RESUMEN
Enfacement illusions are traditionally elicited by visuo-tactile stimulation, but more active paradigms become possible through the usage of virtual reality techniques. For instance, virtual mirrors have been recently proposed to induce enfacement by visuo-motor stimulation. In a virtual mirror experiment, participants interact with an avatar that imitates their facial movements. The active control over the avatar greatly enhances the sense of agency, which is an important ingredient for successful enfacement illusion induction. Due to technological challenges, most virtual mirrors so far were limited to the imitation of the participant's head pose, i.e., its location and rotation. However, stronger experiences of agency can be expected by an increase in the avatar's mimicking abilities. We here present a new open-source framework for virtual mirror experiments, which we call the Open Virtual Mirror Framework (OVMF). The OVMF can track and imitate a large range of facial movements, including pose and expressions. It has been designed to run on standard computer hardware and easily interfaces with existing toolboxes for psychological experimentation, while satisfying the requirement of a tightly controlled experimental setup. Further, it is designed to enable convenient extension of its core functionality such that it can be flexibly adjusted to many different experimental paradigms. We demonstrate the usage of the OVMF and experimentally validate its ability to elicit experiences of agency over an avatar, concluding that the OVMF can serve as a reference for future experiments and that it provides high potential to stimulate new directions in enfacement research and beyond.
Asunto(s)
Ilusiones , Realidad Virtual , Humanos , Expresión Facial , Ilusiones/fisiología , Movimiento/fisiologíaRESUMEN
In our chapter we are describing how to reconstruct three-dimensional anatomy from medical image data and how to build Statistical 3D Shape Models out of many such reconstructions yielding a new kind of anatomy that not only allows quantitative analysis of anatomical variation but also a visual exploration and educational visualization. Future digital anatomy atlases will not only show a static (average) anatomy but also its normal or pathological variation in three or even four dimensions, hence, illustrating growth and/or disease progression.Statistical Shape Models (SSMs) are geometric models that describe a collection of semantically similar objects in a very compact way. SSMs represent an average shape of many three-dimensional objects as well as their variation in shape. The creation of SSMs requires a correspondence mapping, which can be achieved e.g. by parameterization with a respective sampling. If a corresponding parameterization over all shapes can be established, variation between individual shape characteristics can be mathematically investigated.We will explain what Statistical Shape Models are and how they are constructed. Extensions of Statistical Shape Models will be motivated for articulated coupled structures. In addition to shape also the appearance of objects will be integrated into the concept. Appearance is a visual feature independent of shape that depends on observers or imaging techniques. Typical appearances are for instance the color and intensity of a visual surface of an object under particular lighting conditions, or measurements of material properties with computed tomography (CT) or magnetic resonance imaging (MRI). A combination of (articulated) Statistical Shape Models with statistical models of appearance lead to articulated Statistical Shape and Appearance Models (a-SSAMs).After giving various examples of SSMs for human organs, skeletal structures, faces, and bodies, we will shortly describe clinical applications where such models have been successfully employed. Statistical Shape Models are the foundation for the analysis of anatomical cohort data, where characteristic shapes are correlated to demographic or epidemiologic data. SSMs consisting of several thousands of objects offer, in combination with statistical methods or machine learning techniques, the possibility to identify characteristic clusters, thus being the foundation for advanced diagnostic disease scoring.
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Anatomía , Imagenología Tridimensional , Modelos Anatómicos , Algoritmos , Anatomía/educación , Anatomía/métodos , Diagnóstico por Imagen , Humanos , Modelos EstadísticosRESUMEN
Successful functional surgery on the nasal framework requires reliable and comprehensive diagnosis. In this regard, the authors introduce a new methodology: Digital Analysis of Nasal Airflow (diANA). It is based on computational fluid dynamics, a statistical shape model of the healthy nasal cavity and rhinologic expertise. diANA necessitates an anonymized tomographic dataset of the paranasal sinuses including the complete nasal cavity and, when available, clinical information. The principle of diANA is to compare the morphology and the respective airflow of an individual nose with those of a reference. This enables morphometric aberrations and consecutive flow field anomalies to localize and quantify within a patient's nasal cavity. Finally, an elaborated expert opinion with instructive visualizations is provided. Using diANA might support surgeons in decision-making, avoiding unnecessary surgery, gaining more precision, and target-orientation for indicated operations.
