ToScA North America (6 – 8 June 2017, The University of Texas, Austin, TX) Program

ToScA North America will address key areas of science, including Multi-modal Imaging, Geosciences, Forensics, Increasing Contrast, Educational Outreach, Data, Materials Science and Medical and Biological Science.University of Texas High-Resolution X-ray CT Facility (UTCT); Jackson School of Geosciences, The University of Texas at Austin; Natural History Museum (London); Royal Microscopical Society (Oxford, UK)Geological Science

Liver Segmentation and its Application to Hepatic Interventions

The thesis addresses the development of an intuitive and accurate liver segmentation approach, its integration into software prototypes for the planning of liver interventions, and research on liver regeneration. The developed liver segmentation approach is based on a combination of the live wire paradigm and shape-based interpolation. Extended with two correction modes and integrated into a user-friendly workflow, the method has been applied to more than 5000 data sets. The combination of the liver segmentation with image analysis of hepatic vessels and tumors allows for the computation of anatomical and functional remnant liver volumes. In several projects with clinical partners world-wide, the benefit of the computer-assisted planning was shown. New insights about the postoperative liver function and regeneration could be gained, and most recent investigations into the analysis of MRI data provide the option to further improve hepatic intervention planning

Threshold Selection Criteria for Quantification of Lumbosacral Cerebrospinal Fluid and Root Volumes from MRI

BACKGROUND AND PURPOSE: The high variability of CSF volumes partly explains the inconsistency of anesthetic effects, but may also be due to image analysis itself. In this study, criteria for threshold selection are anatomically defined. METHODS: T2 MR images (n = 7 cases) were analyzed using 3-dimentional software. Maximal-minimal thresholds were selected in standardized blocks of 50 slices of the dural sac ending caudally at the L5-S1 intervertebral space (caudal blocks) and middle L3 (rostral blocks). Maximal CSF thresholds: threshold value was increased until at least one voxel in a CSF area appeared unlabeled and decreased until that voxel was labeled again: this final threshold was selected. Minimal root thresholds: thresholds values that selected cauda equina root area but not adjacent gray voxels in the CSF-root interface were chosen. RESULTS: Significant differences were found between caudal and rostral thresholds. No significant differences were found between expert and nonexpert observers. Average max/min thresholds were around 1.30 but max/min CSF volumes were around 1.15. Great interindividual CSF volume variability was detected (max/min volumes 1.6-2.7). CONCLUSIONS: The estimation of a close range of CSF volumes which probably contains the real CSF volume value can be standardized and calculated prior to certain intrathecal procedures

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Development of 3D software for post-surgical shoulder arthroplasty implant position analysis

