CADBOSS: A computer-aided diagnosis system for whole-body bone scintigraphy scans
CADBOSS: A computer-aided diagnosis system for whole-body bone scintigraphy scans
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DOI：
10.4103/0973-1482.150422
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发表时间：
2016-04-01
影响因子：
1.3
通讯作者：
Cakiroglu, Murat
中科院分区：
文献类型：
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作者：
Dandil, Ali Aslantas Emre;Saglam, Semahat;Cakiroglu, Murat
目的：本研究的目的是开发一个骨显像扫描的计算机辅助诊断系统。(CADBOSS)。CADBOSS检测肿瘤转移的成功率高。CADBOSS的主要目的是作为辅助软件，以方便医生的决策。材料与方法：CADBOSS由热点分割、特征提取/选择、分类等多个要素组成。采用水平集主动轮廓分割算法进行热点检测。此外，提出了一种新的图像网格化方法用于转移区域的特征提取。使用人工神经网络分类器来确定是否存在转移。利用包含130张图像的图像数据库对CADBOSS进行性能评价。（30例非转移和100例转移）收集自60名志愿者。在患者体内注入少量放射性物质99mTc-MDP，然后用伽马相机扫描，在大约3小时内获得所有图像。所有试验均采用10倍交叉验证技术。结果：CADBOSS能正确识别130张图像中的120张。因此，CADBOSS的准确性、敏感性和特异性分别为92.30%、94%和86.67%。此外，CADBOSS将医生发现转移的成功率从95.38%提高到96.9%。结论：详细的实验表明，CADBOSS优于最先进的计算机辅助诊断。（CAD）系统，合理地提高了医生的诊断成功率。
Aims: The aim of this study is to develop a computer-aided diagnosis system for bone scintigraphy scans. (CADBOSS). CADBOSS can detect metastases with a high success rates. The primary purpose of CADBOSS is as supplementary software to facilitate physician's decision making. Materials and Methods: CADBOSS consists of various elements, such as hotspot segmentation, feature extraction/selection and classification. A level set active contour segmentation algorithm was used for the detection of hotspots. Moreover, a novel image gridding method was proposed for feature extraction of metastatic regions. An artificial neural network classifier was used to determine whether metastases were present. Performance evaluation of CADBOSS was performed with the help of an image database which included 130 images. (30 non-metastases and 100 metastases) collected from 60 volunteers. All images were obtained within approximately 3 hours after injecting a small amount of radioactive material 99mTc-MDP into the patients and then carrying out scanning with a gamma camera. The 10-fold cross-validation technique was used for all tests. Results: CADBOSS could correctly identify in 120 out of 130 images. Thus, the accuracy, sensitivity, and specificity of CADBOSS were 92.30%, 94%, and 86.67%, respectively. Moreover, CADBOSS increased physician's success in detecting metastases from 95.38% to 96.9%. Conclusions: Detailed experiments showed that CADBOSS outperforms state-of-the-art computer-aided diagnosis. (CAD) systems and reasonably improves physician' diagnostic success.