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Simulación por Computador , Cavidad Nasal/diagnóstico por imagen , Obstrucción Nasal/cirugía , Senos Paranasales/diagnóstico por imagen , Adulto , Toma de Decisiones Clínicas , Técnicas de Apoyo para la Decisión , Femenino , Humanos , Hidrodinámica , Modelos Anatómicos , Modelos Estadísticos , Obstrucción Nasal/fisiopatología , Respiración , Tomografía por Rayos XRESUMEN
Functional surgery on the nasal framework requires referential criteria to objectively assess nasal breathing for indication and follow-up. This motivated us to generate a mean geometry of the nasal cavity based on a statistical shape model. In this study, the authors could demonstrate that the introduced nasal cavity's mean geometry features characteristics of the inner shape and airflow, which are commonly observed in symptom-free subjects. Therefore, the mean geometry might serve as a reference-like model when one considers qualitative aspects. However, to facilitate quantitative considerations and statistical inference, further research is necessary. Additionally, the authors were able to obtain details about the importance of the isthmus nasi and the inferior turbinate for the intranasal airstream.
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Cavidad Nasal/anatomía & histología , Cavidad Nasal/fisiología , Adolescente , Adulto , Femenino , Humanos , Masculino , Persona de Mediana Edad , Modelos Anatómicos , Modelos Estadísticos , Valores de Referencia , Respiración , Adulto JovenRESUMEN
Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.
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Simulación por Computador , Análisis de Elementos Finitos , Cambios Post Mortem , Diseño Asistido por Computadora , Estudios de Factibilidad , Humanos , Modelos Biológicos , Tomografía Computarizada Multidetector , Fantasmas de ImagenRESUMEN
PURPOSE: Morphological data pertaining to the pelvis and lower extremity muscles are increasingly being used in biomechanical modeling to compare healthy and pathological conditions. Very few data sets exist that encompass all of the muscles of the lower limb, allowing for comparisons between regions. The aims of this study were to (a) provide physiological cross-sectional area (PCSA) data for the pelvic, thigh, and leg muscles in young, healthy participants, using magnetic resonance imaging (MRI), and (b) to compare these data with summarized PCSAs obtained from the literature. MATERIALS AND METHODS: Six young and healthy volunteers participated and were scanned using 3 T MRI. PCSAs were calculated from volumetric segmentations obtained bilaterally of 28 muscles/muscle groups of the pelvis, thigh, and leg. These data were compared to published, summarized PCSA data derived from cadaveric, computed tomography, MRI and ultrasound studies. RESULTS: The PCSA of the pelvis, thigh, and leg muscles tended to be 20-130% larger in males than in females, except for the gemelli which were 34% smaller in males, and semitendinosus and triceps surae which did not differ (<20% different). The dominant and the non-dominant sides showed similar and minutely different PCSA with less than 18% difference between sides. Comparison to other studies revealed wide ranges within, and large differences between, the cadaveric and imaging PCSA data. Comparison of the PCSA of this study and published literature revealed major differences in the iliopsoas, gluteus minimus, tensor fasciae latae, gemelli, obturator internus, biceps femoris, quadriceps femoris, and the deep leg flexor muscles. CONCLUSIONS: These volume-derived PCSAs of the pelvic and lower limb muscles alongside the data synthesised from the literature may serve as a basis for comparative and biomechanical studies of the living and healthy young, and enable calculation of muscle forces. Comparison of the literature revealed large variations in PCSA from each of the different investigative modalities, hampering comparability between studies. Sample size, age, post-mortem changes of muscle tone, chemical fixation of cadaveric tissues, and the underlying physics of the imaging techniques may potentially influence PCSA calculations.
