Similar image retrieval of breast masses on ultrasonography using subjective data and multidimensional scaling
Similar image retrieval of breast masses on ultrasonography using subjective data and multidimensional scaling
复制标题
使用主观数据和多维尺度进行超声乳腺肿块的相似图像检索
DOI：
10.1007/978-3-319-41546-8_6
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
and H.Fujita
中科院分区：
文献类型：
--
作者：
C.Muramatsu;T.Takahashi;T.Morita;T.Edno;and H.Fujita
Presentation of images similar to a new unknown lesion can be helpful in medical image diagnosis and treatment planning.我们一直在研究一种检索相关图像的方法，作为乳房 X 光检查和超声图像上乳腺肿块的诊断参考。为了检索视觉上相似的图像，由经验丰富的放射科医生确定肿块对的主观相似性，并通过使用多维尺度（MDS）对主观相似性空间进行建模来计算客观相似性度量。在本研究中，我们研究了基于 MDS 和人工神经网络的乳腺超声图像上肿块的相似性度量，并检验了其在图像检索中的有用性。对于 666 对质量，平均主观相似度与基于 MDS 的相似度测量之间的相关系数为 0.724。当检索一到五幅图像时，选择相关图像（即良性/恶性索引图像的病理匹配图像）的平均精度为 0.778，表明所提出的基于 MDS 的相似性度量的潜在效用。
Presentation of images similar to a new unknown lesion can be helpful in medical image diagnosis and treatment planning. We have been investigating a method to retrieve relevant images as a diagnostic reference for breast masses on mammograms and ultrasound images. For retrieval of visually similar images, subjective similarities for pairs of masses were determined by experienced radiologists, and objective similarity measures were computed by modeling the subjective similarity space using multidimensional scaling (MDS). In this study, we investigated the similarity measure for masses on breast ultrasound images based on MDS and an artificial neural network and examined its usefulness in image retrieval. For 666 pairs of masses, correlation coefficient between the average subjective similarities and the MDS-based similarity measure was 0.724. When one to five images were retrieved, average precision in selecting relevant images, i.e., pathology-matched images for benign/malignant index image, was 0.778, indicating the potential utility of the proposed MDS-based similarity measure.