期刊
PROCEEDINGS OF THE IEEE
卷 100, 期 4, 页码 991-1003出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JPROC.2011.2182074
关键词
Biomedical imaging; biomedical informatics; digital pathology; image analysis; virtual microscopy
资金
- SAIC/NCI from National Cancer Institute [HHSN261200800001E, N01-CO-12400]
- National Heart Lung and Blood Institute [R24HL085343]
- National Library of Medicine [1R01LM011119-01, R01LM009239]
- National Institutes of Health [RC4MD005964]
- PHS [UL1RR025008]
- Biomedical Information Science and Technology Initiative [P20 EB000591]
Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications. Pathology has lagged behind other healthcare practices such as radiology where digital adoption is widespread. As devices that generate whole slide images become more practical and affordable, practices will increasingly adopt this technology and eventually produce an explosion of data that will quickly eclipse the already vast quantities of radiology imaging data. These advances are accompanied by significant challenges for data management and storage, but they also introduce new opportunities to improve patient care by streamlining and standardizing diagnostic approaches and uncovering disease mechanisms. Computer-based image analysis is already available in commercial diagnostic systems, but further advances in image analysis algorithms are warranted in order to fully realize the benefits of digital pathology in medical discovery and patient care. In coming decades, pathology image analysis will extend beyond the streamlining of diagnostic workflows and minimizing interobserver variability and will begin to provide diagnostic assistance, identify therapeutic targets, and predict patient outcomes and therapeutic responses.
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