Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.

/pdf/deformable-medical-image-registration-a-survey-2uee59wp1z.pdf

Deformable Medical Image Registration: A Survey

Radiographic image guidance has emerged as the new paradigm for patient positioning, target localization, and external beam alignment in radiotherapy. Although widely varied in modality and method, all radiographic guidance techniques have one thing in common—they can give a significant radiation dose to the patient. As with all medical uses of ionizing radiation, the general view is that this exposure should be carefully managed. The philosophy for dose management adopted by the diagnostic imaging community is summarized by the acronym ALARA, i.e., as low as reasonably achievable. But unlike the general situation with diagnostic imaging and image-guided surgery, image-guided radiotherapy (IGRT) adds the imaging dose to an already high level of therapeutic radiation. There is furthermore an interplay between increased imaging and improved therapeutic dose conformity that suggests the possibility of optimizing rather than simply minimizing the imaging dose. For this reason, the management of imaging dose during radiotherapy is a different problem than its management during routine diagnostic or image-guided surgical procedures. The imaging dose received as part of a radiotherapy treatment has long been regarded as negligible and thus has been quantified in a fairly loose manner. On the other hand, radiation oncologists examine the therapy dose distribution in minute detail. The introduction of more intensive imaging procedures for IGRT now obligates the clinician to evaluate therapeutic and imaging doses in a more balanced manner. This task group is charged with addressing the issue of radiation dose delivered via image guidance techniques during radiotherapy. The group has developed this charge into three objectives: (1) Compile an overview of image-guidance techniques and their associated radiation dose levels, to provide the clinician using a particular set of image guidance techniques with enough data to estimate the total diagnostic dose for a specific treatment scenario, (2) identify ways to reduce the total imaging dose without sacrificing essential imaging information, and (3) recommend optimization strategies to trade off imaging dose with improvements in therapeutic dose delivery. The end goal is to enable the design of image guidance regimens that are as effective and efficient as possible.

http://www.people.vcu.edu/%7Emjmurphy/publications/TG75_medphys.pdf

The management of imaging dose during image-guided radiotherapy: Report of the AAPM Task Group 75

Records from the Multiple-Institution Database for Investigating Engineering Longitudinal Development indicate that engineering students are typical of students in other majors with respect to: persistence in major; persistence by gender and ethnicity; racial/ethnic distribution; and grade distribution. Data from the National Survey of Student Engagement show that this similarity extends to engagement outcomes including course challenge, faculty interaction, satisfaction with institution, and overall satisfaction. Engineering differs from other majors most notably by a dearth of female students and a low rate of migration into the major. Noting the similarity of students of engineering and other majors with respect to persistence and engagement, we propose that engagement is a precursor to persistence. We explore this hypothesis using data from the Academic Pathways Study of the Center for the Advancement of Engineering Education. Further exploration reveals that although persistence and engagement do not vary as much as expected by discipline, there is significant institutional variation, and we assert a need to address persistence and engagement at the institutional level and throughout higher education. Finally, our findings highlight the potential of making the study of engineering more attractive to qualified students. Our findings suggest that a two-pronged approach holds the greatest potential for increasing the number of students graduating with engineering degrees: identify programming that retains the students who come to college committed to an engineering major, and develop programming and policies that allow other students to migrate in. There is already considerable discourse on persistence, so our findings suggest that more research focus is needed on the pathways into engineering, including pathways from other majors.

/pdf/persistence-engagement-and-migration-in-engineering-programs-24pd2scquw.pdf

Persistence, Engagement, and Migration in Engineering Programs

Overview of image-guided radiation therapy.

Background

As estimates continue to indicate a growing demand for engineering professionals, retention in engineering remains an issue. Thus, the engineering education community remains concerned about students who leave engineering and must work to identify the factors that influence those students’ decisions.



Purpose (Hypothesis)

Our purpose was to identify a set of factors describing the experiences of students’ in a college of engineering that are strong influences on decisions to leave and study how those factors are related to both predictor variables (e.g., high school preparation) and future behaviors (e.g., new major chosen).



Design/Method

We solicited survey data from students who had recently transferred out of a large engineering college. We conducted exploratory factor analysis to determine the main factors for leaving engineering and then used these factors to answer the research questions.



Results

Results indicate that both academic (e.g., curriculum difficulty and poor teaching and advising) and a non-academic factor (lack of belonging in engineering) contribute to students’ decisions to leave engineering. We did find differences for some factors between majority and non-majority students; however, there were no gender differences.



Conclusions

Both academic and non-academic factors contribute to students’ decisions to leave engineering; however, our sample indicated the non-academic factors may be a stronger influence. Implications for educators focus on addressing both academic and the belonging factor and include examining pedagogical activities that may be less welcoming to a wide variety of student groups, providing opportunities for meaningful faculty interaction and other activities designed to support students pursuing engineering degrees.

Leaving Engineering: A Multi‐Year Single Institution Study

Pre-existing factors are quantitatively evaluated as to their impact on engineering student success. This study uses a database of all engineering students at nine institutions from 1987 through 2002 (a total of 87,167 engineering students) and focuses on graduation in any of the engineering disciplines. We report graduation rate as a function of years since matriculation, and determine the typical time-to-graduation. A multiple logistic regression model is fitted to each institution's data to explore the relationship between graduation and demographic and academic characteristics. A pooled model is fitted to six institutions where a complete data set was available. High school GPA, gender, ethnicity, quantitative SAT scores, verbal SAT scores, and citizenship had significant impact on graduation. While HSGPA, SATQ were significant for all models tested, the significance of other predictors varied among institutions. These studies add to the existing body of research about factors affecting the success of engineering students.

Identifying Factors Influencing Engineering Student Graduation: A Longitudinal and Cross‐Institutional Study

Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case.

Model-based image reconstruction for four-dimensional PET

Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast-to-noise ratios (CNRs). We propose a corrective algorithm, coined 'retrospective stacking' (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b-spline deformable image registration to combine amplitude-binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as to {sup 18}FDG-PET images of a pancreatic and a liver patient. Comparisons were made using cross-section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three-fold over gated images, and up to five-fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.

Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking

Four-dimensional (4D) CT is useful in many clinical situations, where detailed abdominal and thoracic imaging is needed over the course of the respiratory cycle. However, it usually delivers a larger radiation dose than the standard three-dimensional (3D) CT, since multiple scans at each couch position are required in order to provide the temporal information. Our purpose in this work is to develop a method to perform 4D CT scans at relatively low current, hence reducing the radiation exposure of the patients. To deal with the increased statistical noise caused by the low current, we proposed a novel 4D penalized weighted least square (4D-PWLS) smoothing method, which can incorporate both spatial and phase information. The 4D images at different phases were registered to the same phase via a deformable model, thereby, a regularization term combining temporal and spatial neighbors can be designed for the 4D-PWLS objective function. The proposed method was tested with phantom experiments and a patient study, and superior noise suppression and resolution preservation were observed. A quantitative evaluation of the benefit of the proposed method to 4D radiotherapy and 4D PET/CT imaging are under investigation.

B. Thorndyke

Papers

Overview of image-guided radiation therapy.

Identifying Factors Influencing Engineering Student Graduation: A Longitudinal and Cross‐Institutional Study

Model-based image reconstruction for four-dimensional PET

Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking

Radiation dose reduction in four-dimensional computed tomography.