Demi M
CNR Institute of Clinical Physiology, Pisa, Italy.
Comput Biomed Res. 1994 Jun;27(3):157-77. doi: 10.1006/cbmr.1994.1015.
A procedure for detecting contours automatically is particularly needed when processing sequences of cardiographic images. In fact, in this field the number of images to be processed is, in general, large enough to make a manual tracing phase unacceptable. In this paper a new approach to automatic contour detection from image sequences is presented. If a rough contour of the desired structure is available on the first frame, every contour of the sequence is automatically outlined. The entire process is based on two main steps carried out in turn. First, an image is convolved with a mask of suitable size in order to transform any discontinuity, such as the boundary of the structure one is looking for, into a furrow of suitable width. Second, every point of a given starting contour, which is entirely contained inside the furrow, is made to fall to the bottom of the furrow by means of a localization algorithm.
在处理心电图图像序列时，特别需要一种自动检测轮廓的程序。实际上，在该领域中，通常需要处理的图像数量足够多，以至于人工追踪阶段是不可接受的。本文提出了一种从图像序列中自动检测轮廓的新方法。如果在第一帧上有所需结构的粗略轮廓，那么该序列的每个轮廓都会被自动勾勒出来。整个过程基于依次执行的两个主要步骤。首先，将图像与合适大小的模板进行卷积，以便将任何不连续性（例如正在寻找的结构的边界）转换为具有合适宽度的沟槽。其次，通过定位算法使完全包含在沟槽内的给定起始轮廓的每个点落到沟槽底部。