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica) Universidade de Lisboa, Faculdade de Ciências, 2020O ombro garante a articulação entre a cabeça do úmero e a parte glenoide da escapula, sendo responsável por diversas tarefas essenciais no nosso dia a dia. Esta articulação tem uma grande amplitude de movimento devido às ações dos músculos e às configurações articulares, permitindo movimentos como abdução, adução, rotação, elevação para a frente e para trás do tronco e mover-se em 360 ° no plano sagital. No entanto, esta grande amplitude de movimento torna o ombro mais instável e suscetível a lesões, o que poderá ter um impacto direto na qualidade de vida de uma pessoa, podendo condicionar significativamente a mobilidade desta articulação. Algumas das patologias do ombro incluem desgaste excessivo, inflamação, rutura do músculo da coifa dos rotadores, instabilidade e impacto que podem estar relacionados a doenças degenerativas, como a osteoartrite, fraturas ou uso excessivo da articulação (devido a movimentos repetitivos em desportos, no trabalho, etc.). Infelizmente, a degeneração da articulação do ombro é um problema particularmente frequente no envelhecimento da nossa população, afetando uma em cada cinco pessoas acima de 65 anos. Existem 2 tipos principais de degeneração do ombro: 1. osteoartrite, que é a degeneração primária da cartilagem articular relacionada com a idade, com um músculo da coifa dos rotadores intacto; 2. Artropatia por rutura da coifa dos rotadores, e, como o nome indica, caracterizada por uma grande rutura do músculo da coifa dos rotadores, levando a alterações na carga articular e danos articulares progressivos. Ambos os tipos de degeneração são caracterizados pela destruição da cartilagem articular que leva à dor, restrição de movimento e incapacidade funcional. Uma degeneração adicional pode levar à destruição óssea da glenoide, um fenómeno conhecido como erosão da glenoide. Existem diferentes tipos de erosões, dependendo do tipo de degeneração do ombro. Curiosamente, a osteoartrite é caracterizada principalmente por erosão óssea posterior e a artropatia por rutura da coifa dos rotadores por erosão óssea superior. A evolução da medicina permitiu a correção destas patologias ou consequências das mesmas, sendo agora uma cirurgia bastante comum na área da ortopedia, especialmente em idosos. Para tal, é necessário estudar cada caso e fazer um planeamento cirúrgico adequado através de imagens raio-X ou tomografias computadorizadas. O tratamento cirúrgico passa pela artroplastia do ombro (anatómica ou invertida) que ganhou popularidade devido à sua eficácia no alívio da dor e na restauração da função do ombro degenerado. Durante a cirurgia, o cirurgião precisa de estudar a inclinação, versão e correção do desvio e suporte ósseo mais adequados para a colocação do implante. A técnica mais utilizada é o alargamento assimétrico, onde a erosão da glenoide é corrigida com a remoção do lado mais alto do osso. Isso leva a uma perda óssea da medialização da glenoide e da linha articular, o que pode influenciar a função do implante do ombro e a duração de vida do mesmo a longo prazo. As causas mais importantes para falha da artroplastia do ombro são complicações do componente glenoide, como alargamento e desgaste, especialmente em glenoides com erosão pré-operatória. Esta erosão pode originar ângulos de inclinação e versão e desvio alterados. A principal causa de falha do componente glenoide em pacientes com erosão é carga anormal descentralizada quando a erosão não é adequadamente corrigida. Portanto, a glenoide erodida deve ser corrigida para uma inclinação, versão e desvio mais normais antes da implantação do componente glenoide. O posicionamento adequado do implante, juntamente com o equilíbrio dos tecidos moles, são questões-chave na artroplastia do ombro, tanto para a função pós-operatória quanto para a duração a longo prazo do implante. O mau posicionamento do componente glenoide pode levar a uma má função, instabilidade e enfraquecimento precoce do componente na artroplastia total e reversa do ombro. Devido às dificuldades com a colocação correta e às possíveis complicações que advém da inadequada da colocação do componente da glenoide, começou-se a investigar o planeamento computacional para a colocação do implante. O uso de ferramentas de planeamento (software) através de tomografia computadorizadas 3D e instrumentação específica do paciente é, neste momento, a prática mais comum. Para além da avaliação pré-cirúrgica de cada caso e do seu planeamento, o seguimento médico e avaliação pós-cirúrgica também é de extrema importância para averiguar se a colocação do implante foi adequada e se está de acordo com o plano pré-operatório. Para isso, são usados, de igual forma do planeamento, raios-X ou tomografias computadorizadas que são avaliadas pelos médicos. A maioria dos estudos em geral demonstra que as técnicas de tomografia computadorizada são mais precisas na determinação da posição pós-cirúrgica do componente glenoide do que as radiografias axiais padrão. Mais do que isso, o uso de destas acoplado a softwares 3D para análise da posição do implante demonstrou ser mais preciso, pois os modelos 3D refletem com maior precisão a verdadeira anatomia da morfologia da escápula. Assim, numa perspetiva de tentar encontrar uma solução idêntica à de software de planeamento, mas adaptado para análise pós cirúrgica do implante, foi proposto um projeto para desenvolvimento de um novo software capaz de realizar a análise da posição pós-cirúrgica do implante em termos de versão, inclinação e desvio do implante. Portanto, o objetivo deste sistema de software é determinar a confiabilidade e a precisão da colocação do implante. O software foi desenvolvido na plataforma MeVisLab e fornece uma descrição