Using Signal-To-Noise Ratio to Connect the Quality Assessment Of Natural and Medical Images
文献类型：会议论文
| 作者 | Yaoqin Xiea; Zhaoyang Wang; Guangzhe Dai; Ruoyu Li; Shaode Yu |
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 英文摘要 | Medical image quality assessment (MIQA) is highly related to content interpretation and disease diagnosis in medical community. However, a few metrics have been developed. On the contrary, massive models have been designed for natural image quality assessment (NIQA) in the field of computer vision. Connect both sides of MIQA and NIQA is useful and challenging. This study explores signal-to-noise ratio (SNR) as the intermediate metric to bridge the gap between MIQA and NIQA and consequently, models for NIQA can be employed or modified for MIQA applications. A number of 411 images from 4 magnetic resonance (MR) imaging sequences are collected. First, the consistency of SNR in MIQA is validated which involves inter-rater and intra-rater (inter-session) reliability analysis. Then, 4 NIQA models (BIQI, BLIINDS-II, BRISQUE and NIQE) are evaluated on these MR images. After that, the correlation between SNR values and NIQA results are analyzed. Statistical analysis indicates that SNR measurement shows reliability regard to different raters in each sequence. Moreover, BLIINDS-II and BRISQUE have the potential for automated MIQA tasks. This study attempts to use SNR bridging the gap between MIQA and NIQA, and a large-scale experiment should be further conducted to verify the conclusion. |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14491]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 推荐引用方式 GB/T 7714 | Yaoqin Xiea,Zhaoyang Wang,Guangzhe Dai,et al. Using Signal-To-Noise Ratio to Connect the Quality Assessment Of Natural and Medical Images[C]. 见:. 2018. |
入库方式： OAI收割
来源：深圳先进技术研究院
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