Dissociable representations of environmental size and complexity in the human hippocampus

The hippocampus is widely assumed to play a central role in representing spatial layouts in the form of "cognitive maps." It remains unclear, however, which properties of the world are explicitly encoded in the hippocampus, and how these properties might contribute to the formation of cognitive maps. Here we investigated how physical size and complexity, two key properties of any environment, affect memory-related neural activity in the human hippocampus. We used functional magnetic resonance imaging and a virtual maze-learning task to examine retrieval-related activity for three previously learned virtual mazes that differed systematically in their physical size and complexity (here defined as the number of distinct paths within the maze). Before scanning, participants learned to navigate each of the three mazes; hippocampal activity was then measured during brief presentations of static images from within each maze. Activity within the posterior hippocampus scaled with maze size but not complexity, whereas activity in the anterior hippocampus scaled with maze complexity but not size. This double dissociation demonstrates that environmental size and complexity are explicitly represented in the human hippocampus, and reveals a functional specialization for these properties along its anterior-posterior axis

Development and Implementation of a Computational Surgical Planning Model for Pre-Operative Planning and Post-Operative Assessment and Analysis of Total Hip Arthroplasty

Total hip arthroplasty (THA) is most often used to treat osteoarthritis of the hip joint. Due to lack of a better alternative, newer designs are evaluated experimentally using mechanical simulators and cadavers. These evaluation techniques, though necessary, are costly and time-consuming, limiting testing on a broader population. Due to the advancement in technology, the current focus has been to develop patient-specific solutions. The hip joint can be approximated as encompassing a bone socket geometry, and therefore the shapes of the implant are well constrained. The variability of performance after the surgery is mostly driven by surgical procedures. It is believed that placing the acetabular component within the “safe zone” will commonly lead to successful surgical outcomes [1]. Unfortunately, recent research has revealed problems with the safe zone concept, and there is a need for a better tool which can aid surgeons in planning for surgery.With the advancement of computational power, more recent focus has been applied to the development of simulation tools that can predict implant performances. In this endeavor, a virtual hip simulator is being developed at the University of Tennessee Knoxville to provide designers and surgeons alike instant feedback about the performance of the hip implants. The mathematical framework behind this tool has been developed.In this dissertation, the primary focus is to further expand the capabilities of the existing hip model and develop the front-end that can replicate a total hip arthroplasty surgery procedure pre-operatively, intra-operatively, and post-operatively. This new computer-assisted orthopaedic surgical tool will allow surgeons to simulate surgery, then predict, compare, and optimize post-operative THA outcomes based on component placement, sizing choices, reaming and cutting locations, and surgical methods. This more advanced mathematical model can also reveal more information pre-operatively, allowing a surgeon to gain ample information before surgery, especially with difficult and revision cases. Moreover, this tool could also help during the implant development design process as designers can instantly simulate the performance of their new designs, under various surgical, simulated in vivo conditions

Computer assisted surgery for fracture reduction and deformity correction of the pelvis and long bones