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Imagen por Resonancia Magnética/métodos , Músculo Esquelético/anatomía & histología , Pelvis/anatomía & histología , Muslo/anatomía & histología , Voluntarios Sanos , Humanos , Factores SexualesRESUMEN
BACKGROUND: Fossil ticks are extremely rare and Ixodes succineus Weidner, 1964 from Eocene (ca. 44-49 Ma) Baltic amber is one of the oldest examples of a living hard tick genus (Ixodida: Ixodidae). Previous work suggested it was most closely related to the modern and widespread European sheep tick Ixodes ricinus (Linneaus, 1758). RESULTS: Restudy using phase contrast synchrotron x-ray tomography yielded images of exceptional quality. These confirm the fossil's referral to Ixodes Latreille, 1795, but the characters resolved here suggest instead affinities with the Asian subgenus Partipalpiger Hoogstraal et al., 1973 and its single living (and medically significant) species Ixodes ovatus Neumann, 1899. We redescribe the amber fossil here as Ixodes (Partipalpiger) succineus. CONCLUSIONS: Our data suggest that Ixodes ricinus is unlikely to be directly derived from Weidner's amber species, but instead reveals that the Partipalpiger lineage was originally more widely distributed across the northern hemisphere. The closeness of Ixodes (P.) succineus to a living vector of a wide range of pathogens offers the potential to correlate its spatial and temporal position (northern Europe, nearly 50 million years ago) with the estimated origination dates of various tick-borne diseases.
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Fósiles/anatomía & histología , Ixodes/anatomía & histología , Ixodes/clasificación , Ámbar , Animales , Vectores de Enfermedades/clasificación , Europa (Continente) , Femenino , Ixodes/genética , Masculino , Tomografía/métodosRESUMEN
PURPOSE: Pelvic tilt determines functional orientation of the acetabulum. In this study, we investigated the interaction of pelvic tilt and functional acetabular anteversion (AA) in supine position. METHODS: Pelvic tilt and AA of 138 individuals were measured by computed tomography (CT). AA was calculated in relation to the anterior pelvic plane (APP) and relative to the table plane. We analysed these parameters for gender-specific and age-related differences. RESULTS: The mean pelvic tilt was -0.1 ± 5.5°. Pelvic sagittal rotation displayed no gender nor age related differences. Females showed higher angles of AA compared with males (20.0° vs 17.2°, p < 0.001; AA relative to the APP). Anterior tilting of the pelvis positively correlated with AA and individuals with high AA had a higher anterior pelvic tilt compared with those with low AA (p < 0.0001; AA relative to the APP). CONCLUSIONS: AA has to be calculated regarding pelvic sagittal rotation for correct acetabular orientation. Pelvic tilt is dependent on acetabular orientation and compensates for increased AA.
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Acetábulo/patología , Artroplastia de Reemplazo de Cadera , Acetábulo/cirugía , Femenino , Humanos , Masculino , Pelvis , Rotación , Tomografía Computarizada por Rayos XRESUMEN
This article reflects the research of the last two decades in computational planning for cranio-maxillofacial surgery. Model-guided and computer-assisted surgery planning has tremendously developed due to ever increasing computational capabilities. Simulators for education, planning, and training of surgery are often compared with flight simulators, where maneuvers are also trained to reduce a possible risk of failure. Meanwhile, digital patient models can be derived from medical image data with astonishing accuracy and thus can serve for model surgery to derive a surgical template model that represents the envisaged result. Computerized surgical planning approaches, however, are often still explorative, meaning that a surgeon tries to find a therapeutic concept based on his or her expertise using computational tools that are mimicking real procedures. Future perspectives of an improved computerized planning may be that surgical objectives will be generated algorithmically by employing mathematical modeling, simulation, and optimization techniques. Planning systems thus act as intelligent decision support systems. However, surgeons can still use the existing tools to vary the proposed approach, but they mainly focus on how to transfer objectives into reality. Such a development may result in a paradigm shift for future surgery planning.
