Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Hardware accelerated ray cast of volume data and volume gradient for an optimized splines-based multi-resolution 2D-3D registration

This paper describes a method for DRR generation as well as for volume gradients projection using hardware accelerated 2D texture mapping and accumulation buffering and demonstrates its application in 2D-3D registration of X-ray fluoroscopy to CT images. The robustness of the present registration scheme are guaranteed by taking advantage of a coarse-to-fine processing of the volume/image pyramids based on cubic B-splines. A human cadaveric spine specimen together with its ground truth was used to compare the present scheme with a purely software-based scheme in three aspects: accuracy, speed, and capture ranges. Our experiments revealed an equivalent accuracy and capture ranges but with much shorter registration time with the present scheme. More specifically, the results showed 0.8 mm average target registration error, 55 second average execution time per registration, and 10 mm and 10° capture ranges for the present scheme when tested on a 3.0 GHz Pentium 4 computer.

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

High resolution fast T1 mapping technique for dGEMRIC

PURPOSE: To determine the feasibility of using a high resolution isotropic three-dimensional (3D) fast T1 mapping sequence for delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) to assess osteoarthritis in the hip. MATERIALS AND METHODS: T1 maps of the hip were acquired using both low and high resolution techniques following the administration of 0.2 mmol/kg Gd-DTPA(2-) in 35 patients. Both T1 maps were generated from two separate spoiled GRE images. The high resolution T1 map was reconstructed in the anatomically equivalent plane as the low resolution map. T1 values from the equivalent anatomic regions containing femoral and acetabular cartilages were measured on the low and high resolution maps and compared using regression analysis. RESULTS: In vivo T1 measurements showed a statistically significant correlation between the low and high resolution acquisitions at 1.5 Tesla (R(2) = 0.958, P < 0.001). These results demonstrate the feasibility of using a fast two-angle T1 mapping (F2T1) sequence with isotropic spatial resolution (0.8 x 0.8 x 0.8 mm) for quantitative assessment of biochemical status in articular cartilage of the hip. CONCLUSION: The high resolution 3D F2T1 sequence provides accurate T1 measurements in femoral and acetabular cartilages of the hip, which enables the biochemical assessment of articular cartilage in any plane through the joint. It is a powerful tool for researchers and clinicians to acquire high resolution data in a reasonable scan time (< 30 min).

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

Structure determination of channel and transport proteins by high-resolution microscopy techniques

High-resolution microscopy techniques provide a plethora of information on biological structures from the cellular level down to the molecular level. In this review, we present the unique capabilities of transmission electron and atomic force microscopy to assess the structure, oligomeric state, function and dynamics of channel and transport proteins in their native environment, the lipid bilayer. Most importantly, membrane proteins can be visualized in the frozen-hydrated state and in buffer solution by cryo-transmission electron and atomic force microscopy, respectively. We also illustrate the potential of the scintillation proximity assay to study substrate binding of detergent-solubilized transporters prior to crystallization and structural characterization.

Design techniques and analysis of high-resolution neural recording systems targeting epilepsy focus localization

The design of a high-density neural recording system targeting epilepsy monitoring is presented. Circuit challenges and techniques are discussed to optimize the amplifier topology and the included OTA. A new platform supporting active recording devices targeting wireless and high-resolution focus localization in epilepsy diagnosis is also proposed. The post-layout simulation results of an amplifier dedicated to this application are presented. The amplifier is designed in a UMC 0.18µm CMOS technology, has an NEF of 2.19 and occupies a silicon area of 0.038 mm(2), while consuming 5.8 µW from a 1.8-V supply.

Palaeoenvironmental changes in Central Europe (NE Poland) during the last 6200 years reconstructed from a high-resolution multi-proxy peat archive

Peat deposits from an ombrotrophic bog (north-eastern Poland) were analysed to reconstruct peatland development and environmental changes. This paper presents reconstructions of hydrological changes and plant succession over the last 6000 years. The methods included the high-resolution analysis of plant macrofossils, pollen and testate amoebae, supported by radiocarbon dating. Three main phases were identified in the history of the bog and surrounding woodland vegetation: 4000–400 BC, 400 BC–AD 1700 and AD 1700–2011. Except for terrestrialisation and the fen-to-bog transition phase, the development of bog vegetation was mainly dependent on the climate until approximately AD 1700. The dominant taxon in Gązwa bog was Sphagnum fuscum/rubellum. Woodland development was significantly affected by human activity at several time periods. The most visible human activity, manifested by the decline of deciduous species, occurred ca. 350 BC, ca. AD 250, ca. AD 1350 and after AD 1700. These events correspond to phases of human settlement in the area. During 400–300 BC, the decline of deciduous trees, primarily Carpinus, coincided with an increase in indicators of human activity and fire frequency. At ca. AD 200, Carpinus and Tilia abundance decreased, corresponding to an increased importance of cereals (Secale and Triticum). Since ca. AD 1350, the impact of Teutonic settlement is apparent, and after AD 1700, deciduous forests largely disappeared.

Virtobot--a multi-functional robotic system for 3D surface scanning and automatic post mortem biopsy

The Virtopsy project, a multi-disciplinary project that involves forensic science, diagnostic imaging, computer science, automation technology, telematics and biomechanics, aims to develop new techniques to improve the outcome of forensic investigations. This paper presents a new approach in the field of minimally invasive virtual autopsy for a versatile robotic system that is able to perform three-dimensional (3D) surface scans as well as post mortem image-guided soft tissue biopsies.