Wang T C, Karayiannis N B
PCD R & D, U.S. Robotics, Skokie, IL 60077-2690, USA.
IEEE Trans Med Imaging. 1998 Aug;17(4):498-509. doi: 10.1109/42.730395.
This paper presents an approach for detecting microcalcifications in digital mammograms employing wavelet-based subband image decomposition. The microcalcifications appear in small clusters of few pixels with relatively high intensity compared with their neighboring pixels. These image features can be preserved by a detection system that employs a suitable image transform which can localize the signal characteristics in the original and the transform domain. Given that the microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands, suppressing the low-frequency subband, and, finally, reconstructing the mammogram from the subbands containing only high frequencies. Preliminary experiments indicate that further studies are needed to investigate the potential of wavelet-based subband image decomposition as a tool for detecting microcalcifications in digital mammograms.
本文提出了一种利用基于小波的子带图像分解来检测数字乳腺钼靶片中微钙化的方法。微钙化以少量像素的小簇形式出现，与相邻像素相比强度相对较高。这些图像特征可以通过一个检测系统来保留，该系统采用合适的图像变换，能够在原始域和变换域中定位信号特征。鉴于微钙化对应于图像频谱的高频分量，通过将乳腺钼靶片分解为不同的频率子带、抑制低频子带，最后从仅包含高频的子带中重建乳腺钼靶片来实现微钙化的检测。初步实验表明，需要进一步研究以探讨基于小波的子带图像分解作为检测数字乳腺钼靶片中微钙化工具的潜力。