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Cráneo/cirugía , Cirugía Asistida por Computador , Cirugía Bucal , Cefalometría , Humanos , Modelos AnatómicosRESUMEN
Facial surgery deals with a part of the human body that is of particular importance in everyday social interactions. The perception of a person's natural, emotional, and social appearance is significantly influenced by one's expression. This is why facial dynamics has been increasingly studied by both artists and scholars since the mid-Renaissance. Currently, facial dynamics and their importance in the perception of a patient's identity play a fundamental role in planning facial surgery. Assistance is needed for patient information and communication, and documentation and evaluation of the treatment as well as during the surgical procedure. Here, the quantitative assessment of morphological features has been facilitated by the emergence of diverse digital imaging modalities in the last decades. Unfortunately, the manual data preparation usually needed for further quantitative analysis of the digitized head models (surface registration, landmark annotation) is time-consuming, and thus inhibits its use for treatment planning and communication. In this article, we refer to historical studies on facial dynamics, briefly present related work from the field of facial surgery, and draw implications for further developments in this context. A prototypical stereophotogrammetric system for high-quality assessment of patient-specific 3D dynamic morphology is described. An individual statistical model of several facial expressions is computed, and possibilities to address a broad range of clinical questions in facial surgery are demonstrated.
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Cara/cirugía , Expresión Facial , Humanos , Modelos BiológicosRESUMEN
Statistical shape models are an essential tool for various tasks in medical image analysis, including shape generation, reconstruction and classification. Shape models are learned from a population of example shapes, which are typically obtained through segmentation of volumetric medical images. In clinical practice, highly anisotropic volumetric scans with large slice distances are prevalent, e.g., to reduce radiation exposure in CT or image acquisition time in MR imaging. For existing shape modeling approaches, the resolution of the emerging model is limited to the resolution of the training shapes. Therefore, any missing information between slices prohibits existing methods from learning a high-resolution shape prior. We propose a novel shape modeling approach that can be trained on sparse, binary segmentation masks with large slice distances. This is achieved through employing continuous shape representations based on neural implicit functions. After training, our model can reconstruct shapes from various sparse inputs at high target resolutions beyond the resolution of individual training examples. We successfully reconstruct high-resolution shapes from as few as three orthogonal slices. Furthermore, our shape model allows us to embed various sparse segmentation masks into a common, low-dimensional latent space - independent of the acquisition direction, resolution, spacing, and field of view. We show that the emerging latent representation discriminates between healthy and pathological shapes, even when provided with sparse segmentation masks. Lastly, we qualitatively demonstrate that the emerging latent space is smooth and captures characteristic modes of shape variation. We evaluate our shape model on two anatomical structures: the lumbar vertebra and the distal femur, both from publicly available datasets.
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Algoritmos , Modelos Estadísticos , Humanos , Imagen por Resonancia Magnética , Procesamiento de Imagen Asistido por Computador/métodosRESUMEN
In the ongoing debate about gender-specific (GS) vs. traditional knee implants, there is limited information about patella-specific outcomes. GS femoral component features should provide better patellar tracking, but techniques have not existed previously to test this accurately. Using novel computed tomography and radiography imaging protocols, 15 GS knees were compared to 10 traditional knees, for the 6 degrees of freedom of the patellofemoral and tibiofemoral joints throughout the range of motion, plus other geometric measures and quality of life (QOL). Significant differences were found for patellar medial/lateral shift, where the patella was shifted more laterally for the GS femoral component. Neither group demonstrated patellar maltracking. There were no other significant differences in this well-functioning group.