da posição do componente glenoide em termos de versão, inclinação e desvio do implante (componente glenóide) entre as posições reais e ideais e a rotação do implante. O MeVisLab é uma plataforma diversificada para processamento de imagens médicas e visualização científica. Inclui algoritmos avançados para registo, segmentação e análise quantitativa de imagens morfológicas e funcionais. A sua estrutura é baseada em módulos e com estes, redes podem ser criadas e diferentes aplicações podem ser construídas. A criação deste software nesta plataforma é considerada uma inovação, pois não há nenhuma referência a algo semelhante, com o mesmo objetivo e funcionalidades, na pesquisa bibliográfica feita. O modelo do implante utilizado ao longo do desenvolvimento do software e na sua análise foi ligeiramente modificado, fechando o lado aberto da glenoesfera (componente glenoide). Assim sendo, o desenvolvimento deste projeto incluiu etapas diferentes: a primeira foi a definição das medidas requisitadas pelos médicos, ângulos e pontos anatómicos de referência necessários, sendo que, neste caso, os pontos anatómicos de referência devem ser selecionados pelo utilizador e os outros dois serão calculados automaticamente; O próximo passo foi o desenvolvimento do software no MeVisLab com uma rede baseada em módulos que incluía módulos de visualização de imagens (2D e 3D), módulos que auxiliam na definição de planos e pontos de referência para os cálculos e módulos scripts em Python que contêm o código para todos os itens necessários para os cálculos; Em seguida, o desenvolvimento da interface para o utilizador foi feito de forma a que o mesmo tivesse uma experiência intuitiva e de fácil uso, e que conseguisse seguir todas as instruções necessárias, para a seleção de todos os pontos de referência e, posteriormente, o cálculo dos ângulos e medidas requisitadas; Finalmente, o último passo foi garantir que o software criado fosse confiável e consistente em todos os seus resultados no domínio intraobservador e interobservador e quando comparado com os resultados encontrados na literatura. Até ao momento, o software desenvolvido fornece os ângulos e medidas desejados com sucesso, no entanto, mostrou-se não ser tão confiável e consistente quanto era desejado. Assim, muito pode ainda ser feito para melhorar a precisão do software desenvolvido e atingir totalmente o objetivo final. Os resultados obtidos através do software podem ainda, mais tarde, ser usados para comparar se o implante colocado tem a mesma orientação que a planeada para um paciente específico antes da cirurgia. Além disso, a posição do implante pode ser correlacionada com a função pós-operatória do paciente.The shoulder has a high range of motion because of its muscles actions and joint configuration, allowing it to abduct, adduct, rotate, be raised in front of and behind the torso and move through a full 360° in the sagittal plane. This large range of motion makes the shoulder more unstable and susceptible to injuries. The most common shoulder pathologies include cuff tear arthropathy and osteoarthritis which are related to permanent loss of the rotator cuff tendons and a gradual wearing of the articular cartilage, respectively, that leads to pain, stiffness and, consequently, to loss of the shoulder function. Reverse shoulder arthroplasty (RSA) has been proven to be a successful treatment for cuff tear arthropathy and osteoarthritis in the elderly patients. RSA consist in a shoulder replacement with a prosthesis that aims to restore the best possible function to the joint by removing scar tissue balancing muscles and replacing the destroyed joint surface of the humerus. The glenosphere positioning during the procedure has a significant impact on outcomes in RSA because it determines the center of rotation and biomechanical traits of the new joint. Misalignment and/or displacement of the glenoid component with respect to the bone can be a cause of, or contribute to, failure of the implant. Reasons for displacementof the glenoid component include inaccurate assessment of the pathologic anatomy of the glenoid, incorrect choice of implant and/or position of the implant to correct the pathologic condition, and inaccurate surgical execution of the preoperative plan. The goal of this project was to create a software for post-surgical shoulder arthroplasty analysis that gives version, inclination and implant shift values of the glenoid component aiming to evaluate the precision and reliability of its placement. The development of this project included different steps: the first one was the definition of the desired measurements, angles and the needed landmarks being that landmarks must be selected by the user and then the other two will be calculated automatically; The next step was the development of the novel software in MeVisLab with a module based network that included image visualizing modules (2D and 3D), modules that assist the definition of planes and landmarks for the calculations and python script modules that contain the code for all needed calculations; Then, the development of the user interface took place with the necessary means for the user to have all instructions needed, for the selection of all landmarks and returning the angles and measurements calculated; Finally, the last step was to ensure that the created software was reliable and consistent in its results in both intraobserver and interobserver domain and when compared with literature findings. So far, the developed software provides the required version and inclination angles and implant shift measure successfully however has shown to not be as reliable and consistent as desired. Thus, a lot can still be done to improve the accuracy of the developed software and to achieve fully the final goal

