Geiser E A, Oliver L H, Gardin J M, Kerber R E, Parisi A F, Reichek N, Werner J A, Weyman A E
College of Medicine, University of Florida, Gainesville 32610.
J Am Soc Echocardiogr. 1988 Nov-Dec;1(6):410-21. doi: 10.1016/s0894-7317(88)80023-3.
The purpose of this study was to validate an edge detection algorithm for short-axis two-dimensional echocardiographic studies in a protocol that stimulated its implementation at multiple clinical laboratories. Six short-axis two-dimensional echocardiographic studies were solicited from each of five clinical laboratories. A single cardiac cycle from each of the resulting 30 studies was entered into the computer system. Five expert observers came to the laboratory on separate occasions and traced endocardial borders from the short-axis studies on 2 separate days. The computer algorithm generated borders on each frame of the cardiac cycles on the basis of regions of search defined by the observers. Of the 30 original studies, five were considered excellent, seven were good, nine were poor, and nine were technically inadequate by consensus of the five observers. The correlation coefficient for computer-defined borders with manually defined borders in the excellent quality studies was 0.985. Interobserver variability was expressed as the mean percent area difference for all possible pairings of observers. The mean percent area differences were decreased from +/- 9.8% to +/- 5.3%, +/- 12.5% to +/- 8.4%, and +/- 17.4% to +/- 15.6% when comparing observer with computer-generated borders in the excellent, good, and poor quality studies, respectively. Intraobserver variability was expressed as decrease in mean percent area difference on corresponding frames between days 1 and 2. Intraobserver variability was decreased from +/- 6.5% to +/- 4.5%, +/- 10.8% to +/- 7.0%, and +/- 14.0% to +/- 11.9%, respectively. All reductions in variability were statistically significant at p less than 0.01. Observer acceptance of computer-defined borders was estimated at 94%, 93%, and 97% for excellent, good, and poor quality studies, respectively. Once the observer defined a region of search, computer process time to generate all borders in the cardiac cycle was approximately 4 minutes. The conclusion is that the algorithm produces accurate, reliable, and acceptable borders.
本研究的目的是在一项促使其在多个临床实验室实施的方案中，验证一种用于短轴二维超声心动图研究的边缘检测算法。从五个临床实验室中的每个实验室征集了六项短轴二维超声心动图研究。将由此得到的30项研究中的每项研究的单个心动周期输入计算机系统。五名专家观察者在不同时间来到实验室，并在两天内从短轴研究中追踪心内膜边界。计算机算法根据观察者定义的搜索区域在心动周期的每一帧上生成边界。在这30项原始研究中，经五名观察者一致认定，五项为优秀，七项为良好，九项为较差，九项在技术上不充分。在质量优秀的研究中，计算机定义的边界与手动定义的边界之间的相关系数为0.985。观察者间的变异性表示为所有可能的观察者配对的平均面积差异百分比。在质量优秀、良好和较差的研究中，将观察者与计算机生成的边界进行比较时，平均面积差异百分比分别从±9.8%降至±5.3%、±12.5%降至±8.4%、±17.4%降至±15.6%。观察者内的变异性表示为第1天和第2天相应帧上平均面积差异百分比的降低。观察者内的变异性分别从±6.5%降至±4.5%、±10.8%降至±7.0%、±14.0%降至±11.9%。所有变异性的降低在p小于0.01时均具有统计学意义。在质量优秀、良好和较差的研究中，观察者对计算机定义边界的接受率分别估计为94%、93%和97%。一旦观察者定义了搜索区域，计算机生成心动周期中所有边界的处理时间约为4分钟。结论是该算法能产生准确、可靠且可接受的边界。
