Medical Image Compression

及时获得临床信息对于改进医疗保健决策至关重要。电子健康记录（EHR）通过提供对构成患者医疗记录的不同数据源的集中访问，承诺提供更好的护理。电子病历预计将通过及时获取信息来提高生产力，从而帮助实现更有效的卫生保健系统；预计它还将通过减少重复测试来帮助建立一个更有效的系统。医学图像是患者健康档案中非常重要的信息。通过加拿大健康信息之路对诊断成像项目的投资，医学图像被集中归档，以便于长期管理。大量医疗保健专业人员也可以共享和访问图像：临床医生将其作为患者随访和治疗的一部分；在创伤或偏远地区病例现场没有放射科医生时，由放射科医生提供第二意见或第一意见；或由专业医生，如外科医生或骨科医生，在计划外科手术或程序。医学图像的尺寸在不断增长。例如，计算机断层扫描（CT）可以生成一系列数千张大小超过千兆字节的图像。在通信网络上传输大图像集需要巨大的带宽，导致系统效率低下和不完备。图像可以在没有信息丢失的情况下进行压缩，将其大小减少30%。需要进一步压缩，但目前可用的方法会引入可能影响诊断准确性的伪影和失真。在本研究计划中，我们提出定量评估压缩方法对医学图像诊断价值的影响。我们还建议开发新的压缩方案，专门用于保留诊断价值。因此，我们希望减少传输医学图像所需的带宽，同时保留其诊断价值。

Prompt access to clinical information is crucial for improved healthcare decisions. The Electronic Health Record (EHR) promises better care by providing centralized access to the different sources of data that make up the patient's medical record. EHR is expected to help achieve a more efficient health-care system by enhancing productivity through timely access to information; it is also expected to help achieve a more effective system by reducing the duplication of tests. Medical images are very important information in the patient's health record. With Canada Health Infoway's investment in diagnostic imaging projects, medical images are centrally archived for easier long-term management. Images are also being shared and accessed by a very large number of healthcare professionals: by clinicians as part of a patient's follow-up and treatment; by radiologists to provide second opinions or first opinions when no radiologists are on site for trauma or remote-area cases; or by specialized physicians, such as surgeons or orthopedists, in planning surgical operations or procedures. The size of medical images is continuously growing. Computed Tomography (CT), for example, can generate a series of thousands of images whose size exceeds the gigabyte. Transferring large image sets on a communication network requires an enormous bandwidth, resulting in an inefficient and inadequate system. Images can be compressed with no information loss, reducing their size by 30%. Further compressing is needed, but currently available methods introduce artifacts and distortions that may impact diagnostic accuracy. In this research program, we propose to quantitatively assess the impact of compression methods on the diagnostic value of medical images. We also propose to develop novel compression schemes specially tailored to preserve that diagnostic value. Therefore, we expect to reduce the bandwidth needed to transfer medical images while preserving their diagnostic value.