Vascular Segmentation Algorithms for Generating 3D Atherosclerotic Measurements

Atherosclerosis manifests as plaques within large arteries of the body and remains as a leading cause of mortality and morbidity in the world. Major cardiovascular events may occur in patients without known preexisting symptoms, thus it is important to monitor progression and regression of the plaque burden in the arteries for evaluating patient\u27s response to therapy. In this dissertation, our main focus is quantification of plaque burden from the carotid and femoral arteries, which are major sites for plaque formation, and are straight forward to image noninvasively due to their superficial location. Recently, 3D measurements of plaque burden have shown to be more sensitive to the changes of plaque burden than one-/two-dimensional measurements. However, despite the advancements of 3D noninvasive imaging technology with rapid acquisition capabilities, and the high sensitivity of the 3D plaque measurements of plaque burden, they are still not widely used due to the inordinate amount of time and effort required to delineate artery walls plus plaque boundaries to obtain 3D measurements from the images. Therefore, the objective of this dissertation is developing novel semi-automated segmentation methods to alleviate measurement burden from the observer for segmentation of the outer wall and lumen boundaries from: (1) 3D carotid ultrasound (US) images, (2) 3D carotid black-blood magnetic resonance (MR) images, and (3) 3D femoral black-blood MR images. Segmentation of the carotid lumen and outer wall from 3DUS images is a challenging task due to low image contrast, for which no method has been previously reported. Initially, we developed a 2D slice-wise segmentation algorithm based on the level set method, which was then extended to 3D. The 3D algorithm required fewer user interactions than manual delineation and the 2D method. The algorithm reduced user time by ≈79% (1.72 vs. 8.3 min) compared to manual segmentation for generating 3D-based measurements with high accuracy (Dice similarity coefficient (DSC)\u3e90%). Secondly, we developed a novel 3D multi-region segmentation algorithm, which simultaneously delineates both the carotid lumen and outer wall surfaces from MR images by evolving two coupled surfaces using a convex max-flow-based technique. The algorithm required user interaction only on a single transverse slice of the 3D image for generating 3D surfaces of the lumen and outer wall. The algorithm was parallelized using graphics processing units (GPU) to increase computational speed, thus reducing user time by 93% (0.78 vs. 12 min) compared to manual segmentation. Moreover, the algorithm yielded high accuracy (DSC \u3e 90%) and high precision (intra-observer CV \u3c 5.6% and inter-observer CV \u3c 6.6%). Finally, we developed and validated an algorithm based on convex max-flow formulation to segment the femoral arteries that enforces a tubular shape prior and an inter-surface consistency of the outer wall and lumen to maintain a minimum separation distance between the two surfaces. The algorithm required the observer to choose only about 11 points on its medial axis of the artery to yield the 3D surfaces of the lumen and outer wall, which reduced the operator time by 97% (1.8 vs. 70-80 min) compared to manual segmentation. Furthermore, the proposed algorithm reported DSC greater than 85% and small intra-observer variability (CV ≈ 6.69%). In conclusion, the development of robust semi-automated algorithms for generating 3D measurements of plaque burden may accelerate translation of 3D measurements to clinical trials and subsequently to clinical care

Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images

Complex scenario of ultrasound image, in which adjacent tissues (i.e., background) share similar intensity with and even contain richer texture patterns than lesion region (i.e., foreground), brings a unique challenge for accurate lesion segmentation. This work presents a decomposition-coupling network, called DC-Net, to deal with this challenge in a (foreground-background) saliency map disentanglement-fusion manner. The DC-Net consists of decomposition and coupling subnets, and the former preliminarily disentangles original image into foreground and background saliency maps, followed by the latter for accurate segmentation under the assistance of saliency prior fusion. The coupling subnet involves three aspects of fusion strategies, including: 1) regional feature aggregation (via differentiable context pooling operator in the encoder) to adaptively preserve local contextual details with the larger receptive field during dimension reduction; 2) relation-aware representation fusion (via cross-correlation fusion module in the decoder) to efficiently fuse low-level visual characteristics and high-level semantic features during resolution restoration; 3) dependency-aware prior incorporation (via coupler) to reinforce foreground-salient representation with the complementary information derived from background representation. Furthermore, a harmonic loss function is introduced to encourage the network to focus more attention on low-confidence and hard samples. The proposed method is evaluated on two ultrasound lesion segmentation tasks, which demonstrates the remarkable performance improvement over existing state-of-the-art methods.Comment: 18 pages, 18 figure

Med-Query: Steerable Parsing of 9-DoF Medical Anatomies with Query Embedding

Automatic parsing of human anatomies at instance-level from 3D computed tomography (CT) scans is a prerequisite step for many clinical applications. The presence of pathologies, broken structures or limited field-of-view (FOV) all can make anatomy parsing algorithms vulnerable. In this work, we explore how to exploit and conduct the prosperous detection-then-segmentation paradigm in 3D medical data, and propose a steerable, robust, and efficient computing framework for detection, identification, and segmentation of anatomies in CT scans. Considering complicated shapes, sizes and orientations of anatomies, without lose of generality, we present the nine degrees-of-freedom (9-DoF) pose estimation solution in full 3D space using a novel single-stage, non-hierarchical forward representation. Our whole framework is executed in a steerable manner where any anatomy of interest can be directly retrieved to further boost the inference efficiency. We have validated the proposed method on three medical imaging parsing tasks of ribs, spine, and abdominal organs. For rib parsing, CT scans have been annotated at the rib instance-level for quantitative evaluation, similarly for spine vertebrae and abdominal organs. Extensive experiments on 9-DoF box detection and rib instance segmentation demonstrate the effectiveness of our framework (with the identification rate of 97.0% and the segmentation Dice score of 90.9%) in high efficiency, compared favorably against several strong baselines (e.g., CenterNet, FCOS, and nnU-Net). For spine identification and segmentation, our method achieves a new state-of-the-art result on the public CTSpine1K dataset. Last, we report highly competitive results in multi-organ segmentation at FLARE22 competition. Our annotations, code and models will be made publicly available at: https://github.com/alibaba-damo-academy/Med_Query.Comment: updated versio

Comparing Features of Three-Dimensional Object Models Using Registration Based on Surface Curvature Signatures

This dissertation presents a technique for comparing local shape properties for similar three-dimensional objects represented by meshes. Our novel shape representation, the curvature map, describes shape as a function of surface curvature in the region around a point. A multi-pass approach is applied to the curvature map to detect features at different scales. The feature detection step does not require user input or parameter tuning. We use features ordered by strength, the similarity of pairs of features, and pruning based on geometric consistency to efficiently determine key corresponding locations on the objects. For genus zero objects, the corresponding locations are used to generate a consistent spherical parameterization that defines the point-to-point correspondence used for the final shape comparison