Development of computer vision algorithms for tissue identification and segmentation in medical ultrasound images

开发用于医学超声图像中组织识别和分割的计算机视觉算法

• 批准号: 238766-2006
• 负责人: Linney, Norma
• 金额: $ 0.73万
• 依托单位: Saint Mary's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=394051
• 关键词: Development; computer; vision; algorithms; tissue

Ultrasound is one of the more patient friendly medical imaging modalities. It is the modality of choice for infants as the equipment can be brought to the bassinette or incubator and administered with minimal disturbance or side effects to the infant. Similarly the equipment can easily be brought to adult patients and the procedure is well tolerated by the extremely ill. However, ultrasound images contain speckle and noise making the extraction of diagnostic information from these images more challenging than for other imaging modalities. The goal of this research project is to develop automated software tools that will help the physician extract relevant diagnostic information from these ultrasound images. In particular to develop an automated technique for the identification and characterization of tissue types so that ultimately healthy tissue can be reliably distinguished from unhealthy tissue. Improving the viability of using a more patient friendly imaging modality while still achieving the same or better clinical results will have a significant impact on patient health and health care costs.

超声是对患者更友好的医学成像方式之一。它是婴儿的首选方式，因为可以将设备带到摇篮或保温箱中并在对婴儿的干扰或副作用最小的情况下进行管理。同样，该设备可以很容易地带给成年患者，并且病情危重的患者也能很好地耐受该手术。然而，超声图像包含斑点和噪声，使得从这些图像中提取诊断信息比其他成像方式更具挑战性。该研究项目的目标是开发自动化软件工具，帮助医生从这些超声图像中提取相关的诊断信息。特别是开发一种用于识别和表征组织类型的自动化技术，以便最终能够可靠地区分健康组织与不健康组织。提高使用对患者更友好的成像方式的可行性，同时仍然实现相同或更好的临床结果将对患者健康和医疗保健成本产生重大影响。