A comparison of seven methods of within-subjects rigid-body pedobarographic image registration

A convolutional neural network Cascade for plantar pressure images registration

BACKGROUND

Plantar pressure image (PPI) recorded in high spatial and temporal resolution is very useful in clinical gait analysis. For functional analysis of PPI, image registration is often performed to maximally correlate source image with a template image. Previous methods estimate the registration parameters by iteratively optimizing different objective functions. These methods are often computational expensive to achieve satisfactory registration accuracy.

RESEARCH QUESTION

Can we develop a single PPI registration technique that performs more rapidly than previous methods, and that also maintains adequate PPI correspondence as defined by various (dis)similarity metrics?

METHODS

A cascaded convolutional neural network (CNN) was proposed for the registration of PPIs. Our model was trained to learn a regression from the difference between the template and misaligned images to the registration parameters. The registration performance was evaluated by three different metrics, i.e. the mean squared error (MSE), the exclusive or (XOR), and the mutual information (MI). For comparison, four previous methods were also implemented. These included the principal axes (PA) method, the center of pressure trajectory (COP) method, the MSE method, and the XOR method.

RESULTS

Experimental results on a dataset with 71 PPI template-source pairs showed that the proposed CNN-based method could obtain comparable registration accuracy to the MSE and XOR method. With regards to the registration speed, registration durations (mean ± sd in seconds) per image pair were: MSE (30.584 ± 2.171), XOR (24.245 ± 1.596), PA (0.016 ± 0.003), COP (25.614 ± 0.341), and the proposed model (0.054 ± 0.007).

SIGNIFICANCE

Our findings indicate that the proposed registration approach can achieve high accuracy but less computational time. Thus, it is more practical to utilize our pre-trained CNN-based model to develop near-real time applications for plantar pressure images registration.

Stat-tracks and mediotypes: powerful tools for modern ichnology based on 3D models

Vertebrate tracks are subject to a wide distribution of morphological types. A single trackmaker may be associated with a range of tracks reflecting individual pedal anatomy and behavioural kinematics mediated through substrate properties which may vary both in space and time. Accordingly, the same trackmaker can leave substantially different morphotypes something which must be considered in creating ichnotaxa. In modern practice this is often captured by the collection of a series of 3D track models. We introduce two concepts to help integrate these 3D models into ichnological analysis procedures. The mediotype is based on the idea of using statistically-generated three-dimensional track models (median or mean) of the type specimens to create a composite track to support formal recognition of a ichno type. A representative track (mean and/or median) is created from a set of individual reference tracks or from multiple examples from one or more trackways. In contrast, stat-tracks refer to other digitally generated tracks which may explore variance. For example, they are useful in: understanding the preservation variability of a given track sample; identifying characteristics or unusual track features; or simply as a quantitative comparison tool. Both concepts assist in making ichnotaxonomical interpretations and we argue that they should become part of the standard procedure when instituting new ichnotaxa. As three-dimensional models start to become a standard in publications on vertebrate ichnology, the mediotype and stat-track concepts have the potential to help guiding a revolution in the study of vertebrate ichnology and ichnotaxonomy.

Laetoli's lost tracks: 3D generated mean shape and missing footprints

The Laetoli site (Tanzania) contains the oldest known hominin footprints, and their interpretation remains open to debate, despite over 35 years of research. The two hominin trackways present are parallel to one another, one of which is a composite formed by at least two individuals walking in single file. Most researchers have focused on the single, clearly discernible G1 trackway while the G2/3 trackway has been largely dismissed due to its composite nature. Here we report the use of a new technique that allows us to decouple the G2 and G3 tracks for the first time. In so doing we are able to quantify the mean footprint topology of the G3 trackway and render it useable for subsequent data analyses. By restoring the effectively 'lost' G3 track, we have doubled the available data on some of the rarest traces directly associated with our Pliocene ancestors.

Preserving the impossible: conservation of soft-sediment hominin footprint sites and strategies for three-dimensional digital data capture

Human footprints provide some of the most publically emotive and tangible evidence of our ancestors. To the scientific community they provide evidence of stature, presence, behaviour and in the case of early hominins potential evidence with respect to the evolution of gait. While rare in the geological record the number of footprint sites has increased in recent years along with the analytical tools available for their study. Many of these sites are at risk from rapid erosion, including the Ileret footprints in northern Kenya which are second only in age to those at Laetoli (Tanzania). Unlithified, soft-sediment footprint sites such these pose a significant geoconservation challenge. In the first part of this paper conservation and preservation options are explored leading to the conclusion that to ‘record and digitally rescue’ provides the only viable approach. Key to such strategies is the increasing availability of three-dimensional data capture either via optical laser scanning and/or digital photogrammetry. Within the discipline there is a developing schism between those that favour one approach over the other and a requirement from geoconservationists and the scientific community for some form of objective appraisal of these alternatives is necessary. Consequently in the second part of this paper we evaluate these alternative approaches and the role they can play in a ‘record and digitally rescue’ conservation strategy. Using modern footprint data, digital models created via optical laser scanning are compared to those generated by state-of-the-art photogrammetry. Both methods give comparable although subtly different results. This data is evaluated alongside a review of field deployment issues to provide guidance to the community with respect to the factors which need to be considered in digital conservation of human/hominin footprints.

Does footprint depth correlate with foot motion and pressure?

