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1.
J Appl Clin Med Phys ; 23(9): e13731, 2022 Sep.
Article in English | MEDLINE | ID: mdl-35920116

ABSTRACT

Accurate coregistration of computed tomography (CT) and magnetic resonance (MR) imaging can provide clinically relevant and complementary information and can serve to facilitate multiple clinical tasks including surgical and radiation treatment planning, and generating a virtual Positron Emission Tomography (PET)/MR for the sites that do not have a PET/MR system available. Despite the long-standing interest in multimodality co-registration, a robust, routine clinical solution remains an unmet need. Part of the challenge may be the use of mutual information (MI) maximization and local phase difference (LPD) as similarity metrics, which have limited robustness, efficiency, and are difficult to optimize. Accordingly, we propose registering MR to CT by mapping the MR to a synthetic CT intermediate (sCT) and further using it in a sCT-CT deformable image registration (DIR) that minimizes the sum of squared differences. The resultant deformation field of a sCT-CT DIR is applied to the MRI to register it with the CT. Twenty-five sets of abdominopelvic imaging data are used for evaluation. The proposed method is compared to standard MI- and LPD-based methods, and the multimodality DIR provided by a state of the art, commercially available FDA-cleared clinical software package. The results are compared using global similarity metrics, Modified Hausdorff Distance, and Dice Similarity Index on six structures. Further, four physicians visually assessed and scored registered images for their registration accuracy. As evident from both quantitative and qualitative evaluation, the proposed method achieved registration accuracy superior to LPD- and MI-based methods and can refine the results of the commercial package DIR when using its results as a starting point. Supported by these, this manuscript concludes the proposed registration method is more robust, accurate, and efficient than the MI- and LPD-based methods.


Subject(s)
Magnetic Resonance Imaging , Tomography, X-Ray Computed , Algorithms , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Multimodal Imaging , Positron-Emission Tomography , Tomography, X-Ray Computed/methods
2.
J Nurs Educ ; 45(6): 229-32, 2006 06.
Article in English | MEDLINE | ID: mdl-16780011

ABSTRACT

Nursing students frequently have difficulty understanding diabetes mellitus and other chronic illnesses. Using the active learning technique of the case study method enables students to understand the difficulty in taking care of clients with chronic illnesses. Three forms of the case study method are shared. The students are enlightened about clients' difficulty in taking care of themselves after the diagnosis of a chronic illness. The case study method is leveled and used to develop critical thinking by focusing on the client's needs and collaborating to solve problems. This enables students to develop a clearer understanding of the disease, how it affects clients and their needs, and responses to studies of the disease.


Subject(s)
Diabetes Mellitus, Type 1/nursing , Education, Nursing, Baccalaureate/methods , Nursing Process , Nursing Records , Problem Solving , Students, Nursing/psychology , Adaptation, Psychological , Adult , Attitude to Health , Chronic Disease , Clinical Competence , Decision Making , Diabetes Mellitus, Type 1/psychology , Drug Monitoring , Empathy , Health Services Needs and Demand , Humans , Life Style , Male , Patient Education as Topic , Problem-Based Learning/methods , Thinking
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