Many orthopaedic operations, for example osteotomies, are not preoperative planned. The operation result depends on the experience of the operating surgeon. In the industry new developments are not longer curried out without CAD planning or computer simulations. Only in medicine the operation technology of corrective osteotomies are still in their infant stage in the last 30 years. Two dimensional analysis is not accurate that results in operation errors in the operating room. The surgeon usually obtains the preoperative information about the current bone state by radiographs. In case of complex operations (also inserting implants) planning is required. Planning based on radiographs has some system-dependent disadvantages like small accuracy, requirement of time for corrections ( distortions due to the projection) and restrictions, if complex corrections are necessary. Today the computer tomography is used as a solution. It is the only modality that allows to reach the accuracy and the resolution required for a good 3D-planning. However its a high dose rate for the patient is the serious disadvantage. Therefore in dilemma between the low dose rate and an adequate planning the first is often preferred. However in future it is expected that good operation results are guarantied only with implementation of 3D-planung. MR systems provide image information too, from which indirectly bones can be extracted. But due to their large distortions (susceptibility, non non-homogeneity of magnetic field), small spatial dissolution and the high costs, it is not expected that MRI represents an alternative in next time. The solution is the use of other image modalities. Ultrasound is here a good compromise both of the costs of the accuracy. In this work I developed an algorithm, which can produce 3D bone models from ultrasonic data. They have good resolution and accuracy compared with CT, and therefore can be used for 3D planning. In the work an improved procedure for segmenting bone surfaces is realised in combination with methods for the fusion for a three-dimensional model. The novelty of the presented work is in new approaches to realising an operation planning system, based on 3D computations, and implementing the intraoperative control by a guided ultrasound system for bone tracking. To realise these ideas the following tasks are solved: - bone modelling from CT data; - real-time extraction of bone surfaces from ultrasound imaging; - tracking the bone with respect to CT bone model. - integrating and implementing the above results in the development of an operation planning system for osteotomy corrections that supports on-line measurements, different types of deformity correction, a bone geometry design and a high level of automation. The developed osteotomy planning system allows to investigate the pathology, makes its analysis, finds an optimal way to realise surgery and provides visual and quantitative information about the results of the virtual operation. Therefore, the implementation of the proposed system can be considered as an additional significant tool for the diagnosis and orthopaedic surgery. The major parts of the planning system are: bone modelling from 3D data derived from CT, MRI or other modalities, visualisation of the elements of the 3D scene in real-time, and the geometric design of bone elements. A high level of automation allows the surgeon to reduce significantly the time of the operation plane development

Automating the multimodal analysis of musculoskeletal imaging in the presence of hip implants

In patients treated with hip arthroplasty, the muscular condition and presence of inflammatory reactions are assessed using magnetic resonance imaging (MRI). As MRI lacks contrast for bony structures, computed tomography (CT) is preferred for clinical evaluation of bone tissue and orthopaedic surgical planning. Combining the complementary information of MRI and CT could improve current clinical practice for diagnosis, monitoring and treatment planning. In particular, the different contrast of these modalities could help better quantify the presence of fatty infiltration to characterise muscular condition after hip replacement. In this thesis, I developed automated processing tools for the joint analysis of CT and MR images of patients with hip implants. In order to combine the multimodal information, a novel nonlinear registration algorithm was introduced, which imposes rigidity constraints on bony structures to ensure realistic deformation. I implemented and thoroughly validated a fully automated framework for the multimodal segmentation of healthy and pathological musculoskeletal structures, as well as implants. This framework combines the proposed registration algorithm with tailored image quality enhancement techniques and a multi-atlas-based segmentation approach, providing robustness against the large population anatomical variability and the presence of noise and artefacts in the images. The automation of muscle segmentation enabled the derivation of a measure of fatty infiltration, the Intramuscular Fat Fraction, useful to characterise the presence of muscle atrophy. The proposed imaging biomarker was shown to strongly correlate with the atrophy radiological score currently used in clinical practice. Finally, a preliminary work on multimodal metal artefact reduction, using an unsupervised deep learning strategy, showed promise for improving the postprocessing of CT and MR images heavily corrupted by metal artefact. This work represents a step forward towards the automation of image analysis in hip arthroplasty, supporting and quantitatively informing the decision-making process about patient’s management

Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review

The medical image analysis field has traditionally been focused on the development of organ-, and disease-specific methods. Recently, the interest in the development of more 20 comprehensive computational anatomical models has grown, leading to the creation of multi-organ models. Multi-organ approaches, unlike traditional organ-specific strategies, incorporate inter-organ relations into the model, thus leading to a more accurate representation of the complex human anatomy. Inter-organ relations are not only spatial, but also functional and physiological. Over the years, the strategies 25 proposed to efficiently model multi-organ structures have evolved from the simple global modeling, to more sophisticated approaches such as sequential, hierarchical, or machine learning-based models. In this paper, we present a review of the state of the art on multi-organ analysis and associated computation anatomy methodology. The manuscript follows a methodology-based classification of the different techniques 30 available for the analysis of multi-organs and multi-anatomical structures, from techniques using point distribution models to the most recent deep learning-based approaches. With more than 300 papers included in this review, we reflect on the trends and challenges of the field of computational anatomy, the particularities of each anatomical region, and the potential of multi-organ analysis to increase the impact of 35 medical imaging applications on the future of healthcare.Comment: Paper under revie

