Microrobots have the potential to revolutionize many aspects of medicine. These untethered, wirelessly controlled and powered devices will make existing therapeutic and diagnostic procedures less invasive and will enable new procedures never before possible. The aim of this review is threefold: first, to provide a comprehensive survey of the technological state of the art in medical microrobots; second, to explore the potential impact of medical microrobots and inspire future research in this field; and third, to provide a collection of valuable information and engineering tools for the design of medical microrobots.

/pdf/microrobots-for-minimally-invasive-medicine-cvnrt37y65.pdf

Microrobots for Minimally Invasive Medicine

/pdf/high-resolution-x-ray-computed-tomography-in-geosciences-a-3sj7249knj.pdf

High-resolution X-ray computed tomography in geosciences: A review of the current technology and applications

http://research.engr.oregonstate.edu/immiscibles/sites/research.engr.oregonstate.edu.immiscibles/files/Papers/Wildenschild_Sheppard_AWR_2012.pdf

X-ray imaging and analysis techniques for quantifying pore-scale structure and processes in subsurface porous medium systems

Current views on fungal chitin/chitosan, human chitinases, food preservation, glucans, pectins and inulin: A tribute to Henri Braconnot, precursor of the carbohydrate polymers science, on the chitin bicentennial

[1] Nondestructive imaging methods such as X-ray computed tomography (CT) yield high-resolution, three-dimensional representations of pore space and fluid distribution within porous materials. Steadily increasing computational capabilities and easier access to X-ray CT facilities have contributed to a recent surge in microporous media research with objectives ranging from theoretical aspects of fluid and interfacial dynamics at the pore scale to practical applications such as dense nonaqueous phase liquid transport and dissolution. In recent years, significant efforts and resources have been devoted to improve CT technology, microscale analysis, and fluid dynamics simulations. However, the development of adequate image segmentation methods for conversion of gray scale CT volumes into a discrete form that permits quantitative characterization of pore space features and subsequent modeling of liquid distribution and flow processes seems to lag. In this paper we investigated the applicability of various thresholding and locally adaptive segmentation techniques for industrial and synchrotron X-ray CT images of natural and artificial porous media. A comparison between directly measured and image-derived porosities clearly demonstrates that the application of different segmentation methods as well as associated operator biases yield vastly differing results. This illustrates the importance of the segmentation step for quantitative pore space analysis and fluid dynamics modeling. Only a few of the tested methods showed promise for both industrial and synchrotron tomography. Utilization of local image information such as spatial correlation as well as the application of locally adaptive techniques yielded significantly better results.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2009WR008087

Segmentation of X‐ray computed tomography images of porous materials: A crucial step for characterization and quantitative analysis of pore structures

This article presents a three-stage approach, combining novel and traditional algorithms, for the segmentation of images of porous and composite materials obtained from X-ray tomography. The first stage is an anisotropic diffusion filter which removes noise while preserving significant features. The second stage applies the unsharp mask sharpening filter which enhances edges and partially reverses the smoothing that is often a consequence of tomographic reconstruction. The final stage uses a combination of watershed and active contour methods for segmentation of the grey-scale data. For the data sets we have analysed, this approach gives the highest quality results. In addition, it has been implemented on cluster-type parallel computers and applied to cubic images comprising up to 20003 voxels.

Techniques for image enhancement and segmentation of tomographic images of porous materials

https://personalpages.manchester.ac.uk/staff/j.gough/lectures/te/7_8_bone/bone_eng/polymer/polym2.pdf

Analysis of 3D bone ingrowth into polymer scaffolds via micro-computed tomography imaging.

https://people.physics.anu.edu.au/~sth110/11_1_proofs.pdf

The chiral structure of porous chitin within the wing-scales of Callophrys rubi

Tight gas reservoirs exhibit storage and flow characteristics that are intimately tied to depositional and diagenetic processes. As a result, exploitation of these resources requires a comprehensive reservoir description and characterization program to identify properties which control production. In particular, tight gas reservoirs have significant primary and secondary porosity and pore connectivity dominated by clays and slot-like pores. This makes them particularly susceptible to the effects of overburden stress and variable water saturation. This paper describes an integrated approach to describe a tight gas sandstone at the pore scale in 3D. In particular, the primary and secondary porosity of a tight gas sandstone are identified and quantified in three dimensions using 3D X-ray micro-CT imaging and visualization of core material at the pore scale. 3D images allow one to map in detail the pore and grain structure and interconnectivity of primary and secondary porosity. Once the tomographic images ar...

3D porosity and mineralogy characterization in tight gas sandstones

Pore network models, in which the pore space is represented by a 3D network of interconnected pores and throats, are used extensively to compute important macroscopic transport properties including capillary pressure, relative permeability and residual saturation [2,6,12]. The predictive value of network models depends on the accuracy with which the network captures the complex geometric and topological properties of real porous rocks. A practical approach for a wide range of rock types is to extract networks and network properties directly from high-resolution 3D images of the pore space [2,7,8]. To ensure that generated networks are accurate representations of the imaged rock one must overcome problems of sensitivity to image noise and the lack of a robust procedure for merging adjacent nodes to form pores. One must also be able to generate networks on 3D volumes that are sufficiently large to be representative . We present an evolutionary approach for network extraction that uses the medial axis transform together with a number of morphological measures to select tessellation boundaries and applies a new node merging algorithm. The algorithms are fully parallel, allowing very large networks containing up to a million nodes to be generated. The power and flexibility of the network extraction procedure is illustrated by examining micro-CT images for a number of sandstone and carbonate samples at image sizes of up to 2000 3 voxels and resolutions down to 2 microns. The variability in network structure obtained across the range of samples imaged highlights the need to generate realistic pore network structures when attempting to perform predictive two phase flow modeling.

/pdf/improved-pore-network-extraction-methods-206px7kb88.pdf

Holger Averdunk

Papers

Techniques for image enhancement and segmentation of tomographic images of porous materials

Analysis of 3D bone ingrowth into polymer scaffolds via micro-computed tomography imaging.

The chiral structure of porous chitin within the wing-scales of Callophrys rubi

3D porosity and mineralogy characterization in tight gas sandstones

Improved pore network extraction methods