MedGIFT Group, Business Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.
Int J Comput Assist Radiol Surg. 2012 Jan;7(1):97-110. doi: 10.1007/s11548-011-0618-9. Epub 2011 Jun 1.
Clinical workflows and user interfaces of image-based computer-aided diagnosis (CAD) for interstitial lung diseases in high-resolution computed tomography are introduced and discussed.
Three use cases are implemented to assist students, radiologists, and physicians in the diagnosis workup of interstitial lung diseases.
In a first step, the proposed system shows a three-dimensional map of categorized lung tissue patterns with quantification of the diseases based on texture analysis of the lung parenchyma. Then, based on the proportions of abnormal and normal lung tissue as well as clinical data of the patients, retrieval of similar cases is enabled using a multimodal distance aggregating content-based image retrieval (CBIR) and text-based information search. The global system leads to a hybrid detection-CBIR-based CAD, where detection-based and CBIR-based CAD show to be complementary both on the user's side and on the algorithmic side.
The proposed approach is in accordance with the classical workflow of clinicians searching for similar cases in textbooks and personal collections. The developed system enables objective and customizable inter-case similarity assessment, and the performance measures obtained with a leave-one-patient-out cross-validation (LOPO CV) are representative of a clinical usage of the system.
介绍并讨论用于高分辨率计算机断层扫描的基于图像的计算机辅助诊断（CAD）的临床工作流程和用户界面，用于间质性肺疾病。
实现了三个用例，以协助学生、放射科医生和医生进行间质性肺疾病的诊断工作。
在第一步中，所提出的系统显示了基于肺实质纹理分析的分类肺组织模式的三维图谱，并对疾病进行量化。然后，根据异常和正常肺组织的比例以及患者的临床数据，使用多模态距离聚合基于内容的图像检索（CBIR）和基于文本的信息搜索来检索相似病例。全局系统导致基于混合检测-CBIR 的 CAD，其中基于检测和基于 CBIR 的 CAD 在用户和算法方面都具有互补性。
所提出的方法符合临床医生在教科书中和个人收藏中寻找相似病例的经典工作流程。所开发的系统能够实现客观和可定制的病例间相似性评估，并且使用Leave-One-Patient-Out 交叉验证（LOPO CV）获得的性能指标代表了系统的临床使用。