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Artroplastia de Reemplazo de Rodilla , Articulación de la Rodilla/fisiopatología , Articulación de la Rodilla/cirugía , Prótesis de la Rodilla , Diseño de Prótesis , Anciano , Fenómenos Biomecánicos , Femenino , Humanos , Imagenología Tridimensional , Articulación de la Rodilla/anatomía & histología , Articulación de la Rodilla/diagnóstico por imagen , Masculino , Persona de Mediana Edad , Radiografía , Factores SexualesRESUMEN
A reliable and comprehensive assessment of nasal breathing is problematic and still a common issue in rhinosurgery. Impairments of nasal breathing need an objective approach. In this regard, currently rhinomanometry is the only standard diagnostic tool available but has various limitations. However, in the last decade, computational fluid dynamics (CFD) has become a promising method in facing the challenge of qualifying nasal breathing. This article presents use of CFD with a symptom-free subject and a symptomatic patient. Thereby, certain flow field features and changes before and after surgery were investigated. Moreover, the study outlines suggestions for concrete rhinologic CFD applications.
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Hidrodinámica , Obstrucción Nasal/fisiopatología , Tabique Nasal/patología , Nariz/fisiología , Ventilación Pulmonar/fisiología , Resistencia de las Vías Respiratorias , Estudios de Casos y Controles , Biología Computacional , Simulación por Computador , Humanos , Masculino , Persona de Mediana Edad , Modelos Anatómicos , Cavidad Nasal/fisiología , Obstrucción Nasal/diagnóstico por imagen , Obstrucción Nasal/cirugía , Tabique Nasal/fisiopatología , Tabique Nasal/cirugía , Radiografía , Rinomanometría , Resistencia al Corte , Estrés MecánicoRESUMEN
PURPOSE: To investigate the influence of teeth and dental restorations on the facial skeleton's gray value distributions in cone-beam computed tomography (CBCT). METHODS: Gray value selection for the upper and lower jaw segmentation was performed in 40 patients. In total, CBCT data of 20 maxillae and 20 mandibles, ten partial edentulous and ten fully edentulous in each jaw, respectively, were evaluated using two different gray value selection procedures: manual lower threshold selection and automated lower threshold selection. Two sample t tests, linear regression models, linear mixed models, and Pearson's correlation coefficients were computed to evaluate the influence of teeth, dental restorations, and threshold selection procedures on gray value distributions. RESULTS: Manual threshold selection resulted in significantly different gray values in the fully and partially edentulous mandible. (p = 0.015, difference 123). In automated threshold selection, only tendencies to different gray values in fully edentulous compared to partially edentulous jaws were observed (difference: 58-75). Significantly different gray values were evaluated for threshold selection approaches, independent of the dental situation of the analyzed jaw. No significant correlation between the number of teeth and gray values was assessed, but a trend towards higher gray values in patients with more teeth was noted. CONCLUSIONS: Standard gray values derived from CT imaging do not apply for threshold-based bone segmentation in CBCT. Teeth influence gray values and segmentation results. Inaccurate bone segmentation may result in ill-fitting surgical guides produced on CBCT data and misinterpreting bone density, which is crucial for selecting surgical protocols. Created with BioRender.com.
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Boca Edéntula , Humanos , Proyectos Piloto , Cara , Computadores , Tomografía Computarizada de Haz CónicoAsunto(s)
Espiración , Inhalación , Cavidad Nasal/diagnóstico por imagen , Obstrucción Nasal/diagnóstico por imagen , Tabique Nasal/diagnóstico por imagen , Adolescente , Adulto , Presión del Aire , Resistencia de las Vías Respiratorias , Estudios de Casos y Controles , Femenino , Humanos , Hidrodinámica , Masculino , Persona de Mediana Edad , Cavidad Nasal/fisiología , Obstrucción Nasal/fisiopatología , Tabique Nasal/fisiología , Proyectos Piloto , Estrés Mecánico , Tomografía Computarizada por Rayos X , Adulto JovenRESUMEN
Alternative treatment methods for knee osteoarthritis (OA) are in demand, to delay the young (< 50 Years) patient's need for osteotomy or knee replacement. Novel interpositional knee spacers shape based on statistical shape model (SSM) approach and made of polyurethane (PU) were developed to present a minimally invasive method to treat medial OA in the knee. The implant should be supposed to reduce peak strains and pain, restore the stability of the knee, correct the malalignment of a varus knee and improve joint function and gait. Firstly, the spacers were tested in artificial knee models. It is assumed that by application of a spacer, a significant reduction in stress values and a significant increase in the contact area in the medial compartment of the knee will be registered. Biomechanical analysis of the effect of novel interpositional knee spacer implants on pressure distribution in 3D-printed knee model replicas: the primary purpose was the medial joint contact stress-related biomechanics. A secondary purpose was a better understanding of medial/lateral redistribution of joint loading. Six 3D printed knee models were reproduced from cadaveric leg computed tomography. Each of four spacer implants was tested in each knee geometry under realistic arthrokinematic dynamic loading conditions, to examine the pressure distribution in the knee joint. All spacers showed reduced mean stress values by 84-88% and peak stress values by 524-704% in the medial knee joint compartment compared to the non-spacer test condition. The contact area was enlarged by 462-627% as a result of the inserted spacers. Concerning the appreciable contact stress reduction and enlargement of the contact area in the medial knee joint compartment, the premises are in place for testing the implants directly on human knee cadavers to gain further insights into a possible tool for treating medial knee osteoarthritis.
