s method, i.e. by summing cross-sectional areas. The AV-ratio was computed for each scan. Results: Mean area was 69 cm2 (range: 23–134cm2), mean volume was 4 cm3 (range: 1.3–10.8 cm3), and mean AV-ratio was 16 cm-1 (range: 11.2–21.0 cm-1). The area correlated linearly to the volume by A = 17.2*V-0.2. Conclusion: The area and volume values corresponded with previous studies, and the additional AV-ratio reflected the functional properties of the mastoid in terms of capability for gas exchange. Due to a series of similarities between structure and function of the lungs and mastoid, it seems likely to propose a tree-structure of dividing mastoid cells. In respiratory research, analysis describing the dimensions of series of bronchi generations has been applied, and based on current results; our aim of future research is to establish similar details of mastoid tree-structure. Funding source: Various private Danish funds.