Intelligent Computing in Medical Ultrasonic System

兵庫県立大学大学院201

Conditional Generative Data Augmentation for Clinical Audio Datasets

In this work, we propose a novel data augmentation method for clinical audio datasets based on a conditional Wasserstein Generative Adversarial Network with Gradient Penalty (cWGAN-GP), operating on log-mel spectrograms. To validate our method, we created a clinical audio dataset which was recorded in a real-world operating room during Total Hip Arthroplasty (THA) procedures and contains typical sounds which resemble the different phases of the intervention. We demonstrate the capability of the proposed method to generate realistic class-conditioned samples from the dataset distribution and show that training with the generated augmented samples outperforms classical audio augmentation methods in terms of classification performance. The performance was evaluated using a ResNet-18 classifier which shows a mean Macro F1-score improvement of 1.70% in a 5-fold cross validation experiment using the proposed augmentation method. Because clinical data is often expensive to acquire, the development of realistic and high-quality data augmentation methods is crucial to improve the robustness and generalization capabilities of learning-based algorithms which is especially important for safety-critical medical applications. Therefore, the proposed data augmentation method is an important step towards improving the data bottleneck for clinical audio-based machine learning systems

Dynamics, Electromyography and Vibroarthrography as Non-Invasive Diagnostic Tools: Investigation of the Patellofemoral Joint

The knee joint plays an essential role in the human musculoskeletal system. It has evolved to withstand extreme loading conditions, while providing almost frictionless joint movement. However, its performance may be disrupted by disease, anatomical deformities, soft tissue imbalance or injury. Knee disorders are often puzzling, and accurate diagnosis may be challenging. Current evaluation approach is usually limited to a detailed interview with the patient, careful physical examination and radiographic imaging. The X-ray screening may reveal bone degeneration, but does not carry sufficient information of the soft tissue conditions. More advanced imaging tools such as MRI or CT are available, but expensive, time consuming and can be used only under static conditions. Moreover, due to limited resolution the radiographic techniques cannot reveal early stage arthritis. The arthroscopy is often the only reliable option, however due to its semi-invasive nature, it cannot be considered as a practical diagnostic tool. Therefore, the motivation for this work was to combine three scientific methods to provide a comprehensive, non-invasive evaluation tool bringing insight into the in vivo, dynamic conditions of the knee joint and articular cartilage degeneration. Electromyography and inverse dynamics were employed to independently determine the forces present in several muscles spanning the knee joint. Though both methods have certain limitations, the current work demonstrates how the use of these two methods concurrently enhances the biomechanical analysis of the knee joint conditions, especially the performance of the extensor mechanism. The kinetic analysis was performed for 12 TKA, 4 healthy individuals in advanced age and 4 young subjects. Several differences in the knee biomechanics were found between the three groups, identifying age-related and post-operative decrease in the extensor mechanism efficiency, explaining the increased effort of performing everyday activities experienced by the elderly and TKA subjects. The concept of using accelerometers to assess the cartilage degeneration has been proven based on a group of 23 subjects with non-symptomatic knees and 52 patients suffering from knee arthritis. Very high success (96.2%) of pattern classification obtained in this work clearly demonstrates that vibroarthrography is a promising, non-invasive and low-cost technique offering screening capabilities

Experimental Analysis of Parameters Influencing the Bone Burring Process

The experimental quantification of the bone removal characteristics associated with bone burring represents a desirable outcome mainly for the selection of optimal parameters. An experimental apparatus was developed that allowed for concurrent measurement of three outputs associated with the bone removal process (cutting force, vibration, and temperature) as a function of various burring-specific parameters. Initial process trends were established on a uniform sawbone analog through use of a fully balanced multivariate statistical analysis. A smaller set of optimal and suboptimal parameters were further validated using a porcine femur. From the parameters tested, an optimal tool configuration, to avoid high temperature and high vibration, was found to be a 6 mm sphere burr at a rotational speed of 15,000 rpm, feed rate of 2 mm/s and a path overlap of 50%. This set of parameters also provided flexibility in tool depth/orientation angle relative to the bone without sacrificing optimal process outcomes

Quantification of knee extensor muscle forces: a multimodality approach

Given the growing interest of using musculoskeletal (MSK) models in a large number of clinical applications for quantifying the internal loading of the human MSK system, verification and validation of the model’s predictions, especially at the knee joint, have remained as one of the biggest challenges in the use of the models as clinical tools. This thesis proposes a methodology for more accurate quantification of knee extensor forces by exploring different experimental and modelling techniques that can be used to enhance the process of verification and validation of the knee joint model within the MSK models for transforming the models to a viable clinical tool. In this methodology, an experimental protocol was developed for simultaneous measurement of the knee joint motion, torques, external forces and muscular activation during an isolated knee extension exercise. This experimental protocol was tested on a cohort of 11 male subjects and the measurements were used to quantify knee extensor forces using two different MSK models representing a simplified model of the knee extensor mechanism and a previously-developed three-dimensional MSK model of the lower limb. The quantified knee extensor forces from the MSK models were then compared to evaluate the performance of the models for quantifying knee extensor forces. The MSK models were also used to investigate the sensitivity of the calculated knee extensor forces to key modelling parameters of the knee including the method of quantifying the knee centre of rotation and the effect of joint translation during motion. In addition, the feasibility of an emerging ultrasound-based imaging technique (shear wave elastography) for direct quantification of the physiologically-relevant musculotendon forces was investigated. The results in this thesis showed that a simplified model of the knee can be reliably used during a controlled planar activity as a computationally-fast and effective tool for hierarchical verification of the knee joint model in optimisation-based large-scale MSK models to provide more confidence in the outputs of the models. Furthermore, the calculation of knee extensor muscle forces has been found to be sensitive to knee joint translation (moving centre of rotation of the knee), highlighting the importance of this modelling parameter for quantifying physiologically-realistic knee muscle forces in the MSK models. It was also demonstrated how the movement of the knee axis of rotation during motion can be used as an intuitive tool for understanding the functional anatomy of the knee joint. Moreover, the findings in this thesis indicated that the shear wave elastography technique can be potentially used as a novel method for direct quantification of the physiologically-relevant musculotendon forces for independent validation of the predictions of musculotendon forces from the MSK models.Open Acces