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Osteoartritis de la Rodilla , Fenómenos Biomecánicos , Humanos , Articulación de la Rodilla/cirugía , Osteoartritis de la Rodilla/cirugía , Poliuretanos , Impresión Tridimensional , Tibia/diagnóstico por imagen , Tibia/cirugíaRESUMEN
Convolutional neural networks (CNNs) are the state-of-the-art for automated assessment of knee osteoarthritis (KOA) from medical image data. However, these methods lack interpretability, mainly focus on image texture, and cannot completely grasp the analyzed anatomies' shapes. In this study we assess the informative value of quantitative features derived from segmentations in order to assess their potential as an alternative or extension to CNN-based approaches regarding multiple aspects of KOA. Six anatomical structures around the knee (femoral and tibial bones, femoral and tibial cartilages, and both menisci) are segmented in 46,996 MRI scans. Based on these segmentations, quantitative features are computed, i.e., measurements such as cartilage volume, meniscal extrusion and tibial coverage, as well as geometric features based on a statistical shape encoding of the anatomies. The feature quality is assessed by investigating their association to the Kellgren-Lawrence grade (KLG), joint space narrowing (JSN), incident KOA, and total knee replacement (TKR). Using gold standard labels from the Osteoarthritis Initiative database the balanced accuracy (BA), the area under the Receiver Operating Characteristic curve (AUC), and weighted kappa statistics are evaluated. Features based on shape encodings of femur, tibia, and menisci plus the performed measurements showed most potential as KOA biomarkers. Differentiation between non-arthritic and severely arthritic knees yielded BAs of up to 99%, 84% were achieved for diagnosis of early KOA. Weighted kappa values of 0.73, 0.72, and 0.78 were achieved for classification of the grade of medial JSN, lateral JSN, and KLG, respectively. The AUC was 0.61 and 0.76 for prediction of incident KOA and TKR within one year, respectively. Quantitative features from automated segmentations provide novel biomarkers for KLG and JSN classification and show potential for incident KOA and TKR prediction. The validity of these features should be further evaluated, especially as extensions of CNN-based approaches. To foster such developments we make all segmentations publicly available together with this publication.
