Mir A H, Hanmandlu M, Tandon S N
Centre for Biomedical Engg. IIT Delhi, New Delhi, India.
Biomed Sci Instrum. 1995;31:213-7.
In certain medical images e.g., ultrasound it has been seen that the texture conveys useful diagnostic information but in CT and MR images its proper use has not been established. Present study is an attempt to investigate the use of texture analysis for early detection of liver malignancy when the onset of disease is beyond human perception, using CT-images. Using grey level run length as a primitive, five parameters viz., Short Run Emphasis (SRE), Long Run Emphasis (LRE), Grey Level Distribution (GLD), Run Length Distribution (RLD) and Run Percentage (RP) have been studied for this purpose. It has been found that the GLD feature, obtained using Grey Level Run Length Method (GLRLM) conveys useful information about the onset of this disease with a confidence level of above 99 percent. The results have been confirmed on the basis of clinical studies.
在某些医学图像中，例如超声图像，已经发现纹理传达了有用的诊断信息，但在CT和MR图像中，其合理应用尚未确立。本研究旨在利用CT图像，在疾病发作超出人类感知范围时，探讨纹理分析在早期检测肝脏恶性肿瘤中的应用。为此，以灰度游程长度为基本特征，研究了五个参数，即短游程强调（SRE）、长游程强调（LRE）、灰度分布（GLD）、游程长度分布（RLD）和游程百分比（RP）。研究发现，使用灰度游程长度方法（GLRLM）获得的GLD特征以高于99%的置信水平传达了有关该疾病发作的有用信息。研究结果已在临床研究的基础上得到证实。
