Learning to identify anomalies in x-ray images is a time consuming and difficult task. Manyhours of looking at similar images to familiarize oneself with the images can feel daunting andunmotivating. This is why a game application where the user, in a challenging environment, canlearn while being adequately stimulated.In this thesis, a game for this exact reason is created, with the aim being to teach anatomy tomedical students in a stimulating fashion. The game is made in the programming languagePython, which uses libraries supporting the DICOM-format, which is widely used in the medicalfield. By combining a score system with a time limit, the user can challenge themselves and seeconcrete improvement by playing the game.The goal of this thesis is to prepare medical students for their future profession as a doctor,training them to easily detect anomalies in the human body. A small test is conducted to test thegame and confirm that it improves the user’s ability to identify anatomical structures. The resultis then presented along with proposed improvements and alternative approaches.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24473号 / 医博第4915号 / 新制||医||1062(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 溝脇 尚志, 教授 黒田 知宏, 教授 花川 隆 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

No description available.

Newborns diagnosed with hip dysplasia face severe consequences when treatments fail. The Pavlik harness presents the most common worldwide treatment for correcting this medical hip abnormality in newborns, but becomes increasingly ineffective as subluxation increases. A dynamic finite element analysis on the hip joint would yield results that could provide insight to physicians as to how the Pavlik harness could be optimized to increase its success rate and develop patient-specific treatment plans. The study completes the first step in such an analysis by generating a three-dimensional model of an infant hip joint directly derived from computed tomography imaging in order to accurately represent the anatomical locations of muscle origins and insertions points as well as the unique cartilaginous characteristics of a neonate hip and femur. Such models will further enhance findings on the biomechanics of hip dysplasia that resulted from a preliminary study using computer-aided design to recreate the hip joint. In addition to the models, the orientation of the psoas tendon in a dysplastic hip through full range abduction and flexion was analyzed using a cadaveric dissection. It was determined that the psoas tendon was not an obstruction to reduction when the hip was in flexion so long as the tendon was not adherent to the hip capsule, and therefore can be disregarded in a finite element analysis or dynamic simulation that introduces flexion. The work of this thesis will lay the foundation for complex finite element analyses regarding the biomechanics of hip dysplasia in neonates as well as other hip abnormalities relevant to early child development.

Computed Tomography (CT) is the standard in medical imaging field. In this study, we look at the curvelet transform in an attempt to use it as a basis for representing a function. In doing so, we seek a way to reconstruct a function from the Radon data that may produce clearer results. Using curvelet decomposition, any known function can be represented as a sum of curvelets with corresponding coefficients. It can be shown that these corresponding coefficients can be found using the Radon data, even if the function is unknown. The use of curvelets has the potential to solve partial or truncated Radon data problems. As a result, using a curvelet representation to invert radon data allows the chance of higher quality images to be produced. This paper examines this method of reconstruction for computed tomography (CT). A brief history of CT, an introduction to the theory behind the method, and implementation details will be provided.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24967号 / 医博第5021号 / 新制||医||1069(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊達 洋至, 教授 江木 盛時, 教授 川上 浩司 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

No description available.

No description available.

No description available.

<p>The typical High Dose Rate (HDR) lung brachytherapy procedure involves inserting treatment catheters into the bronchi next to the tumour location using a bronchoscope. The anterior-posterior and lateral fluoroscopy images are acquired in order to localize the catheters prior to treatment. Although, these images enable accurate reconstruction of the catheter location, they do not allow for the visualization of the tumour or organs-at-risk due to poor soft tissue contrast. Although CT images offer an improved soft tissue contrast, moving the patient with catheters in place prior to each treatment is impractical.</p> <p>An alternative option is to use prior diagnostic or external beam radiation treatment planning CT images. These images cannot be used for treatment planning directly because of the variation in patient positioning between the CT and orthogonal images acquisition. In order to account for positioning differences, a 2D/3D registration algorithm that registers the orthogonal images with a previously acquired CT data was developed. The algorithm utilizes a rigid registration model based on a pixel/voxel intensity matching approach. A similarity measure combining normalized mutual information (NMI), image gradient, and intensity difference was developed. Evaluation of the algorithm was performed using tissue equivalent phantoms, and, in the clinical setting using data from six patients. The mean registration error was 2.1 mm and 3.2 mm for phantoms and patients respectively.</p> <p>External objects such as the treatment table and ECG leads are often in CT images, affecting the above mentioned 2D/3D registration. To address this, an algorithm for automatic removal of external objects from CT images was developed. This was applied to automatic contouring and removal of the fiducial markers in CT images used for external beam radiation therapy treatment planning for breast cancer. The algorithm was further modified to compute the girth of patients as part of a diagnostic radiology clinical trial.</p> / Doctor of Philosophy (PhD)