Clinical Image Retrieval: User needs assessment toolbox development & evaluation

临床图像检索：用户需求评估工具箱开发

• 批准号: 8299311
• 负责人: Jayashree Kalpathy-Cramer
• 金额: $ 23.94万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2014-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8299311
• 关键词: Accounting; Address; Affinity; Algorithms; Anatomy; Applications Grants; Archives; Area; Award; Back; Characteristics; Clinical; Communication; Communities; Computer software; Data; Development; Development Plans; Diagnosis; Diagnostic Imaging; Diffusion; Distance Learning; Education; Educational process of instructing; Effectiveness; Evaluation; Feedback; Goals; Gold; Growth; Head and Neck Cancer; Health Sciences; Healthcare; Hospitals; Image; Image retrieval system; Imaging technology; Information Retrieval; Internet; Interview; Judgment; Learning; Libraries; Link; Lung; Machine Learning; Maps; Measures; Medical; Medical Imaging; Medical Informatics; Medicine; Mentors; Mentorship; Methodology; Methods; Metric System; Multimodal Imaging; National Cancer Institute; Natural Language Processing; Nature; Needs Assessment; Online Systems; Ontology; Oregon; Output; Participant; Pathology; Pathology Report; Pathway interactions; Patients; Performance; Play; Postdoctoral Fellow; Principal Investigator; Process; Property; Quality Control; Radiation; Radiation Oncology; Recruitment Activity; Reporting; Research; Research Personnel; Retrieval; Role; Semantics; Site; Staging; Structure; Students; Surveys; System; Techniques; Technology; Testing; Text; Training; United States National Institutes of Health; Universities; Visual; Vocabulary; Work; Writing; base; biomedical informatics; cancer site; care delivery; career development; data mining; digital imaging; experience; follow-up; image processing; improved; information model; meetings; oncology; open source; satisfaction; skills; success; tool; treatment planning; visual information

DESCRIPTION (provided by applicant): Advances in digital imaging technologies have led to a substantial growth in the number of digital images being created and stored in hospitals, medical systems, and on the Internet in recent years. Effective medical image retrieval systems can play an important role in teaching, research, diagnosis and treatment. Images were historically retrieved using text-based methods. The quality of annotations associated with images can reduce the effectiveness of text-based image retrieval. Despite recent advances, purely content- based image retrieval techniques lag significantly behind their textual counterparts in their ability to capture the semantic essence of the user's query. Preliminary research suggests that a more promising approach is to adaptively combine these complementary techniques to suit the user and their information needs. However, for these approaches to succeed, the researcher needs to enhance her computational skills in addition to acquiring a comprehensive understanding of the relevant clinical domain. This Pathway to Independence (K99/R00) grant application describes a training and career development plan that will allow the candidate, an NLM postdoctoral fellow in Medical Informatics at Oregon Health & Science University to achieve these objectives. The training component will be carried out under the mentorship of Dr. W. Hersh with Dr. Gorman (user studies). Dr. Fuss (radiation medicine) and Dr. Erdogmus (machine learning) providing additional mentoring in their areas of expertise. The long-term goal of this Pathway to Independence (K99/R00) project is to improve visual information retrieval by better understanding user needs and proposing adaptive methodologies for multimodal image retrieval that will close the semantic gap. During the award period, activities will be focused on the following specific aims: (1) Understand the image retrieval needs of novice and expert users in radiation oncology and develop gold standards for evaluation; (2) Develop algorithms for semantic, multimodal image retrieval; (3) Perform user based evaluation of adaptive image retrieval in radiation oncology; (4) Extend the techniques developed to create a multimodal image retrieval system in pathology

描述（由申请人提供）：