12,593 research outputs found
Application of CT in Diagnosing Carcinoma of the Maxillary Sinuses : PART 2: An Experimental Study of Pitfalls Encountered when Diagnosing Carcinoma of the Maxillary Sinuses with CT
No full text1982-03A phantom simulating the transverse section of the maxillary sinuses was constructed for experimentation with various CT scanners to study the following: (1) the occasional inability to image the very thin posterior-lateral walls which have no real bone defects, and (2) to verify whether or not the bony walls surrounding the maxillary sinuses are actually as thick as they appear on CT. The phantom was made of an acrylic cylinder containing three cavities simulating the maxillary sinuses and the nasal cavity and filled with water. The walls, made of thin aluminum and acrylic plates and placed between water and air, disappeared in some CT images. The thickness of the walls calculated from CT values was greater than the true thickness imaged by each CT scanner. The author stresses that in CT images, either experimentally or clinically, thin bony walls placed between water and air or fat tend to disappear, and that bony walls tend to appear thicker than their true thickenss.departmental bulletin pape
4D CT simulator
No full textThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 93-95).This thesis presents the development and application of a 4-Dimensional Computed Tomography (4D CT) simulation program. The simulation is used to understand and quantify the sources of image artifacts that arise from irregular patient breathing during 4D CT. Performance of the simulation is validated by comparing the simulation results with those of phantom experiments with CT scanners. The program simulates 4D CT scanning of objects of arbitrary size and shape and is extended to investigate the accuracy of gated radiotherapy. Experiments are performed using realistic breathing patterns from patients, in addition to synthetic ones for various studies. The simulation is used to study the effects of scan start time shift, breathing trace baseline drift, and hysteresis of internal organ and abdominal surface motion on the quality of 4D CT images. While 4D CT significantly reduces artifacts from helical scans of the thoracic and abdominal areas, a variety of different sources can still contribute to motioninduced artifacts in 4D CT. Since 4D CT is used to determine target margins for radiotherapy, proper precaution should be taken so that image artifacts do not lead to inaccurate treatment planning. Finally, this thesis discusses improvements in 4D CT and suggests additional methods to improve treatment planning for radiotherapy.by Alan Chu.M.Eng
Psychological and family functioning among handicapped college students—A case-control study
No full textsj-pdf-1-acr-10.1177_02841851211029080 - Supplemental material for Total and regional ASPECT score for non-contrast CT, CT angiography, and CT perfusion: inter-rater agreement and its association with the final infarction in acute ischemic stroke patients
No full textSupplemental material, sj-pdf-1-acr-10.1177_02841851211029080 for Total and regional ASPECT score for non-contrast CT, CT angiography, and CT perfusion: inter-rater agreement and its association with the final infarction in acute ischemic stroke patients by Yue Chu, Gao Ma, Xiao-Quan Xu, Shan-Shan Lu, Yue-Zhou Cao, Hai-Bin Shi, Sheng Liu and Fei-Yun Wu in Acta Radiologica</p
Fully Automatic Segmentation of Hip CT Images
No full textAutomatic segmentation of the hip joint with pelvis and proximal femur surfaces from CT images is essential for orthopedic diagnosis and surgery. It remains challenging due to the narrowness of hip joint space, where the adjacent surfaces of acetabulum and femoral head are hardly distinguished from each other. This chapter presents a fully automatic method to segment pelvic and proximal femoral surfaces from hip CT images. A coarse-to-fine strategy was proposed to combine multi-atlas segmentation with graph-based surface detection. The multi-atlas segmentation step seeks to coarsely extract the entire hip joint region. It uses automatically detected anatomical landmarks to initialize and select the atlas and accelerate the segmentation. The graph based surface detection is to refine the coarsely segmented hip joint region. It aims at completely and efficiently separate the adjacent surfaces of the acetabulum and the femoral head while preserving the hip joint structure. The proposed strategy was evaluated on 30 hip CT images and provided an average accuracy of 0.55, 0.54, and 0.50 mm for segmenting the pelvis, the left and right proximal femurs, respectively
What do interest inventories measure? The convergence and content validity of four RIASEC inventories