Footprints are the most direct source of evidence about locomotor biomechanics in extinct vertebrates. One of the principal suppositions underpinning biomechanical inferences is that footprint geometry correlates with dynamic foot pressure, which, in turn, is linked with overall limb motion of the trackmaker. In this study, we perform the first quantitative test of this long-standing assumption, using topological statistical analysis of plantar pressures and experimental and computer-simulated footprints. In computer-simulated footprints, the relative distribution of depth differed from the distribution of both peak and pressure impulse in all simulations. Analysis of footprint samples with common loading inputs and similar depths reveals that only shallow footprints lack significant topological differences between depth and pressure distributions. Topological comparison of plantar pressures and experimental beach footprints demonstrates that geometry is highly dependent on overall print depth; deeper footprints are characterized by greater relative forefoot, and particularly toe, depth than shallow footprints. The highlighted difference between 'shallow' and 'deep' footprints clearly emphasizes the need to understand variation in foot mechanics across different degrees of substrate compliance. Overall, our results indicate that extreme caution is required when applying the 'depth equals pressure' paradigm to hominin footprints, and by extension, those of other extant and extinct tetrapods.

Visual pathway study using in vivo diffusion tensor imaging tractography to complement classic anatomy

BACKGROUND

Knowledge of the individual course of the optic radiations (ORs) is important to avoid postoperative visual deficits. Cadaveric studies of the visual pathways are limited because it has not been possible to separate the OR from neighboring tracts accurately and results may not apply to individual patients. Diffusion tensor imaging studies may be able to demonstrate the relationships between the OR and neighboring fibers in vivo in individual subjects.

OBJECTIVE

To use diffusion tensor imaging tractography to study the OR and the Meyer loop (ML) anatomy in vivo.

METHODS

Ten healthy subjects underwent magnetic resonance imaging with diffusion imaging at 3 T. With the use of a fiducial-based diffusion tensor imaging tractography tool (Slicer 3.3), seeds were placed near the lateral geniculate nucleus to reconstruct individual visual pathways and neighboring tracts. Projections of the ORs onto 3-dimensional brain models were shown individually to quantify relationships to key landmarks.

RESULTS

Two patterns of visual pathways were found. The OR ran more commonly deep in the whole superior and middle temporal gyri and superior temporal sulcus. The OR was closely surrounded in all cases by an inferior longitudinal fascicle and a parieto/occipito/temporo-pontine fascicle. The mean left and right distances between the tip of the OR and temporal pole were 39.8 ± 3.8 and 40.6 ± 5.7 mm, respectively.

CONCLUSION

Diffusion tensor imaging tractography provides a practical complementary method to study the OR and the Meyer loop anatomy in vivo with reference to individual 3-dimensional brain anatomy.

Registration of plantar pressure images

In this work, five computational methodologies to register plantar pressure images are compared: (1) the first methodology is based on matching the external contours of the feet; (2) the second uses the phase correlation technique; (3) the third addresses the direct maximization of cross-correlation using the Fourier transform; (4) the fourth minimizes the sum of squared differences using the Fourier transform; and (5) the fifth methodology iteratively optimizes an intensity (dis)similarity measure based on Powell's method. The accuracy and robustness of the five methodologies were assessed by using images from three common plantar pressure acquisition devices: a Footscan system, an EMED system, and a light reflection system. Using the residual error as a measure of accuracy, all methodologies revealed to be very accurate even in the presence of noise. The most accurate was the methodology based on the iterative optimization, when the mean squared error was minimized. It achieved a residual error inferior to 0.01 mm and 0.6 mm for non-noisy and noisy images, respectively. On the other hand, the methodology based on image contour matching was the fastest, but its accuracy was the lowest.

Medical image registration: a review

This paper presents a review of automated image registration methodologies that have been used in the medical field. The aim of this paper is to be an introduction to the field, provide knowledge on the work that has been developed and to be a suitable reference for those who are looking for registration methods for a specific application. The registration methodologies under review are classified into intensity or feature based. The main steps of these methodologies, the common geometric transformations, the similarity measures and accuracy assessment techniques are introduced and described.

Gait recognition: highly unique dynamic plantar pressure patterns among 104 individuals

Everyone's walking style is unique, and it has been shown that both humans and computers are very good at recognizing known gait patterns. It is therefore unsurprising that dynamic foot pressure patterns, which indirectly reflect the accelerations of all body parts, are also unique, and that previous studies have achieved moderate-to-high classification rates (CRs) using foot pressure variables. However, these studies are limited by small sample sizes (n < 30), moderate CRs (CR ≃ 90%), or both. Here we show, using relatively simple image processing and feature extraction, that dynamic foot pressures can be used to identify n = 104 subjects with a CR of 99.6 per cent. Our key innovation was improved and automated spatial alignment which, by itself, improved CR to over 98 per cent, a finding that pointedly emphasizes inter-subject pressure pattern uniqueness. We also found that automated dimensionality reduction invariably improved CRs. As dynamic pressure data are immediately usable, with little or no pre-processing required, and as they may be collected discreetly during uninterrupted gait using in-floor systems, foot pressure-based identification appears to have wide potential for both the security and health industries.

Human-like external function of the foot, and fully upright gait, confirmed in the 3.66 million year old Laetoli hominin footprints by topographic statistics, experimental footprint-formation and computer simulation

It is commonly held that the major functional features of the human foot (e.g. a functional longitudinal medial arch, lateral to medial force transfer and hallucal (big-toe) push-off) appear only in the last 2 Myr, but functional interpretations of footbones and footprints of early human ancestors (hominins) prior to 2 million years ago (Mya) remain contradictory. Pixel-wise topographical statistical analysis of Laetoli footprint morphology, compared with results from experimental studies of footprint formation; foot-pressure measurements in bipedalism of humans and non-human great apes; and computer simulation techniques, indicate that most of these functional features were already present, albeit less strongly expressed than in ourselves, in the maker of the Laetoli G-1 footprint trail, 3.66 Mya. This finding provides strong support to those previous studies which have interpreted the G-1 prints as generally modern in aspect.