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Cartílago Articular/diagnóstico por imagen , Articulación de la Rodilla/diagnóstico por imagen , Osteoartritis de la Rodilla/diagnóstico por imagen , Bases de Datos Factuales , Femenino , Fémur/diagnóstico por imagen , Peroné/diagnóstico por imagen , Humanos , Incidencia , Imagen por Resonancia Magnética , Masculino , Meniscos Tibiales/diagnóstico por imagen , Osteoartritis de la Rodilla/epidemiología , Tibia/diagnóstico por imagenRESUMEN
BACKGROUND AND OBJECTIVE: We present a fully automated method for the quantification of knee alignment from full-leg radiographs. METHODS: A state-of-the-art object detector, YOLOv4, was trained to locate regions of interests in full-leg radiographs for the hip joint, knee, and ankle. Residual neural networks were trained to regress landmark coordinates for each region of interest. Based on the detected landmarks the knee alignment, i.e., the hip-knee-ankle (HKA) angle was computed. The accuracy of landmark detection was evaluated by a comparison to manually placed ones for 180 radiographs. The accuracy of HKA angle computations was assessed on the basis of 2,943 radiographs by a comparison to results of two independent image reading studies (Cooke; Duryea) both publicly accessible via the Osteoarthritis Initiative. The agreement was evaluated using Spearman's Rho, weighted kappa, and regarding the correspondence of the class assignment. RESULTS: The average deviation of landmarks manually placed by experts and automatically detected ones by our proposed "YOLOv4 And Resnet Landmark regression Algorithm" (YARLA) was less than 2.0 ± 1.5 mm for all structures. The average mismatch between HKA angle determinations of Cooke and Duryea was 0.09 ± 0.63°; YARLA resulted in a mismatch of 0.09 ± 0.73° compared to Cooke and of 0.18 ± 0.67° compared to Duryea. Cooke and Duryea agreed almost perfectly with respect to a weighted kappa value of 0.86, and showed an excellent reliability as measured by a Spearman's Rho value of 0.98. Similar values were achieved by YARLA, i.e., a weighted kappa value of 0.83 and 0.87 and a Spearman's Rho value of 0.98 and 0.98 compared to Cooke and Duryea, respectively. Cooke and Duryea agreed in 91% of all class assignments and YARLA did so in 90% against Cooke and 92% against Duryea. CONCLUSIONS: YARLA yields HKA angles similar to those of human experts and provides a basis for an automated assessment of knee alignment in full-leg radiographs.
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Desviación Ósea , Osteoartritis , Algoritmos , Humanos , Articulación de la Rodilla/diagnóstico por imagen , Pierna , Reproducibilidad de los Resultados , Estudios Retrospectivos , Rayos XRESUMEN
PURPOSE: Segmentation of surgical instruments in endoscopic video streams is essential for automated surgical scene understanding and process modeling. However, relying on fully supervised deep learning for this task is challenging because manual annotation occupies valuable time of the clinical experts. METHODS: We introduce a teacher-student learning approach that learns jointly from annotated simulation data and unlabeled real data to tackle the challenges in simulation-to-real unsupervised domain adaptation for endoscopic image segmentation. RESULTS: Empirical results on three datasets highlight the effectiveness of the proposed framework over current approaches for the endoscopic instrument segmentation task. Additionally, we provide analysis of major factors affecting the performance on all datasets to highlight the strengths and failure modes of our approach. CONCLUSIONS: We show that our proposed approach can successfully exploit the unlabeled real endoscopic video frames and improve generalization performance over pure simulation-based training and the previous state-of-the-art. This takes us one step closer to effective segmentation of surgical instrument in the annotation scarce setting.
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Simulación por Computador , Curaduría de Datos , Endoscopía/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Algoritmos , Artefactos , Humanos , Aprendizaje , Programas Informáticos , Estudiantes , Grabación en VideoRESUMEN
We present a novel approach for nonlinear statistical shape modeling that is invariant under Euclidean motion and thus alignment-free. By analyzing metric distortion and curvature of shapes as elements of Lie groups in a consistent Riemannian setting, we construct a framework that reliably handles large deformations. Due to the explicit character of Lie group operations, our non-Euclidean method is very efficient allowing for fast and numerically robust processing. This facilitates Riemannian analysis of large shape populations accessible through longitudinal and multi-site imaging studies providing increased statistical power. Additionally, as planar configurations form a submanifold in shape space, our representation allows for effective estimation of quasi-isometric surfaces flattenings. We evaluate the performance of our model w.r.t. shape-based classification of hippocampus and femur malformations due to Alzheimer's disease and osteoarthritis, respectively. In particular, we outperform state-of-the-art classifiers based on geometric deep learning as well as statistical shape modeling especially in presence of sparse training data. To provide insight into the model's ability of capturing biological shape variability, we carry out an analysis of specificity and generalization ability.