The feasibility of using feature-flow and label transfer system to segment medical images with deformed anatomy in orthopedic surgery

In computer-aided surgical systems, to obtain high fidelity three-dimensional models, we require accurate segmentation of medical images. State-of-art medical image segmentation methods have been used successfully in particular applications, but they have not been demonstrated to work well over a wide range of deformities. For this purpose, I studied and evaluated medical image segmentation using the feature-flow based Label Transfer System described by Liu and colleagues. This system has produced promising results in parsing images of natural scenes. Its ability to deal with variations in shapes of objects is desirable. In this paper, we altered this system and assessed its feasibility of automatic segmentation. Experiments showed that this system achieved better recognition rates than those in natural-scene parsing applications, but the high recognition rates were not consistent across different images. Although this system is not considered clinically practical, we may improve it and incorporate it with other medical segmentation tools

Three Dimensional Nonlinear Statistical Modeling Framework for Morphological Analysis

This dissertation describes a novel three-dimensional (3D) morphometric analysis framework for building statistical shape models and identifying shape differences between populations. This research generalizes the use of anatomical atlases on more complex anatomy as in case of irregular, flat bones, and bones with deformity and irregular bone growth. The foundations for this framework are: 1) Anatomical atlases which allow the creation of homologues anatomical models across populations; 2) Statistical representation for output models in a compact form to capture both local and global shape variation across populations; 3) Shape Analysis using automated 3D landmarking and surface matching. The proposed framework has various applications in clinical, forensic and physical anthropology fields. Extensive research has been published in peer-reviewed image processing, forensic anthropology, physical anthropology, biomedical engineering, and clinical orthopedics conferences and journals. The forthcoming discussion of existing methods for morphometric analysis, including manual and semi-automatic methods, addresses the need for automation of morphometric analysis and statistical atlases. Explanations of these existing methods for the construction of statistical shape models, including benefits and limitations of each method, provide evidence of the necessity for such a novel algorithm. A novel approach was taken to achieve accurate point correspondence in case of irregular and deformed anatomy. This was achieved using a scale space approach to detect prominent scale invariant features. These features were then matched and registered using a novel multi-scale method, utilizing both coordinate data as well as shape descriptors, followed by an overall surface deformation using a new constrained free-form deformation. Applications of output statistical atlases are discussed, including forensic applications for the skull sexing, as well as physical anthropology applications, such as asymmetry in clavicles. Clinical applications in pelvis reconstruction and studying of lumbar kinematics and studying thickness of bone and soft tissue are also discussed

Image analysis for extracapsular hip fracture surgery

PhD ThesisDuring the implant insertion phase of extracapsular hip fracture surgery, a surgeon visually inspects digital radiographs to infer the best position for the implant. The inference is made by “eye-balling”. This clearly leaves room for trial and error which is not ideal for the patient. This thesis presents an image analysis approach to estimating the ideal positioning for the implant using a variant of the deformable templates model known as the Constrained Local Model (CLM). The Model is a synthesis of shape and local appearance models learned from a set of annotated landmarks and their corresponding local patches extracted from digital femur x-rays. The CLM in this work highlights both Principal Component Analysis (PCA) and Probabilistic PCA as regularisation components; the PPCA variant being a novel adaptation of the CLM framework that accounts for landmark annotation error which the PCA version does not account for. Our CLM implementation is used to articulate 2 clinical metrics namely: the Tip-Apex Distance and Parker’s Ratio (routinely used by clinicians to assess the positioning of the surgical implant during hip fracture surgery) within the image analysis framework. With our model, we were able to automatically localise signi cant landmarks on the femur, which were subsequently used to measure Parker’s Ratio directly from digital radiographs and determine an optimal placement for the surgical implant in 87% of the instances; thereby, achieving fully automatic measurement of Parker’s Ratio as opposed to manual measurements currently performed in the surgical theatre during hip fracture surgery