首页> 外文会议>Image Perception, Observer Performance, and Technology Assessment; Progress in Biomedical Optics and Imaging; vol.7 no.32 >Observer Efficiency in Boundary Discrimination Tasks Related to Assessment of Breast Lesions with Ultrasound
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Observer Efficiency in Boundary Discrimination Tasks Related to Assessment of Breast Lesions with Ultrasound

机译:与超声评估乳房病变相关的边界区分任务中的观察员效率

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The statistical efficiency of human observers in diagnostic tasks is an important measure of how effectively task relevant information in the image is being utilized. Most efficiency studies have investigated efficiency in terms of contrast or size effects. In many cases, malignant lesions will have similar contrast to normal or benign objects, but can be distinguished by properties of their boundary. We investigate this issue in the framework of malignant/benign discrimination tasks for the breast with ultrasound. In order to identify effects in terms of specific features and to control for other effects such as aberration or specular reflections, we simulate the formation of beam-formed radio-frequency (RF) data. We consider three tasks related to lesion boundaries including boundary eccentricity, boundary sharpness, and detection of boundary spiculations. We also consider standard detection and contrast discrimination tasks. We find that human observers exhibit surprisingly low efficiency with respect to the Ideal observer acting on RF data in boundary discrimination tasks (0.08%-3.3%), and that efficiency of human observers is substantially increased by Wiener-filtering RF frame data. We also find a limitation in efficiency is the computation of an envelope image from the RF data recorded by the transducer. Approximations to the Ideal observer acting on the envelope images indicate that humans may be substantially more efficient (10%-75%) with respect to the envelope Ideal observers. Our work suggests that significant diagnostic information may be lost in standard envelope processing in the formation of ultrasonic images.
机译:人类观察者在诊断任务中的统计效率是有效利用图像中任务相关信息的重要指标。大多数效率研究都从对比度或尺寸影响方面研究了效率。在许多情况下,恶性病变与正常或良性对象的对比度相似,但可以通过其边界的性质加以区分。我们在超声对乳房的恶性/良性歧视任务的框架内调查此问题。为了识别特定特征的影响并控制像差或镜面反射等其他影响,我们模拟了波束形成的射频(RF)数据的形成。我们考虑了与病变边界相关的三个任务,包括边界偏心率,边界清晰度和边界斑点的检测。我们还考虑标准检测和对比鉴别任务。我们发现,相对于在边界判别任务中作用于RF数据的理想观察者而言,人类观察者表现出令人惊讶的低效率(0.08%-3.3%),并且通过维纳滤波RF帧数据大大提高了人类观察者的效率。我们还发现效率方面的限制是根据换能器记录的RF数据计算包络图像。作用于信封图像上的理想观察者的近似值表明,相对于信封理想观察者而言,人类的效率可能更高(10%-75%)。我们的工作表明,在超声图像形成过程中,标准包络处理中可能会丢失大量诊断信息。

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