No full textMost interest inventories aim to measure the same core interest traits based on Holland’s (1997) RIASEC model. Despite the widespread use of RIASEC interest inventories, little is known about the extent to which these inventories actually measure the same core constructs and provide similar career recommendations to individuals. The current study investigates the convergent validity among four major interest inventories—the Self-Directed Search (SDS), the O*NET Interest Profiler (IP), the ACT Interest Inventory (UNIACT), and the Strong Interest Inventory (SII). Three methods were used to analyze different aspects of convergence: 1) correlated trait-correlated methods (CT-CM) model, 2) high-point code agreements, and 3) item content analysis. Results showed that, although RIASEC interest scores from the four inventories were highly correlated, the measures often gave respondents different high point codes that lead to divergent career recommendations. Moreover, item content analysis revealed that while the inventories measure some common basic interest dimensions, they also assess distinct peripheral basic interests. Integrating findings from these three unique perspectives, we put forth practical recommendations for constructing future interest inventories to increase convergence. We also discuss the importance of using multiple methods to investigate convergent validity, especially content analysis which provides foundational guidance for interpreting results from existing interest inventories.Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-09-16 without embargo termsThe student, Chu Chu, accepted the attached license on 2021-04-30 at 11:46.The student, Chu Chu, submitted this Thesis for approval on 2021-04-30 at 11:59.This Thesis was approved for publication on 2021-04-30 at 13:05.DSpace SAF Submission Ingestion Package generated from Vireo submission #16625 on 2021-09-16 at 16:49:48Made available in DSpace on 2021-09-17T01:13:35Z (GMT). No. of bitstreams: 2
CHU-THESIS-2021.pdf: 824475 bytes, checksum: de457f108dcae36c437741ca68b36e79 (MD5)
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Previous issue date: 2021-04-3
FACTS: Fully Automatic CT Segmentation of a Hip Joint
No full textExtraction of surface models of a hip joint from CT data is a pre-requisite step for computer assisted diagnosis and planning (CADP) of periacetabular osteotomy (PAO). Most of existing CADP systems are based on manual segmentation, which is time-consuming and hard to achieve reproducible results. In this paper, we present a Fully Automatic CT Segmentation (FACTS) approach to simultaneously extract both pelvic and femoral models. Our approach works by combining fast random forest (RF) regression based landmark detection, multi-atlas based segmentation, with articulated statistical shape model (aSSM) based fitting. The two fundamental contributions of our approach are: (1) an improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the multi-atlas based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 6-fold cross validation. When the present approach was compared to manual segmentation, a mean segmentation accuracy of 0.40, 0.36, and 0.36 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. When the models derived from both segmentations were used to compute the PAO diagnosis parameters, a difference of 2.0 ± 1.5°, 2.1 ± 1.6°, and 3.5 ± 2.3% were found for anteversion, inclination, and acetabular coverage, respectively. The achieved accuracy is regarded as clinically accurate enough for our target applications
[CT and MR imaging follow-up of medically treated acute aortic syndrome].
No full textInternational audienceThe follow-up of medically treated acute aortic syndromes relies on CT and MR imaging. Comparison with prior examinations is essential. For aortic dissections, progressive enlargement of the false lumen, visceral hypoperfusion, and extension should be excluded. Mural hematomas and ulcers also undergo close follow-up to detect progression and recanalization. It is important to be familiar with the risk factors of disease progression for medically treated acute aortic syndromes and their management. It is also important to be familiar with the imaging features of disease progression. Acute aortic syndromes managed medically should undergo routine follow-up with CT or MR because these lesions may evolve silently over time and present with complications
MASCG: Multi-Atlas Segmentation Constrained Graph method for accurate segmentation of hip CT images
No full textThis paper addresses the issue of fully automatic segmentation of a hip CT image with the goal to preserve the joint structure for clinical applications in hip disease diagnosis and treatment. For this purpose, we propose a Multi-Atlas Segmentation Constrained Graph (MASCG) method. The MASCG method uses multi-atlas based mesh fusion results to initialize a bone sheetness based multi-label graph cut for an accurate hip CT segmentation which has the inherent advantage of automatic separation of the pelvic region from the bilateral proximal femoral regions. We then introduce a graph cut constrained graph search algorithm to further improve the segmentation accuracy around the bilateral hip joint regions. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 15-fold cross validation. When the present approach was compared to manual segmentation, an average surface distance error of 0.30 mm, 0.29 mm, and 0.30 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. A further look at the bilateral hip joint regions demonstrated an average surface distance error of 0.16 mm, 0.21 mm and 0.20 mm for the acetabulum, the left femoral head, and the right femoral head, respectively
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